R8: R for Molecular Biology

Molecular biology

FASTA

Regular expressions

Sequence analysis

seqinr

rentrez

Bioconductor

Author

Modesto

Published

August 17, 2023

Modified

August 18, 2026

Warning: package 'formatR' was built under R version 4.6.1

Warning: package 'webexercises' was built under R version 4.6.1

1 Working with sequences

This lesson brings together several ideas from previous topics: importing files, working with character strings, subsetting objects, plotting results and writing functions. The biological context makes the examples more interesting, but also more demanding: we need to be clear about what is a header, what is a sequence, what is a match, and what kind of object each package returns.

The main idea of R8

R8 is about using R to explore molecular biology data. We will start with simple plain-text operations on FASTA files and then move to sequence-aware tools such as seqinr, database queries with rentrez, sequence visualisation and Bioconductor.

The key distinction is:

text tools such as grep() or sub() are useful for finding patterns in strings;
sequence packages such as seqinr or Bioconductor packages are useful for biological operations on sequence objects.

1.1 Regular expressions as a shortcut to explore sequences

Biological data, like protein or nucleic acid sequences can be stored and explored in different formats, each following its own structure. As you can imagine, that facilitates the use of regular expressions in any programming language to access that data. The use of regular expressions in R is similar to other languages, particularly, to the use you learnt in Python. Anyway, I suggest that you have a look to the References below.

Moreover, for advanced manipulation of string object, I’d advice the package Strings.

In the code below, we are going to use some simple regular expressions to explore and analyse the data in a multifasta file containing the whole proteome of the bacterium Bacillus thuringiensis HER1410 (HER1410.fasta) in our data folder, using grep(), substr(), sub(), and regexpr().

Remember the FASTA structure

A FASTA file is a plain-text file. Each sequence usually starts with a header line beginning with >, followed by one or more lines containing the sequence.

>protein_id description
MKKLIA...

This is why a simple pattern such as ">" can be used to count or extract sequence headers.

#read the text file with readLines()
proteome <- readLines("data/HER1410.fasta")
#number of sequences in the multifasta using grep
length(grep(proteome, pattern=">"))

[1] 5807

#extract recombinases
grep("recombinase", proteome,value=TRUE)

 [1] ">QKO37045.1 recombinase RecA (plasmid) [Bacillus thuringiensis]"                          
 [2] ">QKO36998.1 recombinase family protein (plasmid) [Bacillus thuringiensis]"                
 [3] ">QKO36701.1 DDE-type integrase/transposase/recombinase (plasmid) [Bacillus thuringiensis]"
 [4] ">QKO36696.1 tyrosine recombinase XerS (plasmid) [Bacillus thuringiensis]"                 
 [5] ">QKO36060.1 tyrosine-type recombinase/integrase [Bacillus thuringiensis]"                 
 [6] ">QKO36057.1 tyrosine-type recombinase/integrase [Bacillus thuringiensis]"                 
 [7] ">QKO35589.1 recombinase family protein [Bacillus thuringiensis]"                          
 [8] ">QKO35551.1 tyrosine-type recombinase/integrase [Bacillus thuringiensis]"                 
 [9] ">QKO35280.1 recombinase family protein [Bacillus thuringiensis]"                          
[10] ">QKO34873.1 site-specific tyrosine recombinase XerD [Bacillus thuringiensis]"             
[11] ">QKO34618.1 tyrosine recombinase XerC [Bacillus thuringiensis]"                           
[12] ">QKO34567.1 recombinase RecA [Bacillus thuringiensis]"                                    
[13] ">QKO34482.1 recombinase family protein [Bacillus thuringiensis]"                          
[14] ">QKO32507.1 recombinase RecQ [Bacillus thuringiensis]"                                    
[15] ">QKO32484.1 tyrosine-type recombinase/integrase [Bacillus thuringiensis]"

#enzymes (aka "-ases")
head(grep("ase", proteome,value=TRUE))

[1] ">QKO37046.1 helicase DnaB (plasmid) [Bacillus x1]"                                
[2] ">QKO37045.1 recombinase RecA (plasmid) [Bacillus thuringiensis]"                  
[3] ">QKO37043.1 IS3 family transposase (plasmid) [Bacillus thuringiensis]"            
[4] ">QKO37040.1 serine acetyltransferase (plasmid) [Bacillus thuringiensis]"          
[5] ">QKO37039.1 O-antigen ligase family protein (plasmid) [Bacillus thuringiensis]"   
[6] ">QKO37026.1 HK97 family phage prohead protease (plasmid) [Bacillus thuringiensis]"

head(grep("ase", proteome,value=TRUE,ignore.case=TRUE)) #lower- & uppercase

[1] ">QKO37046.1 helicase DnaB (plasmid) [Bacillus x1]"                             
[2] ">QKO37045.1 recombinase RecA (plasmid) [Bacillus thuringiensis]"               
[3] ">QKO37043.1 IS3 family transposase (plasmid) [Bacillus thuringiensis]"         
[4] ">QKO37040.1 serine acetyltransferase (plasmid) [Bacillus thuringiensis]"       
[5] ">QKO37039.1 O-antigen ligase family protein (plasmid) [Bacillus thuringiensis]"
[6] "SMSCDIDPTEIITRLTPLGTRIESKNEGATDASEARLTIESVNNGVPYIDHPSGIKEFGIQGKSITWDDV"

#extract names
fastanames <- proteome[grep(proteome, pattern=">")] #extract the headers of all the sequences
names_ase <- fastanames[grep(fastanames, pattern="ase")]

Three useful string functions

grep(pattern, x) finds elements of x that match a pattern.
substr(x, start, stop) extracts characters by position.
sub(pattern, replacement, x) replaces the first match in each element.

These functions answer different questions. For example, if the protein ID always occupies positions 2 to 11 in the header, substr() is appropriate. If we want to remove the leading >, sub() is more appropriate.

Quick exercise: Using `sub()` and `substr()`.

How would you extract the NCBI protein ID of the enzymes?

sub(names_ase, 1,11) sub(names_ase, 2,11)) substr(names_ase, 1,11) substr(names_ase, 2,11)

   [1] "QKO37046.1" "QKO37045.1" "QKO37043.1" "QKO37040.1" "QKO37039.1"
   [6] "QKO37026.1" "QKO37024.1" "QKO37023.1" "QKO37022.1" "QKO37016.1"
  [11] "QKO37013.1" "QKO37011.1" "QKO37005.1" "QKO36998.1" "QKO36995.1"
  [16] "QKO36992.1" "QKO36990.1" "QKO36988.1" "QKO36987.1" "QKO36983.1"
  [21] "QKO36981.1" "QKO36979.1" "QKO36974.1" "QKO36973.1" "QKO36972.1"
  [26] "QKO36971.1" "QKO36970.1" "QKO36966.1" "QKO36958.1" "QKO36956.1"
  [31] "QKO36954.1" "QKO36952.1" "QKO36940.1" "QKO36939.1" "QKO36938.1"
  [36] "QKO36936.1" "QKO36935.1" "QKO36933.1" "QKO36932.1" "QKO36931.1"
  [41] "QKO36928.1" "QKO36927.1" "QKO36926.1" "QKO36924.1" "QKO36923.1"
  [46] "QKO36922.1" "QKO36921.1" "QKO36920.1" "QKO36918.1" "QKO36912.1"
  [51] "QKO36909.1" "QKO36907.1" "QKO36905.1" "QKO36904.1" "QKO36903.1"
  [56] "QKO36899.1" "QKO36897.1" "QKO36896.1" "QKO36894.1" "QKO36892.1"
  [61] "QKO36891.1" "QKO36890.1" "QKO36889.1" "QKO36887.1" "QKO36885.1"
  [66] "QKO36884.1" "QKO36883.1" "QKO36878.1" "QKO36875.1" "QKO36871.1"
  [71] "QKO36866.1" "QKO36864.1" "QKO36855.1" "QKO36853.1" "QKO36850.1"
  [76] "QKO36849.1" "QKO36848.1" "QKO36845.1" "QKO36844.1" "QKO36843.1"
  [81] "QKO36842.1" "QKO36841.1" "QKO36833.1" "QKO36832.1" "QKO36829.1"
  [86] "QKO36828.1" "QKO36822.1" "QKO36820.1" "QKO36814.1" "QKO36813.1"
  [91] "QKO36812.1" "QKO36808.1" "QKO36807.1" "QKO36806.1" "QKO36805.1"
  [96] "QKO36802.1" "QKO36796.1" "QKO36793.1" "QKO36791.1" "QKO36782.1"
--- Cropped output ---

How would you remove the `>’ from the fasta headers?

sub(names_ase, 2,11) sub(“>”,““,names_ase) substr(names_ase, 2,150)

   [1] "QKO37046.1 helicase DnaB (plasmid) [Bacillus x1]"                                                                                                             
   [2] "QKO37045.1 recombinase RecA (plasmid) [Bacillus thuringiensis]"                                                                                               
   [3] "QKO37043.1 IS3 family transposase (plasmid) [Bacillus thuringiensis]"                                                                                         
   [4] "QKO37040.1 serine acetyltransferase (plasmid) [Bacillus thuringiensis]"                                                                                       
   [5] "QKO37039.1 O-antigen ligase family protein (plasmid) [Bacillus thuringiensis]"                                                                                
   [6] "QKO37026.1 HK97 family phage prohead protease (plasmid) [Bacillus thuringiensis]"                                                                             
   [7] "QKO37024.1 terminase large subunit (plasmid) [Bacillus thuringiensis]"                                                                                        
   [8] "QKO37023.1 P27 family phage terminase small subunit (plasmid) [Bacillus thuringiensis]"                                                                       
   [9] "QKO37022.1 HNH endonuclease (plasmid) [Bacillus thuringiensis]"                                                                                               
  [10] "QKO37016.1 nuclease (plasmid) [Bacillus thuringiensis]"                                                                                                       
  [11] "QKO37013.1 DNA primase (plasmid) [Bacillus thuringiensis]"                                                                                                    
  [12] "QKO37011.1 AAA family ATPase (plasmid) [Bacillus thuringiensis]"                                                                                              
  [13] "QKO37005.1 sigma-70 family RNA polymerase sigma factor (plasmid) [Bacillus thuringiensis]"                                                                    
  [14] "QKO36998.1 recombinase family protein (plasmid) [Bacillus thuringiensis]"                                                                                     
  [15] "QKO36995.1 IS3 family transposase (plasmid) [Bacillus thuringiensis]"                                                                                         
  [16] "QKO36992.1 low molecular weight phosphotyrosine protein phosphatase (plasmid) [Bacillus thuringiensis]"                                                       
  [17] "QKO36990.1 cadmium-translocating P-type ATPase (plasmid) [Bacillus thuringiensis]"                                                                            
  [18] "QKO36988.1 lysoplasmalogenase (plasmid) [Bacillus thuringiensis]"                                                                                             
  [19] "QKO36987.1 signal peptidase I (plasmid) [Bacillus thuringiensis]"                                                                                             
  [20] "QKO36983.1 IS4 family transposase (plasmid) [Bacillus thuringiensis]"                                                                                         
--- Cropped output ---

What about `regexpr()`?

# regexpr() returns the position where the match begins.
# The match length is stored as an attribute.
# Here we search for headers containing the word "DNA".
r <- regexpr(pattern = "(.*)DNA(.*)", text = fastanames[1:200])
r

  [1] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
 [26] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
 [51] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
 [76] -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[101] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[126] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[151] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1  1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[176] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
attr(,"match.length")
  [1] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
 [26] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 58 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
 [51] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
 [76] -1 -1 95 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[101] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[126] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[151] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 68 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[176] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
attr(,"index.type")
[1] "chars"
attr(,"useBytes")
[1] TRUE

# Which elements had a match?
dna <- which(r > 0, arr.ind = TRUE)
dna

[1]  37  78 165

# Extract the length of each match.
dna.length <- attr(r, "match.length")[dna]

# Extract matched headers with a loop.
nombres <- list()
for (i in seq_along(dna)) {
  nombres[[i]] <- substr(fastanames[dna[i]], 1, dna.length[i])
}
head(nombres)

[[1]]
[1] ">QKO37013.1 DNA primase (plasmid) [Bacillus thuringiensis]"

[[2]]
[1] ">QKO36972.1 DNA-3-methyladenine glycosylase 2 family protein (plasmid) [Bacillus thuringiensis]"

[[3]]
[1] ">QKO36885.1 DNA topoisomerase III (plasmid) [Bacillus thuringiensis]"

1.2 Quick exercise: choosing a regular expression tool

You want to find all FASTA headers that contain the word recombinase. Which function is most directly useful?

Select the right answer

You want to remove the initial > from FASTA headers. Which function is most appropriate?

Select the right answer

1.3 Working with sequences as objects

Regular expressions are very convenient for a quick overview of FASTA files, but they do not understand sequences as biological objects. For more specific analyses, it is better to use sequence-aware packages. Two common options are seqinr and Biostrings.

In the following example, we are reading the same protein multifasta and we will obtain basic statistics, subset and save fasta sequences using SeqinR (=seqinr).

From text to sequence objects

After readLines(), the FASTA file is just text. After read.fasta(), the same information is stored as a list of sequence objects. This changes how we access names, annotations and sequences.

#reading fasta and playing with it
if(!require(seqinr)) install.packages("seqinr", repos = "https://cran.rstudio.com/")

Cargando paquete requerido: seqinr

Warning: package 'seqinr' was built under R version 4.6.1

library(seqinr)
prots <- read.fasta("data/HER1410.fasta")
str(prots)

List of 5807
 $ QKO37049.1: 'SeqFastadna' chr [1:67] "m" "t" "l" "t" ...
  ..- attr(*, "name")= chr "QKO37049.1"
  ..- attr(*, "Annot")= chr ">QKO37049.1 hypothetical protein HBA75_30905 (plasmid) [Bacillus thuringiensis]"
 $ QKO37048.1: 'SeqFastadna' chr [1:142] "m" "k" "v" "l" ...
  ..- attr(*, "name")= chr "QKO37048.1"
  ..- attr(*, "Annot")= chr ">QKO37048.1 hypothetical protein HBA75_30875 (plasmid) [Bacillus thuringiensis]"
 $ QKO37047.1: 'SeqFastadna' chr [1:326] "m" "e" "k" "k" ...
  ..- attr(*, "name")= chr "QKO37047.1"
  ..- attr(*, "Annot")= chr ">QKO37047.1 cytosolic protein (plasmid) [Bacillus thuringiensis]"
 $ QKO37046.1: 'SeqFastadna' chr [1:146] "m" "e" "k" "q" ...
  ..- attr(*, "name")= chr "QKO37046.1"
  ..- attr(*, "Annot")= chr ">QKO37046.1 helicase DnaB (plasmid) [Bacillus x1]"
 $ QKO37045.1: 'SeqFastadna' chr [1:359] "m" "a" "a" "t" ...
  ..- attr(*, "name")= chr "QKO37045.1"
  ..- attr(*, "Annot")= chr ">QKO37045.1 recombinase RecA (plasmid) [Bacillus thuringiensis]"
 $ QKO37044.1: 'SeqFastadna' chr [1:110] "m" "s" "y" "d" ...
  ..- attr(*, "name")= chr "QKO37044.1"
  ..- attr(*, "Annot")= chr ">QKO37044.1 hypothetical protein HBA75_31045 (plasmid) [Bacillus thuringiensis]"
 $ QKO37043.1: 'SeqFastadna' chr [1:293] "m" "k" "a" "a" ...
  ..- attr(*, "name")= chr "QKO37043.1"
  ..- attr(*, "Annot")= chr ">QKO37043.1 IS3 family transposase (plasmid) [Bacillus thuringiensis]"
 $ QKO37042.1: 'SeqFastadna' chr [1:102] "m" "g" "k" "i" ...
  ..- attr(*, "name")= chr "QKO37042.1"
  ..- attr(*, "Annot")= chr ">QKO37042.1 helix-turn-helix domain-containing protein (plasmid) [Bacillus thuringiensis]"
--- Cropped output ---

getName(prots)

   [1] "QKO37049.1" "QKO37048.1" "QKO37047.1" "QKO37046.1" "QKO37045.1"
   [6] "QKO37044.1" "QKO37043.1" "QKO37042.1" "QKO37041.1" "QKO37040.1"
  [11] "QKO37039.1" "QKO37038.1" "QKO37037.1" "QKO37036.1" "QKO37035.1"
  [16] "QKO37034.1" "QKO37033.1" "QKO37032.1" "QKO37031.1" "QKO37030.1"
  [21] "QKO37029.1" "QKO37028.1" "QKO37027.1" "QKO37026.1" "QKO37025.1"
  [26] "QKO37024.1" "QKO37023.1" "QKO37022.1" "QKO37021.1" "QKO37020.1"
  [31] "QKO37019.1" "QKO37018.1" "QKO37017.1" "QKO37016.1" "QKO37015.1"
  [36] "QKO37014.1" "QKO37013.1" "QKO37012.1" "QKO37011.1" "QKO37010.1"
  [41] "QKO37009.1" "QKO37008.1" "QKO37007.1" "QKO37006.1" "QKO37005.1"
  [46] "QKO37004.1" "QKO37003.1" "QKO37002.1" "QKO37001.1" "QKO37000.1"
  [51] "QKO36999.1" "QKO36998.1" "QKO36997.1" "QKO36996.1" "QKO36995.1"
  [56] "QKO36994.1" "QKO36993.1" "QKO36992.1" "QKO36991.1" "QKO36990.1"
  [61] "QKO36989.1" "QKO36988.1" "QKO36987.1" "QKO36986.1" "QKO36985.1"
  [66] "QKO36984.1" "QKO36983.1" "QKO36982.1" "QKO36981.1" "QKO36980.1"
  [71] "QKO36979.1" "QKO36978.1" "QKO36977.1" "QKO36976.1" "QKO36975.1"
  [76] "QKO36974.1" "QKO36973.1" "QKO36972.1" "QKO36971.1" "QKO36970.1"
  [81] "QKO36969.1" "QKO36968.1" "QKO36967.1" "QKO36966.1" "QKO36965.1"
  [86] "QKO36964.1" "QKO36963.1" "QKO36962.1" "QKO36961.1" "QKO36960.1"
  [91] "QKO36959.1" "QKO36958.1" "QKO36957.1" "QKO36956.1" "QKO36955.1"
  [96] "QKO36954.1" "QKO36953.1" "QKO36952.1" "QKO36951.1" "QKO36950.1"
 [101] "QKO36949.1" "QKO36948.1" "QKO36947.1" "QKO36946.1" "QKO36945.1"
 [106] "QKO36944.1" "QKO36943.1" "QKO36942.1" "QKO36941.1" "QKO36940.1"
 [111] "QKO36939.1" "QKO36938.1" "QKO36937.1" "QKO36936.1" "QKO36935.1"
 [116] "QKO36934.1" "QKO36933.1" "QKO36932.1" "QKO36931.1" "QKO36930.1"
 [121] "QKO36929.1" "QKO36928.1" "QKO36927.1" "QKO36926.1" "QKO36925.1"
--- Cropped output ---

prots[[1]]

 [1] "m" "t" "l" "t" "l" "h" "n" "g" "d" "l" "n" "k" "l" "a" "r" "d" "t" "s" "q"
[20] "d" "s" "i" "i" "l" "r" "v" "g" "e" "q" "e" "m" "v" "s" "l" "k" "s" "n" "g"
[39] "d" "i" "y" "v" "k" "g" "k" "l" "v" "e" "n" "d" "k" "e" "v" "v" "d" "g" "m"
[58] "r" "e" "l" "l" "m" "l" "s" "r" "k" "r"
attr(,"name")
[1] "QKO37049.1"
attr(,"Annot")
[1] ">QKO37049.1 hypothetical protein HBA75_30905 (plasmid) [Bacillus thuringiensis]"
attr(,"class")
[1] "SeqFastadna"

seq <- getSequence(prots[[1]])
getName(prots[[1]])

[1] "QKO37049.1"

paste(seq, collapse= "")

[1] "mtltlhngdlnklardtsqdsiilrvgeqemvslksngdiyvkgklvendkevvdgmrellmlsrkr"

paste(prots[[1]], collapse= "")

[1] "mtltlhngdlnklardtsqdsiilrvgeqemvslksngdiyvkgklvendkevvdgmrellmlsrkr"

# Amino acid composition and molecular weight.
# Some seqinr functions expect uppercase characters and simple vectors.
aaa(toupper(seq))

 [1] "Met" "Thr" "Leu" "Thr" "Leu" "His" "Asn" "Gly" "Asp" "Leu" "Asn" "Lys"
[13] "Leu" "Ala" "Arg" "Asp" "Thr" "Ser" "Gln" "Asp" "Ser" "Ile" "Ile" "Leu"
[25] "Arg" "Val" "Gly" "Glu" "Gln" "Glu" "Met" "Val" "Ser" "Leu" "Lys" "Ser"
[37] "Asn" "Gly" "Asp" "Ile" "Tyr" "Val" "Lys" "Gly" "Lys" "Leu" "Val" "Glu"
[49] "Asn" "Asp" "Lys" "Glu" "Val" "Val" "Asp" "Gly" "Met" "Arg" "Glu" "Leu"
[61] "Leu" "Met" "Leu" "Ser" "Arg" "Lys" "Arg"

aaa(toupper(unlist(seq)))

 [1] "Met" "Thr" "Leu" "Thr" "Leu" "His" "Asn" "Gly" "Asp" "Leu" "Asn" "Lys"
[13] "Leu" "Ala" "Arg" "Asp" "Thr" "Ser" "Gln" "Asp" "Ser" "Ile" "Ile" "Leu"
[25] "Arg" "Val" "Gly" "Glu" "Gln" "Glu" "Met" "Val" "Ser" "Leu" "Lys" "Ser"
[37] "Asn" "Gly" "Asp" "Ile" "Tyr" "Val" "Lys" "Gly" "Lys" "Leu" "Val" "Glu"
[49] "Asn" "Asp" "Lys" "Glu" "Val" "Val" "Asp" "Gly" "Met" "Arg" "Glu" "Leu"
[61] "Leu" "Met" "Leu" "Ser" "Arg" "Lys" "Arg"

aaa(toupper(as.vector(seq)))

 [1] "Met" "Thr" "Leu" "Thr" "Leu" "His" "Asn" "Gly" "Asp" "Leu" "Asn" "Lys"
[13] "Leu" "Ala" "Arg" "Asp" "Thr" "Ser" "Gln" "Asp" "Ser" "Ile" "Ile" "Leu"
[25] "Arg" "Val" "Gly" "Glu" "Gln" "Glu" "Met" "Val" "Ser" "Leu" "Lys" "Ser"
[37] "Asn" "Gly" "Asp" "Ile" "Tyr" "Val" "Lys" "Gly" "Lys" "Leu" "Val" "Glu"
[49] "Asn" "Asp" "Lys" "Glu" "Val" "Val" "Asp" "Gly" "Met" "Arg" "Glu" "Leu"
[61] "Leu" "Met" "Leu" "Ser" "Arg" "Lys" "Arg"

pmw(toupper(unlist(seq)))

[1] 7602.706

(stats1 <- AAstat(toupper(seq), plot = T))

$Compo

 *  A  C  D  E  F  G  H  I  K  L  M  N  P  Q  R  S  T  V  W  Y 
 0  1  0  6  5  0  5  1  3  6 10  4  4  0  2  5  5  3  6  0  1 

$Prop
$Prop$Tiny
[1] 0.2089552

$Prop$Small
[1] 0.4477612

$Prop$Aliphatic
[1] 0.2835821

$Prop$Aromatic
[1] 0.02985075

$Prop$Non.polar
[1] 0.4477612

$Prop$Polar
[1] 0.5522388

$Prop$Charged
[1] 0.3432836

$Prop$Basic
[1] 0.1791045

$Prop$Acidic
[1] 0.1641791


$Pi
[1] 6.557213

barplot(stats1$Compo, bty="7")

#cool color palette
library(RColorBrewer)
coul = colorRampPalette(brewer.pal(9, "Set1"))(20) #palette is expanded from 9 to 20 colors
barplot(stats1$Compo, col=coul, bty="7")

#dotplot
grep("recombinase",getAnnot(prots))

 [1]    5   52  349  354  990  993 1461 1499 1770 2177 2432 2483 2568 4543 4566

dotPlot(prots[[5]],prots[[2483]], wsize=3, nmatch=2)

dotPlot(prots[[2177]],prots[[2432]], wsize=3, nmatch=2)

dotPlot(prots[[2177]],prots[[2432]], col=c("floralwhite","dodgerblue"), 
        wsize=6, nmatch=3, xlab=getName(prots[[2177]]),ylab=getName(prots[[2432]]))

#extract the recombinases to a new file
recs <- prots[grep("recombinase",getAnnot(prots))]
#save to a file
write.fasta(recs, names=names(recs), file.out="data/recombinases.faa")

As you noticed in the code above, the function read.fasta() can read any (multi)fasta file containing a protein or nucleic acid sequence and create a list of lists. Thus, if you want to extract a sequence as a single element, you need to extract if from the list with unlist() or convert it to a vector with as.vector().

Once you read the fasta, you can extract the headline name with getName() or the sequence with getSequence(). Additionally, you can obtain and plot basic stats or compare sequences using dotPlot(). Moreover, if you extract a subset of sequences, you can use write.fasta() to save those sequences in a new fasta file.

Finally, as in the example below with HER1410 genome sequence (HER1410nt.fasta), you can also play with a nucleotide sequence and obtain some useful data, like the GC() content, the encoded proteins or the reverse complementary sequence with rev() and comp(), respectively.

Biological interpretation matters

Counting nucleotides, translating a sequence or calculating codon usage are technical operations. The biological interpretation depends on the molecule: genome, plasmid, coding sequence, partial sequence, strand, frame and annotation. Always write what the input sequence represents before interpreting the output.

#now the nt sequence
plasmid_nt <- read.fasta("data/HER1410nt.fasta")

count(unlist(plasmid_nt),3)


 aaa  aac  aag  aat  aca  acc  acg  act  aga  agc  agg  agt  ata  atc  atg  att 
2150  705 1089 1420  715  253  321  484  900  437  525  601  992  589  955 1354 
 caa  cac  cag  cat  cca  ccc  ccg  cct  cga  cgc  cgg  cgt  cta  ctc  ctg  ctt 
 848  248  455  548  325   85  126  235  297  126  190  308  448  200  360  569 
 gaa  gac  gag  gat  gca  gcc  gcg  gct  gga  ggc  ggg  ggt  gta  gtc  gtg  gtt 
1273  273  418  829  467  128  212  384  641  224  292  516  620  230  484  755 
 taa  tac  tag  tat  tca  tcc  tcg  tct  tga  tgc  tgg  tgt  tta  ttc  ttg  ttt 
1093  547  501 1093  592  305  262  475  955  404  666  663 1174  615  889 1310

count(unlist(plasmid_nt),5)


aaaaa aaaac aaaag aaaat aaaca aaacc aaacg aaact aaaga aaagc aaagg aaagt aaata 
  307   110   200   221   138    31    58    45   189    77   105    86   133 
aaatc aaatg aaatt aacaa aacac aacag aacat aacca aaccc aaccg aacct aacga aacgc 
  109   170   171   144    25    64    73    34    14    15    24    42    13 
aacgg aacgt aacta aactc aactg aactt aagaa aagac aagag aagat aagca aagcc aagcg 
   28    45    48    24    46    66   199    38    70   104    71    20    38 
aagct aagga aaggc aaggg aaggt aagta aagtc aagtg aagtt aataa aatac aatag aatat 
   61    97    33    40    70    96    13    55    84   112    80    52   116 
aatca aatcc aatcg aatct aatga aatgc aatgg aatgt aatta aattc aattg aattt acaaa 
   81    41    35    54   130    51    95    83   162    77   128   123   109 
acaac acaag acaat acaca acacc acacg acact acaga acagc acagg acagt acata acatc 
   54    63    67    27    18    20    24    52    34    39    44    37    27 
acatg acatt accaa accac accag accat accca acccc acccg accct accga accgc accgg 
   36    64    38    13    28    20    14     2     3    14    13    10     9 
accgt accta acctc acctg acctt acgaa acgac acgag acgat acgca acgcc acgcg acgct 
   16    19     5    20    29    45     8    14    35     9     6     2    23 
acgga acggc acggg acggt acgta acgtc acgtg acgtt actaa actac actag actat actca 
   32    13     8    21    35    10    27    33    39    24    20    44    30 
actcc actcg actct actga actgc actgg actgt actta acttc acttg acttt agaaa agaac 
    7    10    14    44    10    27    36    49    28    41    61   171    51 
agaag agaat agaca agacc agacg agact agaga agagc agagg agagt agata agatc agatg 
  109    84    35    16    19    13    54    15    39    39    85    19    75 
agatt agcaa agcac agcag agcat agcca agccc agccg agcct agcga agcgc agcgg agcgt 
   76    89    12    28    37    12     7    12    20    33    17    20    26 
agcta agctc agctg agctt aggaa aggac aggag aggat aggca aggcc aggcg aggct aggga 
   35    11    41    37    72    26    46    48    24     1    19    21    38 
agggc agggg agggt aggta aggtc aggtg aggtt agtaa agtac agtag agtat agtca agtcc 
   17    23    23    51    20    59    37    73    21    28    65    28    13 
agtcg agtct agtga agtgc agtgg agtgt agtta agttc agttg agttt ataaa ataac ataag 
    9    16    42    18    35    26    60    35    63    69   133    52    53 
ataat ataca atacc atacg atact ataga atagc atagg atagt atata atatc atatg atatt 
   84    79    29    40    46    46    25    20    36    79    74    77   119 
atcaa atcac atcag atcat atcca atccc atccg atcct atcga atcgc atcgg atcgt atcta 
   94    32    37    63    50     8    16    39    40    11    17    32    59 
atctc atctg atctt atgaa atgac atgag atgat atgca atgcc atgcg atgct atgga atggc 
   18    25    48   184    36    36    94    65    17    20    48    80    35 
atggg atggt atgta atgtc atgtg atgtt attaa attac attag attat attca attcc attcg 
   47    69    73    29    34    88   114    92    85   100    83    36    45 
attct attga attgc attgg attgt attta atttc atttg atttt caaaa caaac caaag caaat 
   50   111    43    91    76   153    60    89   126   133    45    57    99 
caaca caacc caacg caact caaga caagc caagg caagt caata caatc caatg caatt cacaa 
   44    11    18    42    59    32    32    47    63    25    38   103    39 
cacac cacag cacat cacca caccc caccg cacct cacga cacgc cacgg cacgt cacta cactc 
   12    26    22    14     3    10    17    14     7    11    11    13     8 
cactg cactt cagaa cagac cagag cagat cagca cagcc cagcg cagct cagga caggc caggg 
   12    29    52    15    28    46    39    10    26    27    29    13    19 
caggt cagta cagtc cagtg cagtt cataa catac catag catat catca catcc catcg catct 
   35    34    16    14    52    37    26     7    63    37    15    13    29 
catga catgc catgg catgt catta cattc cattg cattt ccaaa ccaac ccaag ccaat ccaca 
   38    15    21    18    68    35    46    80    46    14    28    35    27 
ccacc ccacg ccact ccaga ccagc ccagg ccagt ccata ccatc ccatg ccatt cccaa cccac 
    5     6     4    24    17    16    21    18    16     9    39    14     3 
cccag cccat cccca ccccc ccccg cccct cccga cccgc cccgg cccgt cccta ccctc ccctg 
    7    11     6     4     1     5     3     1     0     2    13     2     5 
ccctt ccgaa ccgac ccgag ccgat ccgca ccgcc ccgcg ccgct ccgga ccggc ccggg ccggt 
    8    19     6     2     8     7     6     3     6     9     3     2     7 
ccgta ccgtc ccgtg ccgtt cctaa cctac cctag cctat cctca cctcc cctcg cctct cctga 
   11     7    10    20    23     6     6    28     7     5     3     6    21 
cctgc cctgg cctgt cctta ccttc ccttg ccttt cgaaa cgaac cgaag cgaat cgaca cgacc 
    6    18    11    27    16    13    39    50    12    27    32    10     6 
cgacg cgact cgaga cgagc cgagg cgagt cgata cgatc cgatg cgatt cgcaa cgcac cgcag 
    3    14    10     7     5     9    31     9    38    34    18     7    15 
cgcat cgcca cgccc cgccg cgcct cgcga cgcgc cgcgg cgcgt cgcta cgctc cgctg cgctt 
   13     9     0     3     4     3     1     4     3    12     5    12    16 
cggaa cggac cggag cggat cggca cggcc cggcg cggct cggga cgggc cgggg cgggt cggta 
   36     9    18    23     9     5     3    11     9     2     3     7    23 
cggtc cggtg cggtt cgtaa cgtac cgtag cgtat cgtca cgtcc cgtcg cgtct cgtga cgtgc 
    2    13    17    32    16     5    35    14     5     6    13    24    12 
cgtgg cgtgt cgtta cgttc cgttg cgttt ctaaa ctaac ctaag ctaat ctaca ctacc ctacg 
   17    20    31    21    19    38    74    23    19    42    24     4    13 
ctact ctaga ctagc ctagg ctagt ctata ctatc ctatg ctatt ctcaa ctcac ctcag ctcat 
   26    24     5    11    20    42    30    33    58    29     9    12    24 
ctcca ctccc ctccg ctcct ctcga ctcgc ctcgg ctcgt ctcta ctctc ctctg ctctt ctgaa 
   13     4     6    11     9     5     4    14    18    10     5    27    76 
ctgac ctgag ctgat ctgca ctgcc ctgcg ctgct ctgga ctggc ctggg ctggt ctgta ctgtc 
    9    13    41    20     3     2    17    24    12    13    31    27    11 
ctgtg ctgtt cttaa cttac cttag cttat cttca cttcc cttcg cttct cttga cttgc cttgg 
   22    39    51    22    29    54    30    16     5    35    45    21    32 
cttgt cttta ctttc ctttg ctttt gaaaa gaaac gaaag gaaat gaaca gaacc gaacg gaact 
   30    70    27    33    69   205    71    92   140    68    23    28    38 
gaaga gaagc gaagg gaagt gaata gaatc gaatg gaatt gacaa gacac gacag gacat gacca 
  124    60    60    67    72    43    76   106    34    13    22    29    16 
gaccc gaccg gacct gacga gacgc gacgg gacgt gacta gactc gactg gactt gagaa gagac 
    5    12    14    22     6    11    16    24    11    14    24    74    15 
gagag gagat gagca gagcc gagcg gagct gagga gaggc gaggg gaggt gagta gagtc gagtg 
   23    39    21    14    12    13    37     8    21    30    23    20    25 
gagtt gataa gatac gatag gatat gatca gatcc gatcg gatct gatga gatgc gatgg gatgt 
   43    78    38    37    86    22    18    14    16   103    44    50    62 
gatta gattc gattg gattt gcaaa gcaac gcaag gcaat gcaca gcacc gcacg gcact gcaga 
   62    43    57    99    82    19    41    62    14     6    10    14    32 
gcagc gcagg gcagt gcata gcatc gcatg gcatt gccaa gccac gccag gccat gccca gcccc 
   31    23    15    27    16    21    54    18     3    14    15     5     3 
gcccg gccct gccga gccgc gccgg gccgt gccta gcctc gcctg gcctt gcgaa gcgac gcgag 
    1     1     6     3     5    11    10     4    11    18    24    10     7 
gcgat gcgca gcgcc gcgcg gcgct gcgga gcggc gcggg gcggt gcgta gcgtc gcgtg gcgtt 
   27    22     1     3     4    26     5     4    16    15     8    16    24 
gctaa gctac gctag gctat gctca gctcc gctcg gctct gctga gctgc gctgg gctgt gctta 
   38    15    17    38    15    11    11    15    51    22    18    24    31 
gcttc gcttg gcttt ggaaa ggaac ggaag ggaat ggaca ggacc ggacg ggact ggaga ggagc 
   15    26    36   105    44    47    69    25    10    18    19    53    19 
ggagg ggagt ggata ggatc ggatg ggatt ggcaa ggcac ggcag ggcat ggcca ggccc ggccg 
   28    28    49    13    46    68    32     6    20    26    14     2     3 
ggcct ggcga ggcgc ggcgg ggcgt ggcta ggctc ggctg ggctt gggaa gggac gggag gggat 
    6    12     8    12    18    17    11    17    20    50    12    16    35 
gggca gggcc gggcg gggct gggga ggggc ggggg ggggt gggta gggtc gggtg gggtt ggtaa 
   19     5    10    14    17    15    13    13    20     4    21    28    66 
ggtac ggtag ggtat ggtca ggtcc ggtcg ggtct ggtga ggtgc ggtgg ggtgt ggtta ggttc 
   28    18    40    18     6    15    14    69    35    29    34    32    28 
ggttg ggttt gtaaa gtaac gtaag gtaat gtaca gtacc gtacg gtact gtaga gtagc gtagg 
   28    56    99    37    29    73    39    12    14    21    36    15    18 
gtagt gtata gtatc gtatg gtatt gtcaa gtcac gtcag gtcat gtcca gtccc gtccg gtcct 
   19    38    50    50    70    29     9    15    27    23     2     6    11 
gtcga gtcgc gtcgg gtcgt gtcta gtctc gtctg gtctt gtgaa gtgac gtgag gtgat gtgca 
   16     5     9    12    16    10    14    26    73    15    26    58    30 
gtgcc gtgcg gtgct gtgga gtggc gtggg gtggt gtgta gtgtc gtgtg gtgtt gttaa gttac 
    5     8    28    72    13    16    31    30    16    15    48    64    29 
gttag gttat gttca gttcc gttcg gttct gttga gttgc gttgg gttgt gttta gtttc gtttg 
   28    72    42    29    19    42    50    34    39    55    64    44    51 
gtttt taaaa taaac taaag taaat taaca taacc taacg taact taaga taagc taagg taagt 
   93   193    46   108   123    56    22    24    59    39    21    43    48 
taata taatc taatg taatt tacaa tacac tacag tacat tacca taccc taccg tacct tacga 
   92    34    75   110    76    39    57    40    35    11    11    18    24 
tacgc tacgg tacgt tacta tactc tactg tactt tagaa tagac tagag tagat tagca tagcc 
   14    24    33    42    18    45    60    90    15    26    66    35     7 
tagcg tagct tagga taggc taggg taggt tagta tagtc tagtg tagtt tataa tatac tatag 
   20    23    29    11    21    32    34    17    27    48    95    50    31 
tatat tatca tatcc tatcg tatct tatga tatgc tatgg tatgt tatta tattc tattg tattt 
   84    86    39    38    51    79    40    65    61    99    59    90   126 
tcaaa tcaac tcaag tcaat tcaca tcacc tcacg tcact tcaga tcagc tcagg tcagt tcata 
   97    28    38    65    31    15     7    20    33    20    18    36    51 
tcatc tcatg tcatt tccaa tccac tccag tccat tccca tcccc tcccg tccct tccga tccgc 
   35    26    72    53    23    29    36    10     7     1     8    13     8 
tccgg tccgt tccta tcctc tcctg tcctt tcgaa tcgac tcgag tcgat tcgca tcgcc tcgcg 
    7    19    21    10    20    40    33     9     8    42    15     3     3 
tcgct tcgga tcggc tcggg tcggt tcgta tcgtc tcgtg tcgtt tctaa tctac tctag tctat 
   13    19     7     7    11    27    13    20    32    58    22    17    53 
tctca tctcc tctcg tctct tctga tctgc tctgg tctgt tctta tcttc tcttg tcttt tgaaa 
   22    11     8    25    23     4    17    28    49    27    48    63   182 
tgaac tgaag tgaat tgaca tgacc tgacg tgact tgaga tgagc tgagg tgagt tgata tgatc 
   50   128   112    28    15    15    27    34    19    24    35    74    29 
tgatg tgatt tgcaa tgcac tgcag tgcat tgcca tgccc tgccg tgcct tgcga tgcgc tgcgg 
  100    83    65    19    38    42    15     1     7    13    20     4    15 
tgcgt tgcta tgctc tgctg tgctt tggaa tggac tggag tggat tggca tggcc tggcg tggct 
   16    44    25    45    35   107    25    48    70    32    14    18    19 
tggga tgggc tgggg tgggt tggta tggtc tggtg tggtt tgtaa tgtac tgtag tgtat tgtca 
   49    14    19    30    58    27    74    62    67    21    37    68    20 
tgtcc tgtcg tgtct tgtga tgtgc tgtgg tgtgt tgtta tgttc tgttg tgttt ttaaa ttaac 
   18    12    23    37     6    51    29    70    48    68    88   164    49 
ttaag ttaat ttaca ttacc ttacg ttact ttaga ttagc ttagg ttagt ttata ttatc ttatg 
   50   112    70    30    28    72    91    40    44    51   101    60    85 
ttatt ttcaa ttcac ttcag ttcat ttcca ttccc ttccg ttcct ttcga ttcgc ttcgg ttcgt 
  127    76    23    43    70    55    12    19    30    27    13    14    34 
ttcta ttctc ttctg ttctt ttgaa ttgac ttgag ttgat ttgca ttgcc ttgcg ttgct ttgga 
   57    28    28    86   139    25    37    93    49    11    25    56    74 
ttggc ttggg ttggt ttgta ttgtc ttgtg ttgtt tttaa tttac tttag tttat tttca tttcc 
   23    36    90    63    17    52    99   146    57    84   147    57    35 
tttcg tttct tttga tttgc tttgg tttgt tttta ttttc ttttg ttttt 
   19    72    88    43    61    70   147    52    89   143

uco(plasmid_nt[[1]],frame=0)


aaa aac aag aat aca acc acg act aga agc agg agt ata atc atg att caa cac cag cat 
722 239 389 463 238  84 114 144 286 145 148 192 318 190 328 464 291  88 156 187 
cca ccc ccg cct cga cgc cgg cgt cta ctc ctg ctt gaa gac gag gat gca gcc gcg gct 
125  22  49  94  94  40  62  90 148  73 158 197 374  82 145 267 125  30  75 130 
gga ggc ggg ggt gta gtc gtg gtt taa tac tag tat tca tcc tcg tct tga tgc tgg tgt 
241  78  96 184 220  78 181 249 408 194 181 327 178  88  88 155 341 118 185 223 
tta ttc ttg ttt 
404 206 313 414

uco(plasmid_nt[[1]],frame=2)


aaa aac aag aat aca acc acg act aga agc agg agt ata atc atg att caa cac cag cat 
720 234 340 462 233  89  93 175 283 131 182 225 376 182 328 460 300  82 152 177 
cca ccc ccg cct cga cgc cgg cgt cta ctc ctg ctt gaa gac gag gat gca gcc gcg gct 
 96  37  39  85  97  34  61 117 139  54  96 189 461  97 135 270 183  53  74 140 
gga ggc ggg ggt gta gtc gtg gtt taa tac tag tat tca tcc tcg tct tga tgc tgg tgt 
215  66 109 193 211  73 144 244 332 167 144 391 210 111  80 177 273 129 247 192 
tta ttc ttg ttt 
384 200 299 444

translate(plasmid_nt[[1]])

    [1] "V" "W" "S" "I" "K" "H" "N" "L" "T" "T" "S" "N" "E" "Y" "S" "*" "A" "A"
   [19] "I" "I" "L" "F" "*" "N" "L" "*" "P" "L" "L" "L" "V" "Q" "L" "D" "S" "Y"
   [37] "L" "H" "E" "Q" "V" "L" "*" "L" "R" "L" "*" "W" "K" "I" "Q" "L" "H" "L"
   [55] "L" "L" "L" "S" "*" "I" "R" "C" "L" "N" "C" "T" "I" "H" "L" "S" "T" "D"
   [73] "L" "K" "V" "L" "L" "F" "Q" "V" "K" "R" "L" "Y" "Q" "L" "Y" "*" "P" "V"
   [91] "V" "F" "E" "L" "C" "S" "L" "L" "G" "L" "G" "L" "T" "Y" "P" "F" "Y" "I"
  [109] "R" "S" "*" "E" "Y" "L" "L" "L" "*" "T" "D" "I" "L" "N" "V" "L" "S" "Y"
  [127] "L" "G" "F" "C" "Y" "I" "V" "L" "V" "N" "Y" "L" "T" "L" "L" "V" "S" "L"
  [145] "Q" "Y" "H" "Q" "D" "Q" "R" "W" "R" "L" "P" "R" "G" "L" "E" "I" "L" "F"
  [163] "Q" "L" "H" "P" "L" "E" "L" "E" "A" "Y" "R" "M" "F" "L" "Y" "D" "V" "L"
  [181] "S" "Y" "T" "Y" "S" "S" "L" "Q" "F" "Y" "Y" "G" "F" "L" "L" "V" "Y" "F"
  [199] "P" "K" "N" "A" "F" "R" "I" "W" "R" "T" "L" "K" "H" "*" "R" "I" "R" "K"
  [217] "N" "Y" "A" "I" "*" "L" "C" "L" "S" "F" "Y" "Y" "L" "V" "L" "V" "V" "Q"
  [235] "Y" "T" "K" "Y" "L" "Y" "Q" "*" "K" "F" "R" "N" "P" "F" "E" "Q" "C" "L"
  [253] "L" "E" "C" "R" "L" "P" "S" "G" "F" "F" "Q" "C" "K" "S" "D" "Y" "L" "*"
  [271] "Y" "S" "V" "Q" "H" "H" "N" "*" "I" "F" "S" "L" "S" "*" "S" "*" "R" "H"
  [289] "D" "C" "L" "K" "I" "L" "R" "C" "L" "L" "Y" "L" "L" "F" "*" "T" "S" "R"
  [307] "I" "C" "I" "L" "Q" "F" "Q" "P" "Q" "*" "D" "*" "Y" "I" "S" "F" "L" "C"
  [325] "L" "G" "H" "I" "P" "W" "V" "I" "*" "L" "R" "F" "S" "D" "L" "I" "Q" "P"
  [343] "F" "C" "A" "W" "N" "L" "S" "H" "V" "L" "L" "L" "S" "L" "V" "P" "I" "A"
  [361] "Q" "V" "S" "Q" "L" "R" "*" "*" "T" "F" "F" "R" "*" "R" "L" "L" "Y" "Q"
  [379] "I" "S" "L" "C" "Y" "F" "*" "I" "*" "H" "Y" "I" "H" "P" "L" "F" "L" "E"
  [397] "W" "N" "V" "S" "L" "I" "L" "N" "E" "*" "I" "D" "L" "I" "Y" "K" "Q" "E"
  [415] "*" "Y" "Q" "I" "V" "F" "S" "S" "Y" "L" "L" "S" "F" "F" "E" "K" "Q" "V"
  [433] "V" "L" "Y" "F" "S" "H" "Y" "I" "L" "H" "H" "S" "N" "H" "L" "Q" "L" "P"
--- Cropped output ---

GC(plasmid_nt[[1]])

[1] 0.3437746

plasmid_nt[[1]][1:100]

  [1] "g" "t" "t" "t" "g" "g" "t" "c" "a" "a" "t" "t" "a" "a" "a" "c" "a" "c"
 [19] "a" "a" "c" "c" "t" "a" "a" "c" "t" "a" "c" "a" "t" "c" "a" "a" "a" "t"
 [37] "g" "a" "a" "t" "a" "c" "a" "g" "t" "t" "a" "g" "g" "c" "t" "g" "c" "g"
 [55] "a" "t" "t" "a" "t" "t" "t" "t" "a" "t" "t" "t" "t" "g" "a" "a" "a" "t"
 [73] "c" "t" "g" "t" "a" "a" "c" "c" "t" "t" "t" "a" "t" "t" "a" "c" "t" "g"
 [91] "g" "t" "g" "c" "a" "a" "t" "t" "g" "g"

comp(plasmid_nt[[1]][1:100])

  [1] "c" "a" "a" "a" "c" "c" "a" "g" "t" "t" "a" "a" "t" "t" "t" "g" "t" "g"
 [19] "t" "t" "g" "g" "a" "t" "t" "g" "a" "t" "g" "t" "a" "g" "t" "t" "t" "a"
 [37] "c" "t" "t" "a" "t" "g" "t" "c" "a" "a" "t" "c" "c" "g" "a" "c" "g" "c"
 [55] "t" "a" "a" "t" "a" "a" "a" "a" "t" "a" "a" "a" "a" "c" "t" "t" "t" "a"
 [73] "g" "a" "c" "a" "t" "t" "g" "g" "a" "a" "a" "t" "a" "a" "t" "g" "a" "c"
 [91] "c" "a" "c" "g" "t" "t" "a" "a" "c" "c"

rev(comp(plasmid_nt[[1]][1:100]))

  [1] "c" "c" "a" "a" "t" "t" "g" "c" "a" "c" "c" "a" "g" "t" "a" "a" "t" "a"
 [19] "a" "a" "g" "g" "t" "t" "a" "c" "a" "g" "a" "t" "t" "t" "c" "a" "a" "a"
 [37] "a" "t" "a" "a" "a" "a" "t" "a" "a" "t" "c" "g" "c" "a" "g" "c" "c" "t"
 [55] "a" "a" "c" "t" "g" "t" "a" "t" "t" "c" "a" "t" "t" "t" "g" "a" "t" "g"
 [73] "t" "a" "g" "t" "t" "a" "g" "g" "t" "t" "g" "t" "g" "t" "t" "t" "a" "a"
 [91] "t" "t" "g" "a" "c" "c" "a" "a" "a" "c"

1.4 Connect with sequence databases with seqinr

You can query to NCBI, Uniprot and other databases directly using seqinr. The seqinr package was written by the group that created the ACNUC database in Lyon, France (http://pbil.univ-lyon1.fr/databases/acnuc/acnuc.html). The ACNUC database is a database that contains most of the data from the NCBI Sequence Database, as well as data from other sequence databases such as UniProt and Ensembl. the ACNUC database is organised into various different ACNUC (sub)-databases, which contain different parts of the NCBI database, and when you want to search the NCBI database via R, you will need to specify which ACNUC sub-database the NCBI data that you want to query is stored in.

To obtain a full list of the ACNUC sub-databases that you can access using seqinr, you can use the choosebank() function from seqinr. Then, you just need to select the database and query your sequence. However, as you can see in the example below it does not work currently. I mentioned this here because I used this previously and found it very useful. In case you want to try it again in the future you can check the examples in the Reference 4 below.

choosebank()

 [1] "genbank"         "embl"            "emblwgs"         "genbankseqinr"  
 [5] "swissprot"       "ensembl"         "hogenom7dna"     "hogenom7"       
 [9] "hogenom"         "hovergendna"     "hovergen"        "phever2"        
[13] "phever2dna"      "refseq"          "refseq16s"       "ensprotists"    
[17] "ensfungi"        "ensmetazoa"      "ensplants"       "ensemblbacteria"
[21] "mito"            "emglib"          "refseqViruses"   "ribodb"

#select genbank
choosebank("swissprot")
pol <- query("pol","AC=P0DPS1",verbose=TRUE,invisible=FALSE)

I'm checking the arguments...
... and everything is OK up to now.
I'm checking the status of the socket connection...
... and everything is OK up to now.
I'm sending query to server...
... answer from server is: code=0&lrank=2&count=1&type=SQ&locus=T 
I'm trying to analyse answer from server...
... and everything is OK up to now.
... and the rank of the resulting list is: 2 .
... and there are 1 elements in the list.
... and the elements in the list are of type SQ .
... and there are only parent sequences in the list.
I'm trying to get the infos about the elements of the list...
... and I have received 1 lines as expected.

polseq <- getSequence(pol$req[[1]])
closebank()

1.5 The package rentrez

Like seqinr, other R packages allow accessing to NCBI and other databases, including APE or genbankr. The latter takes advantage of the packages rentrez.

rentrez is an R package that helps users query the NCBI’s databases to download diverse type of data and metadata, including sequences or research papers.

if(!require(rentrez)){
   install.packages("rentrez", repos = "https://cran.rstudio.com/")
}

Cargando paquete requerido: rentrez

Warning: package 'rentrez' was built under R version 4.6.1

library(rentrez)
(pols <- entrez_search(db = "pubmed", term = "DNA polymerase") )

Entrez search result with 380909 hits (object contains 20 IDs and no web_history object)
 Search term (as translated):  "dna directed dna polymerase"[Supplementary Concep ...

str(pols)

List of 5
 $ ids             : chr [1:20] "42610908" "42610786" "42610739" "42610298" ...
 $ count           : int 380909
 $ retmax          : int 20
 $ QueryTranslation: chr "\"dna directed dna polymerase\"[Supplementary Concept] OR \"dna directed dna polymerase\"[All Fields] OR \"dna "| __truncated__
 $ file            :Classes 'XMLInternalDocument', 'XMLAbstractDocument' <pointer: 0x0000010953afe1b0> 
 - attr(*, "class")= chr [1:2] "esearch" "list"

(Gon <- entrez_search(db = "pubmed", term = "Gonzalez", retmax=100))

Entrez search result with 78138 hits (object contains 100 IDs and no web_history object)
 Search term (as translated):  "Gonzalez"[All Fields]

Gon$ids #now kept 100

  [1] "42611012" "42610719" "42610673" "42610369" "42610066" "42609624"
  [7] "42609470" "42609098" "42608522" "42608361" "42608214" "42608132"
 [13] "42608017" "42607945" "42607542" "42607417" "42607149" "42606497"
 [19] "42606425" "42606293" "42606280" "42606018" "42605531" "42605359"
 [25] "42605305" "42604533" "42604080" "42604008" "42603991" "42602869"
 [31] "42602722" "42602528" "42602480" "42602350" "42601166" "42600688"
 [37] "42600177" "42599835" "42599702" "42599438" "42598990" "42598584"
 [43] "42596760" "42596012" "42595947" "42595846" "42595753" "42595729"
 [49] "42595300" "42595014" "42594771" "42594196" "42593953" "42593629"
 [55] "42593620" "42593591" "42592627" "42592493" "42592491" "42592323"
 [61] "42592249" "42591436" "42591398" "42591297" "42590198" "42590175"
 [67] "42590032" "42589719" "42589390" "42589360" "42589312" "42589218"
 [73] "42588921" "42588601" "42587923" "42587603" "42587422" "42587356"
 [79] "42586785" "42586240" "42585376" "42585333" "42585015" "42584808"
 [85] "42584162" "42583913" "42583500" "42582759" "42581758" "42581252"
 [91] "42580964" "42580948" "42580401" "42580343" "42580051" "42579884"
 [97] "42579774" "42579334" "42578920" "42578817"

#we can also fetch data
her1410 <- entrez_search(db = "nuccore", term = "HER1410") 
her1410$ids

[1] "1853362518" "1853362517" "1853362516" "1853362515" "1852678087"
[6] "1852677931" "1852677628" "1852672161" "183211906"

her1410_1 <- entrez_fetch(db="nuccore", id=her1410$ids[1], rettype="fasta")
head(her1410_1)

[1] ">NZ_CP050186.1 Bacillus thuringiensis strain HER1410 plasmid pLUSID3, complete sequence\nGTTTGGTCAATTAAACACAACCTAACTACATCAAATGAATACAGTTAGGCTGCGATTATTTTATTTTGAA\nATCTGTAACCTTTATTACTGGTGCAATTGGATTCTTACCTACACGAGCAGGTTTTGTGACTTCGACTGTA\nATGGAAGATACAATTGCATTTACTGCTGCTTTCTTAGATTCGTTGTTTAAATTGTACCATTCATCTTTCA\nACTGATTTAAAAGTTCTTTTATTTCAAGTGAAGAGGCTGTATCAGTTATATTAGCCAGTTGTTTTTGAAT\nTATGTTCTCTTCTTGGGTTAGGGTTAACATATCCTTTTTATATTCGTTCTTAGGAATATCTCCTTCTATG\nAACAGATATTTTAAACGTGCTTTCTTATCTTGGATTCTGTTATATTGTTCTTGTAAATTACTTAACTCTA\nTTGGTTTCTCTTCAGTATCATCAAGATCAACGATGGCGTCTTCCAAGAGGTTTAGAAATTCTTTTTCAAT\nTACATCCTCTGGAACTTGAGGCATATCGCATGTTCCTTTATGATGTCTTGAGCTACACCTATAGCTCATT\nACAATTCTATTATGGCTTCTTACTTGTTTATTTCCCAAAAAATGCTTTCCGCATCTGGCGCACTTTAAAA\nCATTAGAGAATACGAAAAAATTATGCAATCTAACTTTGCCTCTCTTTCTACTATCTTGTACTTGTTGTAC\nAGTATACCAAGTATCTTTATCAATAAAAGTTTCGAAATCCTTTTGAGCAATGTCTGTTAGAATGTCGTCT\nCCCCAGCGGATTTTTCCAATGTAAATCGGATTATTTATAATATAGCGTACAGCATCATAATTGAATATTT\nTCCCTCTCTTAGTCTTAACGCCACGACTGTTTAAAGATTTTACGATGCTTATTATACCTTTTGTTTTAAA\nCATCTCGAATATGTATTTTACAATTTCAGCCTCAGTAGGATTGATATATAAGTTTCCTTTGTTTAGGTCA\nTATCCCATGGGTGATTTAGCTCCGTTTCTCAGACCTAATTCAGCCTTTTTGTGCATGGAATCTCTCACAC\nGTTCTGCTGTTGTCTCTCGTTCCCATTGCGCAAGTGTCGCAACTAAGGTAATAAACATTCTTCCGGTAGC\nGGTTGTTGTATCAAATATCTCTGTGCTACTTTTAAATTTAACATTATATTCATCCATTATTTTTAGAATG\nGAATGTAAGTCTGATACTGAACGAGTGAATCGATCTAATCTATAAACAAGAATAATATCAAATTGTTTTT\nTCTTCATATCTTTTATCATTTTTTGAAAAGCAGGTCGTTCTGTATTTTTCGCACTATATCCTTCATCACA\nGTAATCATTTACAACTACCCATCCTTGTGATTTAGCATATTGCTCCAGACGTAATTGCTGCATATCTAAT\nGAAATACCTTCTTCAACTTGCATATCAGTAGATACGCGTCTATAAATTACACACTTCATTTGCACATACT\nCCTTTCTTAACTAAATTTCTATATCATATGTTTTATCAAAGCAAATTAGACAAATGTATGGGTCAATCAT\nTTGATTGACTATTTGGCCCAGTGAGAAATTCTCACTGTTCATCCAACTGAATGAAATCATATAAATCTTC\nCATATTTACGTTAAGTTGAGAAGCGATATTCTTAGCGGTTTGATAAGACATGATTCTATCATTATTTGCA\nTAAGAATGAACTTGTTGTTTTTTCATATCTAACTTTAATGCTAAATCTACTTGTGTTAATTTCTTCTCTT\nTTAAAATTTCATTCAGTCGGCATTTGCCGACTACATACACTGTTTCACCGCCTAATTATTGAATGATCGG\nACTCACACTGTATAAAAATTTTCCTATAATTCTTATATCCTCGCAGTTATTTTGTGAGTATTGTTGGTCC\nTTAAAACTTTCGTCATGTGAACAAGGTTCTAAAATTATTAAATCTGTAAATTTATACACCTTTTTTAAAG\nTTGCGTAATGTCCATTTACAATTACAGCTGCTATTTCTCCGTTTTGTACATCACACTGTTTTTTCAGTAT\nGGCGTAATGTCCATTAGGAACAATTTTATTCATGGATTCACCGGTAACAACCAGTCCGAATAATTCATCA\nATACTGTGAGTTTTATATGGAGGTGCAATTCTATCAACTACATCTTCTATAGCTTCCAATGGAACACCAG\nCTGCTATTTTACCAATAATAGGAATTTCTTTTTTTAGTTCACACTCTATAGGTTTTTCTTGAACTAATTG\nAAGTTCCCCATCCACAATTTCAACTTTTGTATTCTTATAAGTTGTATCAATATCAGATTTTGTTACTCCA\nAATACAGCGGCCATTTTTTCTAAAACCCCTGAACTTGGTTTGGCTCTATAATTCATATAATCACTTAAGG\nTACTTCTTGCAATTCCTATTTGACTAGCTAAATCAGATTGAGTCATATTATTTTTTTTTAAAAAATTCTT\nTATGTTTCTTACTATGGTTTGTTTTTGTATATCAGTCATACCGTCACCTCCTATTCTGACTACGCTTTTT\nAATATAACATATTACGAATTATTCGTAAAGCGTTATATCCGTATGGTTTTTTCGTATTTTTGTATTGAAA\nTTACATAAATTTAGTAATACAATAAATCTCGAAGGAAGGGGGAAACGAAATGGATTATTTGAAAAGAACA\nTTGAATGAACTTAGGGAAAGCGCAGGGTTCAATCAAGCAGAGCTTGCGGATATATTAGAAGTATCCCCAA\nAAACGCTATGGTTATACGAACAAGATTCAACAAACATACCAGATGAATTAATTAAAAAGTATATGTATTT\nGTTCGATGTTCCGTATGAGGATATATTTTTTGGTTCTAAGTACGAAAAATTCGTACAAGTGAAGAAACGT\nGTACAAGAAAGAGCAAATAATTTAAAAAAAATTGTTTCGTAAAAATTTGCTTTAAATGGGTAGTCCTATT\nGTCCCACGAACATATAAATGCATTGAGGTGATTGAGGATGAGTGGGGGACAAATCATTCGTGATGAAAAT\nGGGTATGTGGTGAAAGTAATCCTTACAAAGGAACAGTGGAAGAAATTTCTAACACCGTTAATACCAGCTG\nCACGGGAGTTAATAATTCAAAGAAAAGTGGAACAACGAAAAAAAGCAAAATGAATAATTTTTTTAATATA\nTTTGCGAAATTTGACGATAAATATTGGTTCTACAAATTAAAGGAGAGTGAAAAGCATGAATGGAGTACTA\nCTAGCAACACGAATTATGAAAGGGCATGAAGTTGTTAAAAAATGCGCAGAAGCAAGAAATAACCCTTTAC\nTATTAGAAGCTATGGAATCAGAAGCAAAACGTAAGTTATACGAAATGAACTGTAAGGTTTCAAATCGAAG\nACCAACTATGAAAAGTCAAGGGGACATTTTCAAAAAATATTGCTAGAGGAGGTGAGTTAATTGAAGGAAG\nTAACGGTAATTTTTAAATCAGGTGCTAAAGCAAGTTTTACAGTAGAGGAATTTGCGACATTTAAAAATGG\nATTTGGAGCTTTAACAAAAATCGAGTATACAGGTGCTAATAAGAAAGTACCCTTCCACATTGGATTAAGT\nAATATCGATGCAATATTTGTGGAAGACATTGGTGGAAAGGAATCTACTAAAGAACCTGATCATCCAATTG\nAAGATTTCTATGGTTGTGAAATTAAGCAAGATGATAAGTATTTTATGTTCGGACAAAATGCCGTGCTTGA\nAGGGAATCTAACAAATTACTTAATTGCGGAACAAAATGTTGAATGCTTTCGAGCTGTATAAAAAGGAAAG\nGGCGGTAAGGAGTGTTGGCAAATGATTTGTTTGAAGAGAAACAACATCTAGTGTTTGCTGCAATTAAACA\nACAATTTGGAAGTATGACAAGGGCTGCGAAAATCGCAGAGTTAAACAATATGGAACTTGATGATTTAATT\nCAATTCGGTCGTATGTATTTATGGGAGCGTTGTTTAAAGCATGATCCAGAGAGAATAGAAACGTTTAGTG\nCATACGTAATGAGAGGTATGAAATGGGCCATGAGTGATGAACTTCACTTGAAAGGGAGCCTGTTTAAGAT\nTAGCAGACGGATTAGTCATGAAGAAAGGAATAAAATCAACATTCATTCGATTGACTATCATCAAGAGGAG\nGAAGAGGTACACGGATTTTATGCTGTGTCTCCTATCGATGTGGAAGAAGAGGTAACCAAACATATCGAAT\nTTGAAGAAGTAACGAGCGTTCTTGAAGAAAAAGAAAAGTCCATCATTATGCACGTTGGTGAAGGGTATAC\nCACAGAAGAGATTGCTGTGAAATTAGAAATGAAAAAATCAACAGTTCATACAACGAAAACACGTGCGTTT\nAAAAAGATGAACCCAGATTATAAGCCAATAAAACAAAAATCCTTTTTCTTGGGAAAGAGGATAATAAAGA\nGAAACCGCCAGTTGGGGCTGACGGTCTAATAAAAACACATGTTGAGGTCATTATAGCATGAATTGATTTT\nGTGTAAAGGAGAGGCTATGTCTTGAAGAACGGTAAAAAGCCAAACAAACGTGAAAAAATTCATATTCAAT\nCACACGATTTAAATCCACAGGATTGGTTGATTTATAAGAAAGTAAATAAGGAATTGCATTTGGTCCATCG\nGACTACTGGTGTAACTCGTATAATTCCAAATTTATAGATTAGGAGAAAGATATAAATGGCTAATGAAATC\nACGCCTAAATTAGTTGCTGATATAACAGATAAAAGTTTTGGCATACAGCTAATTGTTACTGGTCTTGCTC\nACTTAGTAGAGGAAGAGGGATATACACCACATGAAGCATTAAGTATCGCTCGTTACACAGGAAATAATTG\nTTTCCATGCGTTAGCAGAATTGAAGAAGGAGGCTAAAAAATGAACGACAAACCAATTGATGAATTAGTCG\nCGGAAAAGGTTATGGGATGGATAAAACCACCTGAAACATCAATCCTTAAATCAATGTGGGTTTCTAAGCC\nAATAGGTATGGTTCATCGTGAATTACCTAAATTTAGTATGAATATGAAAGATGCATGGTTAGTTGTTGAT\nAAATTACAAGAGTCATTTAAATCAGTGGAAATATTTATTGAAGACAGAATGACAAATGTGATTATAACTG\nAACATTTCCCAAGTGGACATCTAAAAGATAAATATCAGGGATATGAAAGATCGGCTCCTTTAGCTATTTG\nCAAAGCTGCATTAAAAGCTGTAGGGGAGGAATGGCAGTAATGGATATTAAATCAGTTGCTAAAGCTGTAC\nAAGTTATTCGAGAAGCACAAAATGAACATGGAATCATTAGGATTGATGGAAAGGAAGTACATCTAAAAAA\nTGAAGTATTGGAATCATTGTTAGATGAATCTCAGACTAAGCCTTTAATACTAAGACGTGAATCCAAGTAT\nTATCCTTATGAAGTTTCCTTTATTAATGATCATGTAACCTATTTCTCTCTTTACACTGAAGAAAGAATGA\nAAGAGAAAATTGGAGGGATACCAAATGCTCGAAAATTCAATGGTAATCGGGAACCGTCAGGACTCCCCAT\nTCAATAACGTGATGGATCATTGTCAAAGTTGTGGTAAAGAAATCTATTTTGATGAAGAGTACCGAGATAT\nTGATGGTGATTACATACACGATGAAACAGATTGTATCAAACAATATGTAGAGTCTCATTCCATAAAGAAA\nGTAGCTGGTGAGTAAAATGAACGCTGCTATTGAAGAATTAGAAAAGTCATTATATGTGGAGCAAGGGAGA\nTTAAAAGACTATCACGGCAAGCTAGAGAGGGTAATAGAAAGAAAACCAATCCTTGAAAAGAATATCCAAG\nATACTGAAAGCAAGATCCAGGACATTGAAGCTTCAATTTTTGTTCTGAAAAATATGGTGAAGGAGTGAAT\nTAATTGGAAATCACAAATGGTGCTGAAATTATCAAAAGTGAAAAAGCAAAAATTATCATTTATTCAAAAC\nCAGGTAACGGTAAAACAACGGTTGCTGGATTGTTACCAGGTAAAACATTGGTGTTTGATATCGATGGGAC\nAAGTCAGGTGTTATCGGGTTATAAAAATGTAGATGTAGCTAAAATTGATGGTGAAAATCCACATGATAGC\nATTTTACAATTCTTTGCACTTGCTAAAACAAACATTGGTAAGTATGACAACATCTTTATCGATAACTTAA\nCGCATTACCAAAAGTTATGGCTGCTTAATAAAGGTGAAAAAACAAAAAGCGGTATGCCTGAATTAAAGGA\nCTATGCTTTACTAGATAACCACCTTTTAAAGTTAGTAGAAACATTTAATTCATTAGATGCAAATGTTATT\nTTCACAGCTTGGGAGACAACAAGAAATATCACTCATGATGATGGTCAGCAATATACACAATTCATTCCGG\nATATTCGTGATAAAATCGTAAATCACATTATGGGAATCGTTCATGTTGTTGGTCAATTAGTGAAAAAGGC\nAGATGGTACAAGAGGTTTTGTTTTAGAAGGTAATCAAAGTATTTTTGCTAAGAATCATTTAGATCAGCGT\nAAAGGTTGCGTACAACAAGAATTATTAGTGTCATCCACAAACTAAAATACAGGGGGAAATAAACAATGAG\nTTTTAAATTTAAATTTGATGAAGAAAATGTATCACAAGGGTTTGGATTGGTAGAGGAAGGTAAGTATGAA\nGTTACAATTATTACTGCTGAAGCAAAAGAATGGCAAGGTCAATATTCTATTGGATTTGATGTGGAAATCC\nGTTCAGATATTGAACAAAAACATCAAGGAGCAAAAATCCTATATAACACTCTATATCTAACTACTAACAT\nTCAAGAATATGCAGAGGACACGGAAAGAAGACGTAACTCATTCTTAAAAGCTTGCGGATACACAGGTAAA\nCAGGATTTGGAATTAAATGTTGTTGTACGTGAGATTGTAGGTAAAACGGTTTTAGCTTATGTAAAACATG\nAAACAAATAAGGATGAAAAAACATTTGCTAAAGTTAAATTTGTGGCACCATCGAATGTAAAGCCGTCTGA\nACCAAGTGGACCACCGATTACTGTTGGCGATGATGATTTACCATTCTAAATAACTAAATAGAGAGGTCGG\nTTTTGTCGACTTCTCTTTTTTATACCCTAAAAAGTTAATTGGAGGGCGCAATGAAAGAAAATCCATACAA\nTTTTAATGAAATTCCTGCTGAATTAAAGGGCCTTCCCCAGTGGATCTTATGGAAGCTTGAAACCAGAAAT\nAATAAACAAACAAAAGTACCCTATCAAGTAGATGGAGAAATGGCCCAAGCAAATAATAGACGTACCTGGT\nCAACATTTGCAACGGCAGTCAAATTTTATTTAGAAGGTGACTATGATGGAATCGGGTTCGTGTTTAGCAG\nGCAGGACAATTACATCGGAATCGATATTGATAAGTGTGTTACGGACGGAAAAACAAATGCTTTTGCAACG\nGAAATTATCGATACATTAGATAGTTATACGGAGTTTTCACCTTCAGGAAAAGGTATCCACATCATTATCA\nAAGGGAACCTTCCACAATCTGTTTTAGGTACAGGACGAAAAAATACAAAGCACGGTTTAGAAATTTACTC\nATACGGACGTTTCTTTACCTTTACTGGAAATCGTGAGAATTCCAATGATGTATACGAGCGAACGGATGAA\nCTAGCTGAAGTATTTGAAAAATATTTTGATGATAGCGACATTCAAGGTCGTGTAAATTTAGCAGAGTTTG\nAAAAAGATGAAATCAAAATTTCGAACGATGCTCTATGGGAAAGGATGTTTAGAAGTAAGAATGGTGATGA\nAATTCGCTCGTTATACAATGGCAGCTTAATAAATGATGATCATTCAGCAAGTGACCTTTCTCTATGTAAT\nCATTTAGCATTTTGGACAGGGAAATCAGCAATTCGAATGGACTCCATGTTCCGTGAGTCAAGCCTTATAC\nGTGATAAATGGGACGTTATTCATTTTAGCGATACAAATGAAACATACGGTGAAAGAACGATAGCAACAGC\nCATTTCATCTACTTCCACAACTATTTTAGATAACAAACAGCAATTCGAAGAATTTTCTTTTGATTTCATG\nAATGAAGATGCGGTTGAAGTTGTGGAGGACAAACCGAAAAAGAAATTCCGTTTAACTGAATTAGGAAACG\nCTGAACGTATCGCATATGAATATGGCCATGTAATCAAATATGTTAGCGATATTGGCTGGTACATATGGGA\nCGGTAAACGCTGGAAGTTGGACACGAAAAAAGAGATTGAAAGAATTACAGCAAAAGTACTTAGAAGTCTT\nTATAAATCAGAAGATGAATTAGAAACAAAATGGGCTCGAATGTGTGAACGGAGAAATATTCGTATGAATA\nGCATTAAGGATCTTATGCCATTGGTTCCAGGTGAGCGTGAGGACTTTGATAAGTATAAATACTTGTTCAA\nTGTTGAAAATGGCATTGTTGATTTAAAAACAGGAAAGTTGCAGCAACATGATCGGGAACTTGGTTTAACT\nAAAATTACTAATATTTCATTTGATGAAAATGCAAAATGTCCAGAGTGGCTTAATTTCTTAGATCAAATTT\nTCCAAGGTGATAAGGAACTAACTGAATACATGCAGCGGTTAATTGGTTACTCACTAACAGGGGAAATCAC\nGGAGCAAATAATGGTCTTCTTAATTGGTGGAGGTTCCAACGGAAAATCGACCTTTATTAATACCATTAAG\nGACCTTTTGGGTGAATACGGTAAACAAGCAAAATCAGATACTTTCATCAAAAAGAAAGAAACTGGTGCCA\nATAATGATATTGCTAGATTAGTAGGGGCACGCTTTGTATCTGCAATCGAAAGTGAAGAGGGTGAACAACT\nCTCAGAAGCTTTTGTAAAACAAATAACAGGCGGTGAGCCAGTATTAGCACGTTTCCTTAGACAAGAGTAT\nTTTGAATTCATACCAGAGTTTAAAGTGTTCTTTACAACAAACCATAAACCAGTAATTAAAGGTGTAGATG\nAAGGTATTTGGAGACGTATCCGTTTAGTTCCATTTAACCTGCAGCTACCAAAAGAGAAACGTGATAAGAA\nATTACCAGAGAAAATTAGCTTAGAAATGCCAGGAATCCTGAATTGGGCAATTGAGGGTTGCTTGAAGTGG\nCGGAAGTCGGGACTAAACGATCCAGCAATTGTTATGAAAGCAACAGGTGATTATAAAGAGGAAATGGATA\nTTCTTGGTCCGTTCATGTTTGAATGTTGTTTTAAAAGAGAGGATGTCCAAATTGAAGCAAAAGAATTATA\nTGAAGTTTATGCGAATTGGTGTTTTAGAAATGGTGAACATCAATTAAAAAATAGAGCCTTTTACCGAATT\nTTAGAATCCCAAGGATTCAAAAGAGAACGTGGCAGCAAAAACAAGTATTACATCAAAGGTGTTACTCTAA\nCCGACCGAAAAAATACTTTTAAGCAGCAAAAGTTACTGAATTTCGATGAAAATAGCAAAAGTGTTACTAA\nAAGTAACCCATTTAAAATCACTTAAAACCCTTGATACATAAGGGCTCAAGATACTTTTTATATTCCTTTT\nGTTACTTTTGTTACTAAAAAATACTATAAACAAAAAATAAATATATATATAAGTATTCTATTAGGAGCTT\nCTTTGAACTTTTTAGGTAACCTTAGTAACCCGAAAGTAGCATGAGCCGTTGGGGCTGTAAGGCTCAAGGC\nGTGTTACTAAATGAAAAATAAGAGTAATTTATGGTGTTTTTTAAGTAAAAAACGGTTATTTAAGTAACAC\nACTTAGTAACGGAGGTTGTATTAAATTGGAAAAACATTATAAAGAACACGGGCTAGAAGATTTTTGGAAA\nTTTAAAATTATACGATCCAAGAAAAATGAAATTGGTTGTTCAGAAACCTATGAAAAATATAAAAAATGGT\nGCTATGAAAACAATACTATTCCGAATAAAAGAATTACATTTTTAAGATTCTTAGAAACAAAAGGGTTTGA\nAATTGTGAAGAGCAAAAAAGAACCATTGTATTTTAAAGGAATGAAGATTAAATGGTGAAAGTTTTATTAA\nTTTTAAGTGCGATTTGGAAATCAGGTGCAGATATCTATCTTGATAAAAAGGATAATCAAGTTGCGATAAA\nAAAACAAAATTTAATTCCAGCGGAAGTAATGAAAGCCGCTGAACAAAACTATCAAGCTATTTATGATTGG\nTTTCAATCTTGGAAAGATGAGAGTGCGGAGAAAATTACGTTAATGAAGATATTTCATCATTTTTGTGGGT\nGGAAACATAATCAAAAATTACACAATTGGTTAGTTGAAGAAGAAGATTCATTGCAACTGTTTTATGAGTG\nGACGATTGTCCTTGCTAATAATGGTTGGACAGATGTTTATGAGGATCATCGTCAGTTTGAAAATGATGAA\nTCAAATGCAATGGCAAGAAAGATATATGAACGTGCGGTTTTATATGCAAGGAAAGGGGCATGAAAATGAG\nAGAGATAAAATTCCGTGCTTGGGATGGAACGAGTTGGGTTTATAGCGAATGTATATCAAAAGATGGTATT\nAATTGGTGGATATTAAATAATGAAGATGATAATTGGTTGACGTGTTTAGATCCACAGCAATATACAGGTT\nTAAAAGACAAGAACGGTAAGGAGATTTATGAAGGAGATATTACAAAAGACAAGTTTGGTAATCTTGATGT\nTATTTGTTGGATTAATAGTTCAGGTGCATATGCGACTGTGTCGATTAATTTGTATTTAGACGGAGAGTAT\nGAACATACGGTTGTTGATGAATTTGGAACGGATTGTTTCTTTGAGAATAATGTTCCTGGTGATTTTTTAG\nAAGTAATCGGAAATATCTACGAAAACCCAGGGTTACTGGAGGATTCAAAATGATTCGTTTCCATTACACA\nGATAAAGAAATAGAAAAAATCCTTAAAACACTCACTATCGTTATCGATACTCGTGAAAATGTAAATGACC\nACATTCGTGATTACTTATATCAAAAGGGCATCCCAATTAAAAATCAAAAATTAGATACCGGTGATTATGG\nTTGCATGATTCCCAAAAATGAAGAGTTAGGAATACCACGTGATATTTATTTAGATCGTCGGATAGAAAGA\nAAAATGAGTATCGATGAAATTACAAGTAACCTACAAAAAGATACGCAAACAAGATTTGAAAATGAATTGA\nTTCGATCGAAGGATATTCCATTCACTTTAATTGTGGAAGATCAACGTGGTTACGAGAAAATACTTAAAGG\nTGATTATAAATCAAGATATAACCCATTGGCATTACTCGGTAGGCTTAATACTTTTAAAGCAAAATATGAT\nTTTGAAATAGTCTATCTAGATAAAAAGTTTGTTGGTAATTGGATATATTATGTCCTTTATTATCATGCAA\nAACATTATCTTAAAACAGGTGCATTTTAAGTTCAGAAACGTACAGAAATAACAGAAAAACTTTAGTTCTA\nATATCAATTTAATATAAAAGGAGTCGGAAGACATGACAAAGGTAAAATTGAACGTATTATTCAAGAAAAT\nGCAAAAGGATGATAAAAAGGAAGTTTTGATGTTCCACGTATTAAGTGATGAATTACCACATGCTGATGAG\nTTATTGAAGATGCCAGGTACTATTGTTTATCTAACTGTGGAAAAAAGCGATGTTGAAGCAATTGGTGCTG\nAATTTGTTTCTATTCAACGTGATAGTAAGAAAACCGTTCTTAAATTCAATGTAAAAGGCGATACGAAAGA\nTAAAATTAATAAACTTTATCCATTCGCTGGTGAAAATGTTTCTATTACTCTAGAGCCTTCGCAAATGTCG\nATTGATGAGTTTTACGAAGAACAACATGAAGGAGTGGAGTATAACGTTAATCCTGATGGAACAACTGATG\nTTGCTCCGGGGCAATTGAAGATTGTTGATGAAGAAACGATTGCTGAATAAAAATTTATCCTGGGCTTCGG\nCTCAGGATATTAATACATTTTGAATTTTGTTAAGAAATGAGGGTAACTTTTGAAAATTATAAAAGATGAT\nAAGAAGTGCCAAACATGTATTTTCTATGGTTTATGCACGAAAGCGCACTTACCACACTGCCTAGGAAATG\nATTACTTCAAAGACAGTGTCCAAAAAGAAAAATAAAACTAAAGCTAAAGCGTTACTTTAATCGGAAATGG\nCAGGTAATTGACCAAATCACCTGCCATTTGCCTAAACAGTCCGGAGGGGTAAAGCTCCGTTTTGAAAGAG\nTGTAGCCGACTCGTAGATAGTATGTGTAATGTAAAAAAGATTATTCGTATATCACACGGGATATGAAAAG\nGAGAATGAAAAATGTCTAACAAATTTGATAAGGACTTTGAAGCAATTACGAATAATGGTGAATTAACGAA\nAGAAGGAACAGAATTTATAGAAGCTGTAAAGCAATTCGTCGGTACGCAATATGATTCAGAGGATTTAGCG\nAAATTAATGGTATTAATTATGGCTGCTTTAGATGTGGATGACAATGCTTTTAATACAGCGATATCCGCTT\nTATATCAAACTGCAATAGAAGTGCAAACAGGTATCAATCTGAATGAATTACTGGATTTAGTGACAAAAGG\nTGAACCAGGCTTAACTCATTAGGAGAACCCAATGTATTCGACGAGTTTCGACATGAAAACGACCGTCAGA\nAACATAGTGATTTGAAGTTTTATTTCTTTCTGAATACAAATAGGTGCACAAGTGTTAAAACGTCTTAGAA\nAGGAAAATAAACGTGTTTTATGAGATGTATTGTTTTTTATAGAAAGTAGGTGAATCATCATTTGTTTGAC\nTGGCTAAAAGACTATCAGAAATTAGAAGAAGACATTGAGTACTTAGATTACAACTTAGATAAAACAAAAG\nCAGAATTAAAACGCTGGGTCAGTGGTGATTTGCGAGAGGTACGTTTAACTGCTGAATCGGAAGGTGCAAA\nGGTAGAAGAACGTATAGAAGCAATTGAATATGAGTTAGCGCACAAGATGAATGCAATGCAGGATGTATTG\nAAATTGATAAATAGGTTCAAAGGTTTAGAAAATAAAATGTTAAAAATGAAATATGTGGACGGAATGACAT\nTAGAAGAAATAGCTGAGAATATGAATTATAGTTCTAGTTATATCTATAAGAAACATGCTGAAATAATAAG\nGAGAATAAAGTTTGCTGAAGAACTTGCACTTTACTGACACCCAGTTTTATGAATGTTAACTCTTGAAGAT\nATCGATTATAGTAATAACATAAGAAATTGACGAAAGGGCAACTGGTGCACAGTTGCTCTTTTTAATTAAA\nCAAACCATATCCATATAATAATGATAACAGCAAAGATAATGATTAGTATTTGTGAGAATTTCATAACATG\nCTCCTTTTAAACTATAGTGTTTGCAAAGGATTGAAGAGGCATTCCTTATGGAGTGTTTTTTATTATGTAA\nAAATTATATAGGTGGTGTAGAGATGACTTTAACGTTGCATAATGGAGATTTGAATAAGTTAGCAAGAGAT\nACTTCACAGGACAGTATCATCTTGAGAGTTGGTGAACAAGAAATGGTATCTCTGAAAAGCAATGGAGATA\nTCTATGTTAAAGGTAAGCTTGTTGAAAACGATAAAGAAGTTGTAGATGGCATGAGAGAGTTATTGATGTT\nATCTAGGAAAAGGTAAGCGCAAACGTGTTGCATTTTATAAGGATGGTGAAAAGAAGATGTTCTCATATAA\nAAAACGTATTGAATCCTTAGATGAACTTCATAAAGTTATTGATGCATTAGAAACGTTAAAGAAGGAGTAT\nCAGATTATCAAAAAGATAGAATGGTCGGAACCTAAATCACCTCTTCCTAAATTACCAAAGAATGTTTGGT\nATGTTGAAGAAGTTGATACATCTAAAATCTTTTTTACTGATGCTGATGCAATAGTTAAATTAGTTTGTAA\nAAATTGTGGAATATCGTGTAGAGGGAAAAGAAATCTATTAGAAGGAATGAGTTGTATTTATTGCTTTAAT\nCACAATACAACAATAGTTTCTTTAGATAAGGAGTTTGAATGTAAATGAAAGTAATTATGGGTGAAGAACC\nTTTATTACCTAATGGAAAAAGAAATGGAGAAGCTGTTAGAAGTATGCTTGATAAAATTAGGTCGCAAGAA\nCAGAAAGATAAGGAGAGTGAATGCAAATGATTACTGAAATTAGAAAAACAATATCTGGTACAGAGTATTG\nGGATAACAAAGAAAAACGAAGTCTATTTGTTCCTACAGATGAAGAACCAGGATTCGAAGTAACTGTTAAT\nCCTGAGAGTATGATCTTAGGCATGGACATATCAAGTGAACCTGATAAGACAGTAGTTAATTTAAATGGTA\nTGACAGTGAAACAATTACATGAATATGCTGCATCGATTAATGTTGAGATTCCAGCCGATGTTAAAAAGAA\nAGAAGACATCATTGATTTACTATCATGAAGTACTGTGCTGAACAAGGCTGCAAGACATTAATCGATAAAG\nGACGATACTGTCTCAATCATAAACGTAAACAGAAGAAGACAGTTGTGTATTCAAAGAACAGATCATTCTA\nTCGTACAAAAGCCTGGCAAGATTTAAAGTCATTCTGTTATCAAAGAGACAAAGGATTGTGTCAACGATGT\nGGAAGGTTTGTGTTTGGTAAGCAAGCACATCATCATCATATTGTTCCAATTAAAATCAATCCTTCATTAA\nGATTAGATCCAGATAATATCGATACACTTTGTTCTAAGTGTCATCCGATTGTAGAAAGAGAAACAAATGA\nAAAATACCAGGAAAAGAAAAAGTTCGACTGGAAACTATAAGCCCCCCCTATCAAAAAAAGAAAAGCTGGC\nCTTATGGGGGGATAGGGAGTGGGGGTGCAAACGCGCACCTCAAAATGGTTTTTTGAAAAAAATTTGTTTT\nTTTTAGGTGGTGATTTAAGGAATGGCCAGAAAATCGAAGGTCGTAATTGAAGCTGAAAAGAAAAAAGAAT\nTAGAAGCGCAGCGTATTATGGATGTTTTGGTTGAAGCCGGAACTTATTCGCCAGCGCTCGATCCATTAAT\nTGAAGTTTATCTTGATGCAGTTGAGATATACAGCGTCAAATATGGATTGTGGAAGAATTCTAATTTTCCA\nACAGTCCAAAAAACAAAGAATGTAAATGGTGATGTGAAAGAATCAAAGCATCCATTAGCTCAACAAGTTG\nAAGTTTGGTCTAAGCAAAAAGCGAAATATTTGGGGCAATTAGGACTGGACGGAAAGAACAAAGATTTACT\nTAAAAAAAGTGGGGTTCTTCTCGAAAAAGGAAAAAATGAAAAAGAGCCCACGGAGTCTACTGATAACAAC\nAAATTATTGCAATTTAGGCAGAGGTTAAATAGATGATTGATTTTGAAACAAATTACGCTGATATATTCGT\nTTCGGAAGTAGATGCAGCCCCGCACTTATATCCTGATTCAATTAAATTAGCAATCAAACGATATAAGAAA\nTGGAAGAAACGAAAAGATATTTGGTTTGATGTTGAAAAAGCAAATGCTATGATTTATTTCACAGAAACAT\nTCTTAAAACATGCAAAAGGAAAATGGGCAGGACAGCCGTTAATTTTAGAATCCTGGCAAAAGTTCTACTT\nTGCTAACATTTATGGATGGCAAAAATATAATGAAGATGGTAAAGCGGTGCGAGTGATTCGTACGGCTTAT\nTTGCAGGTTCCAAAGAAAAACGGAAAAACAATCATGGGCGGTTCACCTGTTATTTATGCGATGTACGGTG\nAAGGTGTAAAAGGCGCAGATTGTTATATTTCCGCTAATACTTTTGAACAATGTCAAAATGCAGCTGGACC\nAATTGCATTAACTATTGAAAATAGTCCAGATTTACGGCCAGATACACGTATCTATAAAGGCAAAGAAGAC\nACGATTAAATCAATTAAATACACATTTGTGGAGGATGATATAAAATATGCAAATGTAATTAAGGTTTTAA\nCGAAAGATAACGCTGGTAATGAAGGTAAAAACCCGTATATTAATTATTTTGATGAAGTTCATGCTCAAAT\nGGACCGTGAACAATATGATAACTTACGTTCAGCACAAATTGCCCAAGAAGAACCACTCAACATCATCACT\nTCCACAGCAGGGAAGAATACCGGCTCGCTTGGAACTCAAATTTATACCTATGCAAAAGAAGTTTTGGATA\nAGGATAAAGATGATTCTTGGTTCATGATGATCTATGAGCCGAATAAAAAGTTTGATTGGGAAGACCGTGA\nTGTTTGGCGAATGGTTAACCCGAACATGGATGTATCAGTTAACATGGAGTTTCTTGAAAATGCATTTAAA\nGAAGCTCAAAACAACAGCTTTAATAAGGCGGAGTTCTTATCAAAGCATTTAGATGTATTTGTTAACTATG\nCTGAAACATATTTTGATAAAGACCAATTGGATAAAATGCTTGTTGATGATTTAGGAGATATTGAAGGTTT\nAACTTGTGTTATCGGTGTGGATTTATCAAGACGTACCGATTTAACTTGCGTATCGTTAAATATTCCAACA\nTACGATGAGGAAGGTCTTTCATTGTTAAAAGTAAAACAAATGTATTTTATTCCAGAGTTTGGAATTGAAG\nATAAAGAACAGCAAAGAAATGTTCCATATCGGGAATTAGCTGAAAAAGAATTTGTGACGATTTGTCCTGG\nTAAAACGGTTGACGAAGAAATGGTCAATCAGTACGTTGAATGGGTATTTGAGAACTTTGATTTACGTCAA\nATTAATTATGATCCAGCGCTTGCTGAAAAGCTTGTTGAGAAGTGGGAAATGCTCGGTATTCAATGTGTGG\nAAGTTCCACAGTATCCAACTCATATGAATGAACCATTTGATGATTTTGAAATCTTATTGCTTCAGGACCG\nAATTAAAACTGATAATCAATTATTAATTTATTGTGCAAGCAATGCAAAAGTAATAACTAATATTAATAAT\nTTAAAAACACCATCTAAACGAAAATCACCGGAGCATATCGATGGGTTTGTGGCCATGTTAATTGGTCATA\nAAGAAACGTTGAATATGATGGAAGATGCTGTTCCAGATGAAAATTATGATGAATATTTAGATGATATTTA\nTCGATAGAAAGGCGGTGAGGAATTGGGTTTAAAGGATAGATTTTCAAGTTTTTTACTTAAACAAGCTGAA\nAAGCGTGGTTTATTCGAAGACATTTTCAATAATGTTGTTCGCTATGGTGGTAGATATGCAGGCGATGATA\nATATCTTGGAATCTAGTGATGTTTATGAATTACTACAAGATATAAGTAATCAAATGATGTTGGCTGAGAT\nTGTTGTGGAAGAAAAAGACGGTAAGGAAATTAAAAATGATTCAGCTCTTAAGGTTTTAAAGAATCCAAAC\nAATTATCTTACACAGTCTGAATTCATTAAGTTAATGACTAATACCTATTTACTTCAAGGTGAAGTCTTTC\nCAGTGTTGGATGGTGACCAATTACATTTAGCATCTAATGTTTATACAGAATTGGATGATAGATTGATAGA\nACATTTCAAAGTGAATGGAGAAGAAATTTCATCATTTATGATTCGACATGTGAAGAATATTGGTGCCGAT\nCATCTAAAAGGTACAGGCATTCTTGATTTAGGTAAGGATACACTTGAAGGTGTTATGTCAGCTGAGAAAA\nCTTTAACTGATAAGTATAAAAAAGGTGGTTTATTAGCATTCTTACTTAAGCTAGATGCTCATATTAATCC\nACAAAATGGAGCGCAGTCCAAATTAATTAAAAAGATTTTAGATCAATTGGAATCCATCGATGATGCAAGG\nTCAGTTAAAATGATTCCACTCGGAAAAGGATATTCAATAGAGACGCTTAAAAGCCCGTTAGACGATGAAA\nAGACCCTGGCCTATCTAAACGTATACAAAAAGGATTTAGGTAAGTTTTTAGGCGTAAATGTGGACACATA\nTACGGCCTTGATTAAGGAAGACCTTGAGCAAGCAATGATGTATTTGCATAACAAGGCAGTTAGACCGATA\nATGAAAAACTTTGAAGACCATTTGAGTCTTCTTTTTTTCGGAAAAAATTCGGATAAACGTATTAAATTCA\nAGATAAATATCCTTGATTTTGTTACTTATAGCATGAAAACAAACATTGCTTACAACATTGTTCGAACTGG\nTATTACTTCACCAGATAATGTTGCGGATATGCTTGGATTCCCTATGCAAAATACACCTGAGTCACAAGCG\nATTTATATTTCAAACGACTTATCAAAAATTGGTGAGAAACAAGCTACAGATGATTCACTGAAGGGAGGTG\nATGGAAATGGCAAAGACAAAGGAAACACGGACATTTGACATCACCAAATTAAGTACCAGGGATGCTACGG\nAAGAACAACCTTCCAAGATAACGGGTTATGCAGCCGTATTTAATTCAAAGACAACTATTGGTGGCTGGTT\nTGATGAAGTTATTGAACCTGGTGCATTTGCTCGTTCTCTTTCTGAGAATGGTGATATTAGAGCGTTATTC\nAATCACAATTGGGATAATGTCCTAGGGAGAACAAAAAGCGGTACATTGAGACTAGAAGAGGATGAAAAAG\nGACTTAAATTCGAAATTGAATTACCAAATACATCTGTTGGTCGAGATTTAGCTGAAAGTATGTCCAGGGG\nAGATATTAACCAATGCTCATTTGGATTTTGGATAACAGAAGAGAATTGGGATTACAGTGTTGAACCAGCA\nTTAAGGACCATTAAAGAAGTAGAACTTTATGAAATATCGGTTGTTTCAATACCAGCTTATGACGATACGG\nAAGTATCTTTAGTTCGCAGTAAAGAGATTGGTAAAGAAATAGAACAACGAATGAAAATGATTAAACAAAT\nAAATCAAATCTTGGGGGAAAAGTAAAATGAACAAACAATTATTATTAGCATTACAAAAACGAAGCAATGA\nAAGATTAGTGGAATTACGTACACAGGTTGAGAATCCTGAATTACGTGCTGAAGACTTACCAGCAATTCAA\nGAAGAAATCGATGAAATTAACAAGCAATTGCAAGAAGTTGCGGATGCTTTAGCAAATCTTGAAGATGATG\nGTGGAGGTGAAGAAGGAAACGAAGATAATGAAGAAGGTGATGAGGGATCTGGTACTGAAGGTTCTGGAGA\nAGGCGGAGAAGGGCGTGCTAGCAATACTGAAGGTGGAGAAAATAGAAATGGATTAACGCCTGAACAAAGA\nAGTGCAGCAATGGCAGCTATTGCAACAGGTCTTTCTACTCGAGGCCATAAATCTACTAAAAAGAAAGAGA\nAAGAAATTCGTTCGGCATTTGCTAACTTTGTAGTTGGGAAAATTACAGAAGCTGAAGCGCGTTCTCTTGG\nTATTGAAGCTGGTAATGGTTCAGTAACTGTGCCAGAAGTTATTGCGAGCGAAATCATTACTTATGCTCAA\nGAAGAGAACTTACTACGTAAATATGGTTCAGTTCATAAAACAGCAGGTGATATGAAATATCCTGTTCTTG\nTTAAGAAAGCAGATGCAAATGTACGTAAGAAGGAACGTAAAGATAGTGATGAAATCGTAGCAACAGATAT\nTGAATTTGATGAAGTGTTACTTGATCCAGCTGAGTTTGATGCACTTGCTACTGTTACTAAAAAGTTATTA\nAAAATGACAGGTGCTCCAATTGAGCAAATCGTTGTGGACGAGCTGAAAAAGGCTTATGTTCGTAAAGAAA\nTTAACTACATGTTCAATGGCGATGATGTAGGTAATGAAAACCCAGGTGCGTTAGCAAAAAAAGCGGTAGC\nGTTTAAGCCTTCTAATCCAGTTGATTTAAAAGCAAAAGATGCAGGGCAATTAATGTATGATGCATTAGTT\nGAAATGAAAAATACACCTGTTACAGAAGTAATGAAAAAAGGACGTTGGATTATTAACCGTGCAGCATTAA\nCAGCAATTGAAAAAATGAAAACAACTGATGGATTCCCATTACTACGTCCAATGACACAAGTAGAAGGTGG\nTATTGGAAATACGCTTATTGGCTATCCTGTGGACTTTACTGATGCGGCAGACGTAAAAGGAAAACCAGAC\nGTTCCAGTTTTATATTTTGGTGATATTTCAGCGTTCCATATTCAAGATGTAATTGGCGCTATGGAATTAC\nAAAAATTGATTGAAAAATTTGCTGGTACAAACAAAGTTGGATTCCAAATTTACAACTTATTAGATGGTCA\nATTAGTTTATTCTCCATTTGAGCCAGCTGTGTATCGTTTTGAAGTGCAAGCTACAACTGAAGGTAAATAG\nGTTATGAATGATTTAATTGAGAAATTAAAATCTCATATTCATTGGGAAGAGGGTATGGATGAAACCATGC\nTCTCTTTTTATATCACTCAAGCAAGGACTTATGTAAAGAATGCGACAGGCAAACAGACCGAATATCTAAT\nTATTATGGTCGCCGGCATTTTCTATGATTACAGGGTCGCTGAAAAAGAATTAGAACAAGCTCTTGATGCC\nTTAACACCAATGTTTGTCCAGGAGGTTTATGCTGATGAAGAGAAAGACGAATAAACTCAAATGGATGGGT\nGAGCTACTTAAATTAGGAGAAACAATTGATCCGGAAAATGACCGAGTTGTTATGGGATATCCATTAGAAC\nGGAAAATTCGTTATAACAACATTGGAGTTACGGCTACTGATAAATTTACAACGAAAGATACGAATGAAAT\nTGTAAAGAAAATTGAAGTTCGTATTGATCGAGATATTGAAAACGATCAAAAGGATTATCGTGTAAAAGTT\nGGTGGCCGTATTTATAACATTGAGCGCATTTATGTGAAAGAAGAAGATCGATTGATGGAGGTGTCACTAT\nCGTATGCAAATTAGTTTTGAACAGTTGCGAAGCCTTATGAAGAAATCTGGTATTCCAGTTTCTCGTGATA\nGTGCTCCTACAGGGATTGATTACCCTTATATTGTGTATGAATTTGTGAATGAGCAACAGAAAAGAGCTTC\nTAATAAGGTTCTAAAAGATATGCCACTTTATCAAATTGCTGTTATTACAAATGGAACTGAAAAAGATTAT\nGAGCCGTTAAAGGCTGTTTTTAACGAAGCAGGCGTGTCTTATTCTCAATTTGATGGAATGGGTTATGACG\nAGAATGATGACACTATCACGCAGTTTATAACGTATGTGAGGTGTATCCAGTAATGGCTTCAAATAACAAT\nGGTTTTGCTGAAGCTTTAGAAGATATTAATACGCTATTACGATTGAATAAAAAGGTCGAACTGGATGTAT\nTGGACGAAGCAGCGAAGTATTTTGCGAGTAAATTAAAACCAAAAATTAAAGCATCCAGTAAAAACAAGCG\nGACACATTTAAGGGATAGCCTAAAGATTGTTGTGAAAGATGATCGTGTATCTGTGGAATTTAAAGATGAA\nGCTTGGTATTGGTACTTAGTTGAACATGGCCATAAAAAAGCAAATGGTAAGGGACGTGTGAAAGGAAAAC\nACTTTGTTCAAAATACCTTTGATGCAGAAGGTGACAAAATCGCTGATATTATGGCACAAAAAATAATTGA\nTAGAATGTGAGGATGATATACATGACAGTTGAAAATAAAGAAATTCAATATTCTGTAGGGATCGAAGATT\nTATATCTGTGCTTGATGAAGGGAAATGAAACTTCTAGTGCACTACCAACTTATGAGGATATCGTTTATAG\nACAAACGAATATTTCTGATTTAACGATTTCCACTACTTCTACTAATTTTACAAAGTGGGCATCTAACAAA\nAAAATTATTAACATTGTCAAAAATACAGCGTTTGGATTAGCTTTTAATCTTGCTGGTCTAAATCGTGAAG\nTAAAAGATAAAATCTTTGCTAAAACACGTAAAAAAGGTGTGTCTTTTGAAACAGCGAAGGCGAAGGCGTA\nTCCAAAGTTCGCAGTAGGGGTTGTATTCCCTTTAAATGATGGAACAAAAATATTACGTTGGTACCCAAAA\nTGTACAGTTGCTCCAGTAGAGGAATCTTGGAAAACACAAGGTGATGAAATGACTGTGGATGACATTGCTT\nACACAATTACAGCAGATCCATTGTTATTTAATGATGTAACACAAGCTGAATTGGATACTGGTGATCCAGA\nGGCAAAAGGAATTAAAGCTGAAGATTTCCTAAAACAAGTCATTTGTGATGAATCTCAACTAGCGCAGCTA\nGGTGGAACGACTCAAACAGGTAAATAAGGAGGGTGACTATGGCACGTTTAAGTGATTTAGTTAACGTTAA\nTATAACTAGGAATAGCATTAAGATACAGGGTGTCTCAATCCCTGTTATTTTCACTTTTGAATCTTTTCCT\nTATGTGGAAGAAGCATTTGGAACACCTTATCATGAATTTGAAAAAGAAATGAATGATATGTTAAGGAAAG\nGTCAATTTAGCCTGGGAGAAAATGAAGCGAAATTGATGCGTGCATTAATTTATGCGATGGTACGTAGTGG\nTGGTACGGAATGTACATTAGATGAATTGAAAGGTGCTATTCCTATGAATGAATTACCTGATATTTTCATC\nGTTGTATACGAAATTTTCAGTGGCCAAACTTTCCAGAATTCTGATATGGAGAAGTTGAAGCAAGAAAAAA\nAGTAAAAAACATACTGACTAAAAACGAGGAATCTCAGTCCGAATTGGACTGGGATTTTTATTTTTATGTT\nGGTAATACGTTGCTTGGTTTAAGTATGAATGACTTCTGGAAAATCACACCTGCACATTTTTTAAAGCAAT\nTCATCATGCATCTCAGATACAACAATCCGGATGCGTTACATGAGCAGAAAACGAAACAAATTTACACGCT\nAGATCAAACACCATTCCTATAAGAAATGAGGTGAGAAAATGCCTGGGAATAGTAAAGAAAGAAACGTTGT\nTCTTAATTTTAAAATGGATGGCCAAGTTCAGTATGCAAATACATTGAAACAAATCAATATGGTTATGAAT\nAATGCAGCGAAAGAATATAAAAATCATATTGCAGCAATGGGCCAAGATGCGACGATGACTGATAAACTTC\nTTGCTGAAAAGAAGAAGCTTGAAATTCAAATGGAAGCAGCTAAAAAGCGTACAGCTATGTTGCGTTCTGA\nATATCAAGCGATGTCCAAGGACACAAGTACAACCGCTGAACAACTCAATAAAATGTATGGAAAGTTACTT\nGATGCAGAACGTGCTGAAACTACTCTTAATAATGCAATGAAAAGAGTGAATGAAGGTCTTTCAGAGCAAG\nCCATTGAAGCACGAGAAGCACGTGGAGACATGGAGAAACTTGAAGCTAATACTAAACAACTAGAAGCTGA\nACAAAAGCGACTAACAAGCTCGTTTAAGCTTCAAAATGCCGAACTAGGAGCGAATGCTAGTGAAGCTGAT\nAAGTTGGAATTAGCGCAAAAACAATTACGTCAGCAAATGGAAATGACAGATAGAGTCGTCCACAATTTAG\nAACAACAGTTAAGTGCAGCAAAGCGTGTATATGGTGAGAATTCCACAGAAGTACAGCAACTTGAGACGAA\nGCTAAACCAAGCTAAAACCACGTTGAAGCAGTTTGAGAATTCATTACAGAGTGTTGGTCGAAGTGGAGAT\nCAAGCAGCAGATGGTATGGAGAAATTAGGAAAGAAGTTAGACTTGCACAATATGATGGAAGCTGTCCAAA\nTGCTACAAGGAGTATCACAACAGTTAATTGAACTTGGTAAAGCTACAGTGGGTATAGCGATAGATTTTGA\nTAGGTCACAAAGGAAAATACAATCCTCATTAGGGCTAACTCAAAAGGGTGCAGAGAATCTTGGCAAGATT\nTCAAAAGATGTGTGGAAAAAGGGATTTGGTGAAAGCCTTGAAGAGGTCGATAATTCACTGATTAAAGTCT\nATCAAAATATGCGTGATGTTCCACATGAAGAATTACAAGGGGCATCAGAGAATGTTTTAACATTAGCTAA\nAGTTTATGATGTGGACTTAAATGAAGCAACTCGTGGCGCAGGACAATTAATGTCTCAATTTGGTTTATCT\nACACAACAAACATTTGATTTATTGGCAGCAGGTGCTCAAGCTGGGTTGAACTATTCTGATGAACTCTTTG\nACAATCTTTCAGAGTATGCACCGTTATTCAAACAAGCGGGTTTTAGTGCGGATGAAATGTTTACCATTCT\nTGCGAATGGAACCGCAAATGGATCGTATAACTTGGATTACATTAATGACCTTGTAAAAGAGTTTGGTATC\nCGTGTACAAGATGGTTCTAAAGGTGTATCAGAAGGATTCGGTGATTTATCAGAAGAGACACAAAAAGTAT\nGGGAATCATTCAATGAAGGTAAGGGAACCGCGGCTGCTGTATTTAATGCTGTATTAGGTGACTTACGTAA\nAATGGATGACAAAGTAAAGGCAAACCAGATTGGTGTTGCTCTATTCGGTACCAAATGGGAAGACATGGGG\nGCAGACGCCGTACTAAGTTTAAATGATGTGAATGGTGGTCTGGGTGATGTAAATGGCCGTATGGACGAAA\nTGAAAAAACTGCAAGAAGAATCACTGGGCCAAAAATTCCAGAGCGCATTAAGGGAAACTCAAACAGCACT\nTGAGCCTTTAGGAAAACAACTTGCGGATCTTGCAGCAGATGTTCTCCCTAAAGCTGCAAAAGGACTATCA\nGACCTTGCTGAATGGTTTTCCAAGTTACCAGAACCTGTCCGAAACTTTGTTGCTATTTCTGCCGGATTAA\nCGATTGCTATTACTGCAATTGGCGTTGCTATTGGTGTTTTAACTTTTGCAGTTGGTGCTTTGAATATTGC\nATTAGGACCTGTAATATTAGCGATTTTGGGAATTTCCGCCGCAATAACTATTGCTATAGCGATAGTGAAA\nAATTGGGGTGCTATAACCGATTGGCTTTCCGAAAAGTGGACCCAATTTAAAGATTGGTTTGGTGAATTGT\nGGTCTGGAATAGTTCAGGCTTGTAGTGATGGGTGGTCTTCCACAGTTGAGTACTTTTCCGAAGCCTGGTC\nGTCATTTATTGAAATGATGCATGAATTTTTTGACCCTATAGGTCAGTTTTTTAGTGAATTGTGGTCTGGA\nATTGTCGAAACAGCGTCATCTTGGTGGTCGAATCTTGTCACAACTGCATCAGAATTGTGGAGTCAACTGA\nCTCAAGCCTGGCAAGAAACTTGGAATACGATACTTACCGTCTTAGATCCAATTATTTCGGCGATATCTGT\nCGTTTTAGAAGCAGGTTGGTTATTAATACAGGCAGGTACACAAATTGCCTGGGCCTTAATAAGTAAATAT\nATTATTGATCCGATTACTGAAGCGTACAACTGGTGTAAAAATCAGTTCGGTGAGTTAGTTTCTTGGTTAA\nATTCACAGTGGGAAACGGTAAAATCTTATACACTTGCAGCGTGGAATTTGGTAAAACAGTATGTTATTCA\nACCGGTTCAAGAATTGTGGAATACAACAAAGCAAAAACTTGGAGATTTAGCTAATTGGATACTATCAAAT\nTGGGAATCTATAAAATCCTATACGCTTACGGCGTGGAATTTGGTGAAGAAATATGTGATTGATCCAGTAA\nCTGAAGCCTATAATTCAGCTAAGCAAAAATTTACTGATTTATATAATTCAGCGAAAGAAAAATTCGATTC\nTGTGAAGAATGCTGCACAAGAAAAATTTGATGCTGCTAAACGTAACATCATTGATCCAATAAAAGAAGCA\nGTTGGGAAGGTAGAAGAGTTTGTGGGTAAAATCAAAGGTTTCTTTGATAATTTGAAGCTGAAAATCCCTA\nAACCTGAAATGCCAAAGCTTCCACATTTCAGTCTGCAGACTAGTTCTAAAACAATTGCAGGTAAAGAAAT\nCTCTTATCCATCTGGCATAAATGTGGATTGGCGTGCTAAAGGCGGTATTTTCACACGGCCAACTATTTTC\nGGAATGAATGCTGGAAACTTACAAGGCGCAGGAGAAGCTGGACCGGAGGGGGTTCTACCCTTAAATGAAA\nAGACACTAGGTGCCATTGGAAAAGGAATTGCATCTACGATGACACAACAAAGTAATGACCGTCCAATTAT\nCCTACAAGTGGATGGAAGAACGTTTGCTCAAATCACCGGTGATTATACAGATCATGAAGGTGGAGTGAGA\nATTAGAAAAATCGAAAGGGGGCTGGCATAGATGCTATATGGAATTAATTTTAATGGAAAACATTCATATG\nACGATATGGGATACACTATGCCAGCTGATGGCAGAGATATTGGCTTTCCAAGTAAAGAGAAAATTGTTGT\nAAAAGTTCCTTTTAGTAATGTTGAATACGATTTTAGTGAAATATACGGATCTCAAACATATACTTCAAGA\nACATTGAAATACCAATTTAACGTTTTAAGGCAAGGGAATTTTACACCGCATGCAATGCAAATCGAAAAAA\nCAAAGTTAATTAATTGGCTTATGAATACTGGCGGAAGAAAAAAGCTTTATGATGATACTATTCCTGGTTA\nTTACTTTTTAGCTGAGGTAGAAAGTGCGGCTGATTTCCAAGATGATTGGGAAACGGGAACAATGACGGTA\nACTTTCAGAGCATATCCTTTTATGATTGCTGAATTGTATGAAGGTAATGATATATGGGATAGTTTTAACT\nTTGATTTGGATGTTGCGCAAACTACTAATTTCACTGTGAATGGTATGTTACAAATGGTTTTACTAAATGT\nAGGGGCTTCTGGTGTAGTTCCAGAGATAACAACATCTAAGCAAATGAAGATTATTAAAGATGGAGTCACC\nTATACTGTGTCAACAGGTATTACAAGAGATAAGAATTTTGTACTTAAATCAGGAGAAAATCCCATAAAAG\nTTACTGGTAATGGTACCATCTCATTCCGTTTCTATAAGGAGTTGATTTAAGTGTATAAAGTAACGATTAT\nTAATGATGGTATTGAAACAATAATTCATAGCCCCTATGTAAATGACCTTAAATTACCGTTTGGTGTAATA\nAAAAAAAGTATAAATCTAATAGATGCATTTAATTTTAGTTTTTATATGAATAATCCTGGTTTCCATAAGA\nTAAAGCCGTTAAAAACACTTGTAAATGTGTTAAATACAAAGACAGGTAAGTATGAATTTGAAGGGCGTGT\nGTTAGGTCCAAGTAAGAATATGGACAATTCAGGACTTCATAGTACTTCATATGAGTGTGAAGGTGAACTT\nGGGTATCTACATGATTCAGTTCAACGGCATTTAGAATTCCGTGGAACGCCAAAGGAACTTTTTGCAAAAA\nTTATTGAGTATCATAACAACCAAGTAGAGGAATATAAAAGATTTAAAATTGGAAATGTAACAATTACCAA\nTACTACAAATAACCTTTATCTTTATTTATCAGCGGAAAAAGATACTTTTGAAACAATTAAAGAAAAACTA\nATAGATAAATTAGGTGGCGAACTCCAAATACGTAAAGTAAACGGAGTTCGTTTTTTAGATTATTTAGAAC\nGTGTTGGTGAAGAGAAAAAAACAGAAATTCGAATCGCTAAAAATTTACTCAGTATGTCTTGCGACATAGA\nTCCGACTGAAATTATTACTCGCTTGACTCCTTTAGGTACACGAATAGAGTCAAAAAATGAAGGAGCGACA\nGATGCATCAGAAGCGCGATTAACTATTGAATCAGTTAACAATGGAGTACCTTATATTGATCATCCAAGTG\nGAATAAAAGAGTTTGGTATACAAGGTAAATCTATAACTTGGGACGATGTAACAATAGCAAGTAACTTACT\nTGCAAAAGGAAAAGAGTGGTTTGCAAATCAAAAATCAATTGTAACTCAATATAAACTAAGTGCAGTTGAT\nTTGTATTTAATTGGTCTAGACATCGATTACTTTGAAGTAGGGAATTCTCATCTAGTCATAAATCCTGTTA\nTGGGGATAGATGAGCTTCTAAGGATTGTTGGGAAATCCTTAGATATTAATAATCCACAAGGAGCCAGTTT\nAACAATTGGAGGTGCATTAAAAACATTAAATCAATATCAAAGTGATTTGAAAAAATCAGCACAGCAAGTT\nGTGGATTTACAATATACAGTGCTGAGACAAAACGGGAAAATCAATTCGTTGTCAGCCAGTCTTGTTGAAG\nCAGAAAAATTATTACAGTCCTTAAATGAAGCTGTTGAAAATGCGGATTTACAAATGATTGTTCAGTCAGT\nTTCTGATTTAAAAAGTGCTTTAAAAAAAATTGAAGAGGAAATACAAACTTTACCCACATCCGAAGTGATT\nTTGCAGATGCAAAAAGATATACAAAATAATACAACTGAAATTGTAGATATCGATGAAAGAATGATTGAAT\nCTGAAGTAGTAATTGAAAATAATAGTAAAAGCATTGAAGTATTACAAATCGATTTAAAAGATGTAGTAGA\nTCGTCTAACTGCTTTAGAAAATGGAGGTTCATAATGTGGCAAATATAAGTGGTTTTTTAAATAGAATTCG\nAACCGCTATTTATGGTAAAGATGTTCGTGAGTCTATACATGATGGGATAGAAGCTATCAATAAAGAGACA\nGAGATAGCGACGAAACTTTCCAATAATATAAAGATTAAACAAGTTGCTTTAGAAAAGAAATATGATGACC\nAAATTTCTAACATGACAAATGAAAATCCATCTATTAGTGAATTGGTTGATTTTAGAACTAGTGGATTTAC\nAGGAATGTCATATGTTACAGCGGGAAAAAGAACTGATGCTATTGATGAAAGGATTACAGATATGTCTGTC\nAGCATAAAAGACTTCGGAGCAGACCTCACAGGAGAGACAGACAGTACGGTAGCTATTCAACAAACAATAG\nACTACGTATATGATCGTGGAGGTGGTGTAGTTTATATTCCGCCAGGGATTTTAAGATACACTTCTATAAT\nTGTTAAAATTGGTGTTCATATTCGTGGTTCATTAGTTTCAATTACAGATTGGAATGGGAGGTTAGGCTCT\nAATACGTCCGTAACTACTTTGATACCAACTGATCTTAATAGACCTTCTATCATCATGCATGGGAACTCAA\nCGATTAATGGCGTCTGTTGGTTTTACGAAGGGCAAAAGAAAGAACTGACGTCTGAAAGTGACACATTTAT\nTCAATACCCTCCAACTATTCAGTTGGGTGATGCGTCAAACAAGGCTATTGGAAATTATATTGGAAACTTT\nATAGTAATTGGAGCATATGACTTCATATCGCAATACTCATTTTCAAATAGCGTAGAAAAGTTATTTGTAG\nAAAAAGGATATGGTATGTTCTTAAATACATTTTGTACGCTTAAAAAATGTACTGATATTCCTAGATTCTC\nTAAGATTCATATGAATCTAAATTCAGCATTAGGATGGCTAACTGGAAATACAGTTCCTTATTACTCTAAA\nATCGCTCGTAATGGTGTAATGTTTAAGGTTGCGCGTGTCGATGACTGTGTGATAGAAGATTGTTTTGCAT\nATGGCGTTAAGCACTTTGCTCATCTCTATAAAGAGGTGGGTGAGGATGGGAACGGCGGTGGTATAACAGT\nAATTGGATCAAGCTGTGATGTTTGCCATCAAGCGTTTAGAAACGATCGTGGAAATCTATCGTTTGGCGTG\nAAAGTAATCGGGGGATTTTTCACACCAGTTGTTAACGTGGATGGCAGCGAAAAATGTTTAATTTACCTTA\nGTCAAAACGCTACATATACTAGAATGCAATTTTCGTCATTCAAATGTTATGGAGATGTTGTATCACAGGT\nAAGTAATACTTCAAAAACAGACCATATTGTTATTTTCGAAAACGGAAATGCGGGTAATAACGTCGTAAAT\nTTATTTGGCGATGTACAGTTTAATATTGGTATTTCGAAAAACGAGAACGTGTTGATCAATAATGTTGTAA\nATTTTATTGGTACAGATAGGGATTCCTCTTTATCAAAACTAGATAGAGTGACTATCCGTCATCTTGTAAT\nGACCGGTTCTCGAATTGATCTAACTCATGGTGTCGATGATATTGCATGGTTTAAAGTGAATAATGAATAC\nGCTTTTGGTGCAGTTAAGGATGCCTATGATCCGACATTTTTTACAAAAGCGTATTTCCGACCAGGTACAC\nTGACTTCATTACCAACCGCAAATGCAAATCATCGTGGAAAGATGATTCGTCTGGAAGGTGCAAATGGTGT\nTGAGGATAGGTTATTTATATGTAAAAAGAAAAGCGATGGAACATATCACTGGAAACAGCTAGACGCAGAA\nCAATAATGATGAAGGGGTGTTTTAAATGGGATTGCAAGTTAATATAACTTTATTTAATCAATTAGAAGTA\nAATTCATATGCAAGAGTCGGCAATATTGGAGGAACAAAAGAGGAACAGTTTTTTTCTATTGATTACTACG\nCTTCGCGAAATGCCTTTTTGAGGAAACTTGACCCTATCAAACAAGAAAACTATAAATTCACTCCATCTGT\nTATGGATGACTCATTGAATTTTGTGAAACAAGCTTATATTTATGTTAAAAGAAGAACGGAATTTGCGGGT\nGCTGTCGATGTATTAGAAGAAGGGCAAAAATCTTGAGTTTAATAAAATTCCTCAGTTTATCTAATATATA\nAGATTTTATATGTTATTATATGTAATGGCGTCTTAATATAAGACGCTAATACATATAATTTGGAGGAAAA\nAGATGAACATATCCAGTCACCAAGAGGGAATGTCAAAACTGAATATAATAATACTACTTTTTCTCTCGTA\nTATAATGAGTACTTATAAATACGGGGAATTTGTACATTATTTTGTGTTTATAGTCATGGCCGCTCTTATA\nCTTAGAATGCTTACTGTAGGCATCAAGGTAAGTAATGAAATATCAATAAATAAAGGCATATTGACGTTTT\nGCGTAATTTTATTAGGGTTATTGTTATTGAAATCGATTTTTAACTTAAATGAATTAAAGGCATTTATTAA\nGAATTATTCAGTTATCTATTTCGTTCTAATTTACGGCCTTCTAGAATATTATAAGAATGGTGCTAGGTAT\nGGAGAGCAAGTTTTTATACAGCTTACTAAAATACTAAATGTACTTTCTGTCTTAAACCTAATTCAGGTTG\nTTTTACACAGACCGTTATTATCTGGATTCTTCACAGAACAGATGGACAAGTATCAATATTGGGCGTATGG\nTACTGGTGACTTTAGACCAGTTTCCGTGTTTGGTCACCCTATTGTAAGTGCATTGTTTTTTTCTATATTA\nGTGATCTGTAATCTTTATATACTTAAAGGCAATTTAAAATATCCATTGCAGATTGTGGCACTTGTGAATG\nTCTATGCCTCGCAATCTAGGAGTGCTTGGATTGCATTAGCAATTATTGTATGCTTGTATTTTATTAAAAA\nTTACCGTATTAAAAAAATAAAAAGAAATGTTCGATTTACTTATAGTCAATTATTAAAAATTTATGTTTCA\nTTAGTAATAGTGATCTGTGGATTTGGCTTAGTTGCTTTAAGCTCGGATAGTATCATAAGTTCCATAATTG\nAAAGATTCGGAGATTCTTTAAGTGGGAATAGTAAAGATATTTCAAACTTACAACGGACGGGCACATTAAG\nTTTAATTAATACTTATATGTTTCAACAAGATATGTTTAGATTACTGTTTGGTTATGGATTAGGGACTGTA\nGGAGATTTTATGTCTGTTAATACCGTTGTTATTCGTAATTTCTTGACGACAGATAATATGTATTTGACTT\nTTTTCTTTGAATTAGGGCTCTTGTCATTGATTAGTTATGGATTATTCTTTATTATTGGAGTCATTCGTTT\nTTTCTTATCTAAAAATTACTGGTTAAGCGAATTAGGCGCTTTATGTTTTATCTTTTTATCAATCATAATA\nTTTTTCTTTGAAGGTATAGGGTGGGGTACTGTAGTAACTGTTTGGATGTTTTCTTTACTGACCATTCTAA\nTGAAATTTAAAAATCCAAACAGTTTAACAAAAAATAAAATAAAATAGTTACAGTAGTATTTATACTAGTT\nTTTGGGAGAGAAACATGAACAAAAAACAATTAAAAGAAACAATTAATTCAGACTTATACAGAGTATACGG\nAAGTCAAGGAACAAAAAAGAAAATTATTAATTTCTTAAGAAACCCTGGCTTTAAATATTTATATATACTA\nCGTAAATGTAGTTATTATAAAGAGAAAAACAAGTTAATGTATAGATTGTATTTTATATTATTGTTGCGTT\nATCAGTATAAGTATGGACTAGAAATAATGCCTGATACGAAGATTGGAAAAGGCTTTTACATTGGACATAT\nAGGAGCTATTACAATTAATCCTAAATCTATAATTGGTGAAAATGTAAATATATTAAAAGGGGCATTACTT\nGGCTATAATCCGCGAGGGAAATATAAAGGCTGTCCAACTATAGGAGATGGTGTTTGGATAGGTCCTAATG\nCTGTAATAGTTGGTAATATTACAGTTGGAAATAATGTAGTGGTAGCGCCAAATACGTTAGTCAATAGGGA\nTGTTCCAAGTAATTCAGTTGTGGTAGGTAATCCGTGTCAAATTATTTCACAGGATAATGCAACTGAAGCT\nTATGTCAATTATACAGTTTAACAAAATACAATTTTAGTTGAAAAGGAGACGAGTTATCGTCTTCTTTTTT\nTATTGTCAAAAGGAGATGAGAACAGTGGAAGATGCAATTTTCAATTCAGTCATTCAACAGGGCGCATTCG\nCAGCGTTATTTGTGTGGATGCTATTTACTACACAAAAAAAGAACGAGCAGCGTGAGGAAAAGTATCAACA\nAGTAATTGATAGAAACCAACAAGTAATTGAAGAACAGGCAAAAGCCTTTGGATCTATTTCTAAGGATGTA\nACAGAAATTAAACAAAAATTATTTGAAGGAGATGTTCAATAATGGGATATATCGTTGATATTTCAAAATG\nGAATGGCAATATTAATTGGGATGTAGCTGCAGCGCAATTAGATTTAGTAATTGCTAGGGTACAAGATGGT\nTCAAATGTTGTGGATCATATGTATCAAAGTTATGTGAGTGAAATGAAAAGGCGTGGTGTTCCTTTTGGTA\nATTATGCGTTTTGTCGTTTCGTTTCTGAAAATGATGCAAGAGTTGAAGCGAGGGACTTCTGGAACCGCGG\nTGATAAAGATGCATTATTCTGGGTTGCTGATGTGGAAGTAAAAACAATGGGGAATATGTTAGCCGGAACA\nTTAGCTTTTATCGATGAGTTACGTCGATTAGGTGCTAAAAAGGTTGGTTTATATGTTGGCCATCATACAT\nATAAAGAGTTCCAAGCTGATAAAGTAAACGCTGATTTTGTATGGATTCCTCGATATGGTGGGAATAGACC\nAGCTTATCCATGTGATATCTGGCAATACACAGAGACAGGAAATGTACCTGGTATCGGTAAATGCGATTTA\nAATGAGTTAATTGGTGATAAATCGTTATCTTGGTTTACCAATAATCACATGGGCTTAGTTGTTCCTGAGG\nTAGGAAAGCGAGTTGTTTCTAAAGTAGAGACTCTTAGATTTTATTCAAAACCTTCCTGGGCGGATGTGGA\nTGTTGCTGGAACAGTTTCTAATGGTTTGGGGTTCGCTATCATTGGAAGAGTCGATGTGAATGGTTCGCCA\nCAATATAAAGTACAAAATTCTCGTGGTAGTGTCTTTTATATTACGGCTAGTCCAAAATATGTAGAAGTAA\nAATAAAAATTGCCGGCTCTTAATTGATATGCTCCCCCTATAGTAGACAGAAAAAAGAAAGCTTTATATCC\nTGTCTACTATAAGGGGGATTTTTTTATGGGGAAAATTAGAAGAACATATGATGAAACATTTAAGAAAAAG\nGCTATAGATTTATATTTTAAAGAAGGCATGGGTTATACCCAAATAGGAAAAACACTAAGCATTGATGAAA\nAAAACGTACGTAGATGGGTAAAACGTTTCAAAGAAGAGGGTATCAAAGGCTTAGAAGAGAAACGTGGAAA\nGGCTACTGGAGGAACAAAGGGGCGACCTAAAAATTGTCCAAAGGAGCCTACAGAAAGAATCAAATATTTA\nGAAACAGAGAATGAAATGCTAAAAAAGCTATTGGGAATGTTAAAGGAGGGATGAAAGCTGCACCAGCATA\nCAAAAAATATGAAATCATACAAGAAATGTCCAAAGGTATGCGTTCAATACAGCTACTGTGTAAAATCGCG\nGAAGTATCTAGAAGCGGATATTACAAGTGGTTAAAAAGGCAAAGCAATCCTTCTCCGAAGGAGATAGAAG\nATGAAAAAATAAAGAATAAAATTTTGGAATGTTATAACCAAGTGAAGGGTATCTACGGATACCGAAGAAT\nAACTGTGTGGTTAAAGATGAAACATGGGATCGTCGTAAACCACAAGAGAGTTCAACGACTAATGAATAGG\nATGAAACTTAAAGCAATTATCAGAAAAAAACGACCTTATTTTGTATCAAAAGAAGCATATGTAGTCTCAA\nAGAATTACTTGAATCGAGATTTTAAAGCGGAACAACCAAATGAAAAATGGGTAACAGATATTACTTACCT\nTATTTTTAATGGGAAAAAGCTATATCTATCCGCCATAAAGGACCTTTATAACAATGAAATTGTAGCTTAT\nCATATTAGCCATCGTCATGATATACAACTAGTTATCGATACGCTAAACAAGGCGAAAAAACAACGAAACG\nTGCAAGGGATTCTTTTGCATAGTGATCAAGGTTTCCAATACACTTCACGCCAATATAATGATTTCCTAAA\nAAAACATAAGATGAAAGCTAGTATGTCTAGAAAGGCGAATTGTTGGGACAATGCTTGTATGGAGAATTTC\nTTTAGTCATTTCAAAGCGGAGTGTTTTAATCTGAGTTCATTTCGTTCAGTAGAAGAAGTTAAATTTGCCG\nTACATAAGTATATTCATTTTTATAACCACCATCGTTTTCAGAAAAAATTAAAGAACCTGAGTCCATACGA\nATATCGAACTCAGGCTTCTTAACTATGCGTTTTAATTACTGTCTACTTGACAGGGGTCAGTACATAATTG\nAGTCGGCTTTTTTATTGCAAATCAGATATCCTTCTAACTTGTTTTTCTTTCTTCTTGAAGTTCTTCTTGT\nACTGTTTAAATTCTTCTTTATCTACGTGGAACTTTTCTCCGGTGGCAACGTTTTTAACTAAGTATGTTTT\nGGTTGTAAGAGATTTAATTATGTAATAAATAGCAAATAGCATAAGAGAAATACAAAAGGTAGGAATAGAA\nAATACAATAGCAAGTGCAGCTAGTATATTATCTCTCTTATGATCTCTTTGTAACACTAAACGTTTCCCTG\nCTGCAGCTTGAGCTTGTTCTAATTGTTGCATACGTTGTAGCGATGCTACAGTATCATAACTCATGAAAAA\nACCTCCTTGAAATAATACCTAAATCATACCAATTTCATGTAACAACTGTAAATGTTAGTTTCTCATTTAT\nTGACAAAACAGAACAATTGTTCTACAATTCATTTACAAACAAATGTTCTTGAAAGGGGAAATTCATATGG\nCAGCAACTGAAAATACAACTAAAGGAAAAGAGAAAGCATTAGAAGAGGCTCTGAAGAAAATCGTAAAAGA\nATTTGGTACAGGGGCTATTATGAAACTGGGTGAGCGTCCTAATCAAAAAGTATCTGTCGTATCAAGTGGT\nTCTGTTGGATTAGATAATGCTTTAGGGGTTGGTGGATATCCAAAAGGACGCATTACTGAAATCTTTGGTC\nCTGAATCTTCAGGTAAGACAACTATAGCATTACATGCAATTGCAGAAGCGCAAAAAGAAGGTGGAACAGC\nGGCATTTATTGATGCAGAGCATGCACTTGACCCTATTTATGCACAGAAGTTAGGTGTTAATATTGATGAA\nCTGCTCATGTCACAACCAGATACAGGAGAGCAAGCACTAGAGATTGCAGAAGCTCTAGTTAGAAGTGGGG\nCTGTAGATATCATTGTGATAGATTCTGTAGCTGCTCTAGTCCCGAAAGCGGAAATTGATGGGGACATGGG\nAGATTCACATGTGGGATTGCAGGCTAGATTGATGGGGCAGGCAATGAGAAAAATATCAGGAGCAATATCC\nAAAAATGGAGTTGTAGCAATCTTTTTAAATCAAATCAGAGAAAAAGTTGGTGTTTCTTTTGGGAGTCCTG\nAGACAACACCGGGTGGTAGGGCGTTAAAATTCTATTCAACAATTCGACTAGATGTACGTCGAGGAGAACA\nGTTGAAAGGAAAAGAAAGTGACGTTTTAGGGAATAAAACAAAAGTGAAAGTAGTAAAAAATAAAGTTGCT\nCCACCATTTAAAAACATTGACTTTGACATCTTATACGGAGAAGGGATTTCCCTAGAGGGAGAGCTTATTG\nATATTGGGGTAGAGTTAGATATTGTTCAGAAAAGTGGTGCATGGTACTCGTATCAAGAAGAACGTCTTGG\nGCAGGGTAGAGATAATGCCAAGCAATTTCTGAAAGAGAATGAAAACATACGTAATTCTGTTCGAAATAAA\nATTTATGAATACTATTCTCCAAAAGAAGACTCTGTTGTTGTAAAAGCGGAGCTTATAAAAGAAAATGAGC\nCCATCACTTTAAAAGAATCTGAATAAGGTTATATAAAGAGAATCTTAAAATAAAATTCATGCTATGTATA\nTTTTAAAAACTGGAACACCTAGTTATTAGAACTGGGTGTTTTTATATACTCATAAACTCACGATCAAAAT\nAAAGCTTATCCATTAAGTTTTTTGTATATTATTTTGCAAGTAAGTTCCGTACATATTTACCCAACTGTTC\nATCTGTTAAACCTGACTTAATTGCACCTTTAATAGCATCAATTGTATTAATTGTATGAGGTTCATTCTCT\nTCTTTCTTTTTACTATGTATCCATTTCTTATATAGTTCATCCTCTTTCTTTGCCAAACTCAAAGCGTTCT\nCAACAGTAGTAACTTTCTTCCTCACCCAATGACCAGCTATTTTTTTGACATACTCAGGATTCAATATCAT\nGTCTGATCTCAGCATCACATAATAAATCAAAACATTTATAACAGGGTTAGGCAACCTATAATTATCACGC\nATATCAGTAACTATATGCAAATCCCCTTTTGGAACAGTAGCACCGCCTGATAACTCGCTTAAAAGTTGTT\nCAGGTGTAACAGAATTTAATTGCTGTATCAATTTTTGTTGTTTTTCCATGAATTTATCCTCCTAATACTT\nTGTATAATATAAATTTTATCTAGTAATCTTCCGCATTTAATATAACCCCATTTCATCAGATTCTTCTTTA\nGATAGTTTGTAATATATACTTGGTGCAAGAGGGTTATCTATTGTATTTGTGGAGGGGGTTTTTGAGTCAT\nTATCTTCTAACCAATTATAATATACACTACTAGTATCTGTGTTAGTTTTACGTTTAGAAATATTGTGGAT\nGTCTCTAAATCTATCGATGTAGTCATATACCATACTTTTAAATGTATTAGTAAAGTATCCAATTGGATTT\nTTCATAAGCTCTCCATTGTGTTCAACTTCATGAGTTTTAGAGAATAAAGTAACAGATGCATTCGCAAGGA\nTATTGTTAAATACATCCTTGTCAGATAGTAAACTAAACTTCTTAGCAGCCTTTTTAGCGATATTTACAGC\nATTGTGGAAGGATTCGTTAATAACTTTTGAACCAAATGCAGTTGCTAATTTCATACGCATAGATTGTGGA\nACACGATAGTCGATAAAATCATTATCATTGACTGTAGATTGAAACTCATTTCTATTACGTATATTTATAT\nTTTTTATATTTTGTTTTAAGGTTTTAGTAGTTGTTTTATTGGTGTGACATTTTTCTTCATTTTTAATAGG\nTGCTTGTGTGACAACCTGTTCCTCCACAATAATTGGTTGAATAACAATCGCATTGCATGTTTGCCTCATA\nTCGCTTTTACGCTTCATTTCTAGTTGTTTAATAATACCTAAAGACTCTAAGTGTAGGCATACTCTAATAA\nCCGTTCTACGGCTAATATTGAGGTCTTCAGCGATGTGTTTTTTTGTTCTGAATGATACACCAAAGAACTT\nAGAAGAATAGTTGTGTAATTTATTTAATACAGCCAATTGAGTTTTATTTAACTGATCTACGAATTTTTCT\nTTGTATGCACGAACAGTCTTGTTTAATTCATCGACTGTTTTAAATGTTGCTAGGTTTTCATATGTTTCAT\nTACCTGCAATAATTGTAATTCCTTGTTTCTTTTCCATAACGGTTTGTCTCCTTTTTGGAAACAAAAAAGC\nAACAGAATGCCAAGTGTAAGCAAACTGTTGCTAAGGAGCCCTTACGTACTGTAAAATAGTTCGTAAGAGT\nACAGCAAGTGTTTGCCTAGTGTGATTAGGCGGACGGTATATAGAGTGTTGACGCACTTTATATACACGCT\n\n"

class(her1410_1)

[1] "character"

dim(her1410_1)

NULL

length(her1410_1)

[1] 1

write(her1410_1,file="her1410_1.fasta")
seq1 <- read.fasta("her1410_1.fasta")

As you can see, you can very easily download the data from any NCBI database. Regarding sequences, the main drawback of the function entrez_fetch() is that the downloaded sequences are character objects and transform it into sequences that you can handle with seqinr or other packages is not always straightforward and it requires some polishing (see ref. 7). Alternatively, you can save the data as a new fasta file in your computer before importing with seqinr, as in the following example.

# compare two files
her1410_2 <- entrez_fetch(db="nuccore", id=her1410$ids[2], rettype="fasta")
write(her1410_2,file="her1410_2.fasta")
seq2 <- read.fasta("her1410_2.fasta")

#codon frequencies
freq1 <- count(unlist(seq1),3, freq=TRUE)
freq2 <- count(unlist(seq2),3, freq=TRUE)

stop1 <- freq1[which(names(freq1)=="tga"| names(freq1)== "tag" | names(freq1)== "taa")]
stop2 <- freq2[which(names(freq2)=="tga"| names(freq2)== "tag" | names(freq2)== "taa")]
stops <- rbind(stop1,stop2)
stops <-  as.data.frame(stops)
stops$sequences <- c(her1410$ids[1],her1410$ids[2])
stops <- cbind(stops$sequences,stack(stops[,1:3]))
names(stops) <- c("sequences","freqs","stop_codon")
#plot
library(ggplot2)
p <- ggplot(data=stops) + geom_bar(aes(x=toupper(stop_codon),y=freqs,col=sequences,fill=sequences),stat="identity",position="dodge",alpha=0.8) 
p + scale_fill_brewer(palette = "Dark2") + scale_color_brewer(palette = "Dark2") + theme_linedraw() + ylab("Codon frequency") + xlab("Stop codon") +  guides(color="none", fill=guide_legend(title="HER1410 sequences"))

1.6 Plotting sequences

1.7 Example 1: Sequence logos with `ggseqlogo`

R is very useful for many applications in Biochemistry and Molecular Biology, and ggplot2 is a very good example of that. Sequence logos are a compact way to visualise how frequent each nucleotide or amino acid is at each position of an alignment or motif.

#script by Luis del Peso
Counts<-matrix(c(2,38,0,0,0,0,10,8,4,7,21,9,9,11,9,23,4,15,10,0,46,0,0,0,32,17,
                 10,15,11,18,9,16,23,11,20,8,10,8,0,46,0,46,2,17,21,13,14,15,
                 27,8,13,8,16,22,24,0,0,0,46,0,2,4,11,11,0,4,1,11,1,4,6,1),
               nrow=4,byrow = T,
               dimnames=list(Nucleotide=c("A","C","G","T"),Pos=1:18))
counts <- data.frame(Counts)
names(counts) <- 1:18
counts <- cbind(stack(counts),c("A","C","G","T"))
colnames(counts) <- c("values","pos","nucleotide")
ggplot(counts, aes(x=pos, y=values, fill=nucleotide)) + 
    geom_bar(position="stack", stat="identity")

This is not a very interesting plot. Now, in order to plot the PSSM as a sequence logo, we are going to use the package ggseqlogo. Also, to arrange plot, we will use the package gridExtra, which is very handy and commonly used to generate complex figures.

if(!require(ggseqlogo)) install.packages("ggseqlogo", repos = "https://cran.rstudio.com/", dependencies = TRUE)

Cargando paquete requerido: ggseqlogo

Warning: package 'ggseqlogo' was built under R version 4.6.1

library(ggseqlogo)

ggseqlogo(Counts)

Warning: The `<scale>` argument of `guides()` cannot be `FALSE`. Use "none" instead as
of ggplot2 3.3.4.
ℹ The deprecated feature was likely used in the ggseqlogo package.
  Please report the issue at <https://github.com/omarwagih/ggseqlogo/issues>.

Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
ℹ Please use tidy evaluation idioms with `aes()`.
ℹ See also `vignette("ggplot2-in-packages")` for more information.
ℹ The deprecated feature was likely used in the ggseqlogo package.
  Please report the issue at <https://github.com/omarwagih/ggseqlogo/issues>.

#install.packages("gridExtra")
p1 <- ggseqlogo(Counts, method="prob")
p2 <- ggseqlogo(Counts, method="bits")
gridExtra::grid.arrange(p1, p2)

Let’s plot some protein logo from the example sequences in the package. Remember that we are working with an add-ons to ggplot. That means that all ggplot elements can be used.

data(ggseqlogo_sample)
str(seqs_aa)

List of 4
 $ AKT1   : chr [1:172] "VVGARRSSWRVVSSI" "GPRSRSRSRDRRRKE" "LLCLRRSSLKAYGNG" "TERPRPNTFIIRCLQ" ...
 $ CDK2   : chr [1:444] "LGPYEAVTPLTKAAD" "SGSESGYTTPKKRKA" "GSESGYTTPKKRKAR" "VTTQTPLTPEQLRAV" ...
 $ AURKB  : chr [1:106] "ITVTRRVTAYTVDVT" "PWPYGRQTAPSGLST" "APSLRRKTMCGTLDY" "PSKKRTQSIQGKGKG" ...
 $ CSNK2A2: chr [1:80] "KHEEEEWTDDDLVES" "VWDHIEVSDDEDETH" "TSADVKMSSSEEVSW" "SADVKMSSSEEVSWI" ...

head(seqs_aa)

$AKT1
  [1] "VVGARRSSWRVVSSI" "GPRSRSRSRDRRRKE" "LLCLRRSSLKAYGNG" "TERPRPNTFIIRCLQ"
  [5] "LSRERVFSEDRARFY" "PSTSRRFSPPSSSLQ" "GRSGRGKSFTLTITV" "SGRGKSFTLTITVFT"
  [9] "SGRAREASGAPTSSK" "CVRMRHLSQEFGWLQ" "GTRGRLESAQATFQA" "ARRARSKSLVMGEQS"
 [13] "QFRRRAHTFSHPPSS" "ATRGRGSSVGGGSRR" "ATRKRRWSAPESRKL" "PFRGRSRSAPPNLWA"
 [17] "FIFMRRSSLLSRSSS" "GQRDRSSSAPNVHIN" "PQRERKSSSSSEDRN" "LKRKRRPTSGLHPED"
 [21] "QTSKRHDSDTFPELK" "RFRDRSFSEGGERLL" "TRRTRTFSATVRASQ" "KLRRRFSSLHFMVEV"
 [25] "GSRVRVDSTAKVAEI" "SRRPRRRTFPGVASR" "LKKIRLDTETEGVPS" "GQVPRTWSEKDLREL"
 [29] "SIRPRPGSLRSKPEP" "THLSRVRSLDLDDWP" "LLRDTFTSLGYEVQK" "AKRPRVTSGGVSESP"
 [33] "HKRRRSRSWSSSSDR" "RRRRRSRTFSRSSSQ" "DHWIRMRSQEGRPVQ" "EDQPRCQSLDSALLE"
 [37] "QDTQRRTSMGGTQQQ" "LGGGRVKTWKRRWFI" "RTPRRSKSDGEAKPE" "SFRRRHNSWSSSSRH"
 [41] "RTRSRRLTFRKNISK" "SYKIRFNSISCSDPL" "TSRIRTQSFSLQERQ" "RVSIRLPSTSGSEGV"
 [45] "GGRERLASTNDKGSM" "IKRSKKNSLALSLTA" "CWRKRVKSEYMRLRQ" "ASPARRASAILPGVL"
 [49] "CLRSRDPSLMVDFIL" "GLETRRLSLPSSKAK" "LGRERLGSFGSITRQ" "KTYRRSYTHAKPPYS"
 [53] "KLRRRSTTSRAKLAF" "LPRPRSCTWPLPRPE" "SPRRRAASMDNNSKF" "TFRPRTSSNASTISG"
 [57] "QSRPRSCTWPLQRPE" "APRRRAVSMDNSNKY" "QSRPRSCTWPLPRPE" "APRRRAASMDSSSKL"
 [61] "TFRPRSSSNASSVST" "LLRERKSSAPSHSSQ" "QTRNRKASGKGKKKR" "QTRNRKMSNKSKKSK"
 [65] "INRERQKSLTLTPTR" "ANLNRSTSVPENPKS" "SGRARTSSFAEPGGG" "SGRPRTTSFAESCKP"
 [69] "RKRSRKESYSIYVYK" "LYRSRMNSLEMTPAV" "SQRGRSGSGNFGGGR" "RALSRQLSSGVSEIR"
 [73] "RVRVRLLSGDTYEAV" "GGRSRSGSIVELIAG" "EMRERLGTGGFGNVC" "VPSGRKGSGDYMPMS"
--- Cropped output ---

ggseqlogo(seqs_aa, ncol=4)

ggseqlogo(seqs_aa, ncol=2) +   theme_light()

1.8 More examples

There are two other ggplot-based packages that I find very interesting for sequence-based plots:

1. `ggmsa` allows visualization and annotation of multiple sequence alignments.

Check out vignette and examples here: http://yulab-smu.top/ggmsa/

2. `drawproteins` is very useful to represent and compare protein domains and catalytic residues.

See the vignette and some example here: https://rforbiochemists.blogspot.com/

2 Bioconductor

Bioconductor is a repository of R packages for “the analysis and comprehension of high-throughput genomic data”. It started 2002 as a platform for understanding analysis of microarray data, being the first R version 1996, and the first stable beta in 2000. For example, release 3.16 included 2183 packages on November 2, 2022, covering diverse bioinformatics tasks. It also contains many learning resources, spanning vignettes, course materials, and workflows.

The diversity of packages in Bioconductor allows working with widely used bioinformatics apps and file formats (fasta, fastq, BAM, SAM, vcf…), for different stages of sequence analysis, quantification, annotation… You can explore packages by categories on the Bioconductor site.

Illustrative description elaborating the different file types at various stages in a typical analysis, with the package names (in pink boxes) that one will use for each stage. From: https://www.bioconductor.org/packages/release/workflows/vignettes/sequencing/inst/doc/sequencing.html

Some of the most common Bioconductor packages and functions are:

GenomicRanges: ‘Ranges’ to describe data and annotation; GRanges(), GRangesList()
Biostrings: DNA and other sequences, DNAStringSet()
GenomicAlignments: Aligned reads; GAlignments() and friends
GenomicFeatures, AnnotationDbi: annotation resources, TxDb, and org packages.
SummarizedExperiment: coordinating experimental data
rtracklayer: import Genome annotations e.g BED, WIG, GTF, etc.
Annotationhub: access to Ensembl, UCSC, NCBI and other databases.

I recommend you to check the examples in the reference 9 below and other workflows that you can find at Bioconductor.

4 Exercises

Write a function that, given an input name:

1-. It downloads a sequence from the nucleotide database in Genbank. The function needs to check if the different available sequences for that name are identical and rule out duplicates.

2-. It plots the nucleotide composition (% of A, C, G and T) and the amino acids frequencies in the 6 possible frames.

3-. It should also download the protein sequences with that name and count the number of enzymes (you can use ase as keyword) and the number orfans (hypothetical protein).

Test your function with the nucleotide sequences of the plasmids pSE-12228-03 and pCERC7.

5 Session Info

sessionInfo()

R version 4.6.0 (2026-04-24 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26200)

Matrix products: default
  LAPACK version 3.12.1

locale:
[1] LC_COLLATE=Spanish_Spain.utf8  LC_CTYPE=Spanish_Spain.utf8   
[3] LC_MONETARY=Spanish_Spain.utf8 LC_NUMERIC=C                  
[5] LC_TIME=Spanish_Spain.utf8    

time zone: Europe/Madrid
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggseqlogo_0.2.2    ggplot2_4.0.3      rentrez_1.2.4      RColorBrewer_1.1-3
[5] seqinr_4.2-44      webexercises_1.1.0 formatR_1.14       knitr_1.51        

loaded via a namespace (and not attached):
 [1] ade4_1.7-24       gtable_0.3.6      jsonlite_2.0.0    dplyr_1.2.1      
 [5] compiler_4.6.0    tidyselect_1.2.1  Rcpp_1.1.1-1.1    gridExtra_2.3    
 [9] scales_1.4.0      yaml_2.3.12       fastmap_1.2.0     R6_2.6.1         
[13] labeling_0.4.3    generics_0.1.4    curl_7.1.0        htmlwidgets_1.6.4
[17] MASS_7.3-65       XML_3.99-0.23     tibble_3.3.1      pillar_1.11.1    
[21] rlang_1.2.0       xfun_0.57         S7_0.2.2          otel_0.2.0       
[25] cli_3.6.6         withr_3.0.2       magrittr_2.0.5    digest_0.6.39    
[29] grid_4.6.0        rstudioapi_0.19.0 lifecycle_1.0.5   vctrs_0.7.3      
[33] evaluate_1.0.5    glue_1.8.1        farver_2.1.2      rmarkdown_2.31   
[37] httr_1.4.8        pkgconfig_2.0.3   tools_4.6.0       htmltools_0.5.9

References

3 References

R in action. Robert I. Kabacoff. March 2022 ISBN 9781617296055
Regular expressions in R: https://rstudio-pubs-static.s3.amazonaws.com/74603_76cd14d5983f47408fdf0b323550b846.html
R Programming for Data Science (Chapter 17): https://bookdown.org/rdpeng/rprogdatascience/
A little book of R for bioinformatics: https://a-little-book-of-r-for-bioinformatics.readthedocs.io/en/latest/index.html
rentrez vignette: https://cran.r-project.org/web/packages/rentrez/vignettes/rentrez_tutorial.html
Biostrings: https://kasperdanielhansen.github.io/genbioconductor/html/Biostrings.html
Example of the generation of multiple sequence alignments and phylogenies with R: https://rpubs.com/bhuvic/828540
Where do I start using Bioconductor: http://lcolladotor.github.io/2014/10/16/startbioc/#.Y4ZCaOyZP0p
Bioconductor Workflow: Introduction to Bioconductor for Sequence Data: https://www.bioconductor.org/packages/release/workflows/vignettes/sequencing/inst/doc/sequencing.html

Workflow for sequence projects

A useful sequence-analysis workflow is:

Identify the input format: FASTA, GenBank, alignment, table or database result.
Start with simple text inspection when needed.
Convert the data into a sequence-aware object for biological operations.
Keep track of names, annotations and sequences separately.
Save intermediate or final sequences in reproducible files.
Plot results only after checking what the sequence object represents.