SeqinR - biological data handling

Pau Corral Montañés

RUGBCN
03/05/2012

VIDEO:
“what we used to do in Bioinformatics“

note: due to memory space limitations, the video has not been embedded into
this presentation.

Content of the video:
A search in NCBI (www.ncbi.nlm.nih.gov) for the entry NC_001477 is done
interactively, leading to a single entry in the database related to Dengue Virus,
complete genome. Thanks to the facilities that the site provides, a FASTA file for
this complete genome is downloaded and thereafter opened with a text editor.

The purpose of the video is to show how tedious is accessing the site and
downleading an entry, with no less than 5 mouse clicks.

Unified records with in-house coding:
The 3 databases share all sequences, but they use different A "mirror" of the content of other databases
accession numbers (IDs) to refer to each entry.
They update every night.

ACNUC
A series of commands and their arguments were
NCBI – ex.: #000134 defined that allow
EMBL – ex.: #000012
(1) database opening,
(2) query execution,
(3) annotation and sequence display,
(4) annotation, species and keywords browsing, and
(5) sequence extraction

DDBJ – ex.:
#002221

Other Databases
– NCBI - National Centre for Biotechnology Information - (www.ncbi.nlm.nih.gov)
– EMBL - European Molecular Biology Laboratory - (www.ebi.ac.uk/embl)
– DDBJ - DNA Data Bank of Japan - (www.ddbj.nig.ac.jp)
– ACNUC - http://pbil.univ-lyon1.fr/databases/acnuc/acnuc.html

ACNUC retrieval programs:

i) SeqinR - (http://pbil.univ-lyon1.fr/software/seqinr/)

ii) C language API - (http://pbil.univ-lyon1.fr/databases/acnuc/raa_acnuc.html)

iii) Python language API - (http://pbil.univ-lyon1.fr/cgi-bin/raapythonhelp.csh)

a.I) Query_win – GUI client for remote ACNUC retrieval operations
(http://pbil.univ-lyon1.fr/software/query_win.html)
a.II) raa_query – same functionality as Query_win in command line interface
(http://pbil.univ-lyon1.fr/software/query.html)

Why use seqinR:
the Wheel - available packages
Hotline - discussion forum
Automation - same source code for different purposes
Reproducibility - tutorials in vignette format
Fine tuning - function arguments

Usage of the R environment!!

#Install the package seqinr_3.0-6 (Apirl 2012)

>install.packages(“seqinr“)
package ‘seqinr’ was built under R version 2.14.2

A vingette:
http://seqinr.r-forge.r-project.org/seqinr_2_0-7.pdf

#Choose a mirror
>chooseCRANmirror(mirror_name)
>install.packages("seqinr")

>library(seqinr)

#The command lseqinr() lists all what is defined in the package:
>lseqinr()[1:9]

[1] "a" "aaa"
[3] "AAstat" "acnucclose"
[5] "acnucopen" "al2bp"
[7] "alllistranks" "alr"
[9] "amb"

>length(lseqinr())
[1] 209

How many different ways are there to work with biological sequences using SeqinR?

1)Sequences you have locally:

i) read.fasta() and s2c() and c2s() and GC() and count() and translate()
ii) write.fasta()
iii) read.alignment() and consensus()

2) Sequences you download from a Database:

i) browse Databases
ii) query() and getSequence()

FASTA files example:
Example with DNA data: (4 different characters, normally)

The FASTA format is very
simple and widely used for
simple import of biological
sequences.
It begins with a single-line
description starting with a
character '>', followed by
lines of sequence data of
maximum 80 character each.
Lines starting with a semi-
colon character ';' are
comment lines.

Example with Protein data: (20 different characters, normally)
Check Wikipedia for:
i)Sequence representation
ii)Sequence identifiers
iii)File extensions

Read a file with read.fasta()

#Read the sequence from a local directory
> setwd("H:/Documents and Settings/Pau/Mis documentos/R_test")
> dir()
[1] "dengue_whole_sequence.fasta"

#Use the read.fasta (see next slide) function to load the sequence
> read.fasta(file="dengue_whole_sequence.fasta", seqtype="DNA")
$`gi|9626685|ref|NC_001477.1|`
[1] "a" "g" "t" "t" "g" "t" "t" "a" "g" "t" "c" "t" "a" "c" "g" "t" "g" "g"
[19] "a" "c" "c" "g" "a" "c" "a" "a" "g" "a" "a" "c" "a" "g" "t" "t" "t" "c"
[37] "g" "a" "a" "t" "c" "g" "g" "a" "a" "g" "c" "t" "t" "g" "c" "t" "t" "a"
[55] "a" "c" "g" "t" "a" "g" "t" "t" "c" "t" "a" "a" "c" "a" "g" "t" "t" "t"
[............................................................]
[10711] "t" "g" "g" "t" "g" "c" "t" "g" "t" "t" "g" "a" "a" "t" "c" "a" "a" "c"
[10729] "a" "g" "g" "t" "t" "c" "t"
attr(,"name")
[1] "gi|9626685|ref|NC_001477.1|"
attr(,"Annot")
[1] ">gi|9626685|ref|NC_001477.1| Dengue virus 1, complete genome"
attr(,"class")
[1] "SeqFastadna"

> read.fasta(file="dengue_whole_sequence.fasta", seqtype="DNA", as.string=T, set.attributes=F)
$`gi|9626685|ref|NC_001477.1|`
[1] "agttgttagtctacgtggaccgacaagaacagtttcgaatcggaagcttgcttaacgtag...__truncated__......"

> seq <- read.fasta(file="dengue_whole_sequence.fasta", seqtype="DNA", as.string=T, set.attributes=F)
> str(seq)
List of 1
$ gi|9626685|ref|NC_001477.1|: chr
"agttgttagtctacgtggaccgacaagaacagtttcgaatcggaagcttgcttaacgtag...__truncated__......"

Usage:
rea d.fa s ta (file, seqtype = c("DNA", "AA"), as.string = FALSE, forceDNAtolower =
TRUE, set.attributes = TRUE, legacy.mode = TRUE, seqonly = FALSE, strip.desc
= FALSE, bfa = FALSE, sizeof.longlong = .Machine$sizeof.longlong,
endian = .Platform$endian, apply.mask = TRUE)

Arguments:
file - path (relative [getwd] is used if absoulte is not given) to FASTA file
seqtype - the nature of the sequence: DNA or AA
as.string - if TRUE sequences are returned as a string instead of a vector characters
forceDNAtolower - lower- or upper-case
set.attributes - whether sequence attributes should be set
legacy.mode - if TRUE lines starting with a semicolon ’;’ are ignored
seqonly - if TRUE, only sequences as returned (execution time is divided approximately by a factor 3)
strip.desc - if TRUE, removes the '>' at the beginning
bfa - if TRUE the fasta file is in MAQ binary format sizeof.longlong
endian - relative to MAQ files
apply.mask - relative to MAQ files

Value:
a list of vector of chars

Basic manipulations:
#Turn seqeunce into characters and count how many are there
> length(s2c(seq[[1]]))
[1] 10735

#Count how many different accurrences are there
> table(s2c(seq[[1]]))
a c g t
3426 2240 2770 2299

#Count the fraction of G and C bases in the sequence
> GC(s2c(seq[[1]]))
[1] 0.4666977

#Count all possible words in a sequence with a sliding window of size = wordsize
> seq_2 <- "actg"
> count(s2c(seq_2), wordsize=2)
aa ac ag at ca cc cg ct ga gc gg gt ta tc tg tt
0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0

> count(s2c(seq_2), wordsize=2, by=2)
aa ac ag at ca cc cg ct ga gc gg gt ta tc tg tt
0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0

#Translate into aminoacids the genetic sequence.
> c2s(translate(s2c(seq[[1]]), frame=0, sens='F', numcode=1))
[1] "SC*STWTDKNSFESEACLT*F*QFFIREQISDEQPTEKDGSTVFQYAETREKPRVNCFTVGEEILK...-Truncated-...
RIAFRPRTHEIGDGFYSIPKISSHTSNSRNFG*MGLIQEEWSDQGDPSQDTTQQRGPTPGEAVPWW*GLEVRGDPPHNNKQHIDAGRD
QRSCCLYSIIPGTERQKMEWCC*INRF"
#Note:
# 1)frame=0 means that first nuc. is taken as the first position in the codon
# 2)sense='F' means that the sequence is tranlated in the forward sense
# 3)numcode=1 means standard genetic code is used (in SeqinR, up to 23 variations)

Write a FASTA file (and how to save time)
> dir()
[1] "dengue_whole_sequence.fasta" "ER.fasta"
> system.time(seq <- read.fasta(file="ER.fasta", seqtype="DNA", as.string=T, set.attributes=F))
user system elapsed
3.28 0.00 3.33

> length(seq)
[1] 9984
> seq[[1]]
[1] "gtggtatcaacgcagagtacgcggggacgtttatatggacgctcctacaaggaaaccctagcctt..._truncated_...ctcata"
> names(seq)[1:5]
[1] "ER0101A01F" "ER0101A03F" "ER0101A05F" "ER0101A07F" "ER0101A09F"

#Clean the sequences keeping only the ones > 25 nucleotides
> char_seq = rapply(seq, s2c, how="list") # create a list turning strings to characters
> len_seq = rapply(char_seq, length, how="list") # count how many characters are in each list
> bigger_25_list = c()
> for (val in 1:length(len_seq)){
+ if (len_seq[[val]] >= 25){
+ bigger_25_list = c(bigger_25_list, val)
+ }
+ }
> seq_25 = seq[bigger_25_list] #indexing to get the desired list
> length(seq_25)
[1] 8928
> seq_25[1]
$ER0101A01F
[1] "gtggtatcaacgcagagtacgcggggacgtttatatggacgctcctacaaggaaaccctagccttctcatacct...truncated..."
#Write a FASTA file (see next slide)
> write.fasta(seq_25, names = names(seq_25), file.out="clean_seq.fasta", open="w")
> dir()
[1] "clean_seq.fasta" "dengue_whole_sequence.fasta" "ER.fasta"

Usage:
w rite.fa s ta (sequences, names, file.out, open = "w", nbchar = 80)

Arguments:
sequences - A DNA or protein sequence (in the form of a vector of single characters) or a list of such sequences.
names - The name(s) of the sequences.
file.out - The name of the output file.
open - Open the output file, use "w" to write into a new file, use "a" to append at the end of an already existing file.
nbchar - The number of characters per line (default: 60)

Value:
none in the R space. A FASTA formatted file is created

Write a FASTA file (and how to save time)
# Remember what we did before
> system.time(seq <- read.fasta(file="ER.fasta", seqtype="DNA", as.string=T, set.attributes=F))
user system elapsed
3.28 0.00 3.33

# After cleanig seq, we produced a file "clean_seq.fasta" that we read now
> system.time(seq_1 <- read.fasta(file="clean_seq.fasta", seqtype="DNA", as.string=T, set.attributes=F))
user system elapsed
1.30 0.01 1.31

#Time can be saved with the save function:
> save(seq_25, file = "ER_CLEAN_seqs.RData")

> system.time(load("ER_CLEAN_seqs.RData"))
user system elapsed
0.11 0.02 0.12

Read an alignment (or create an alignment object to be aligned):
#Create an alignment object through reading a FASTA file with two sequences (see next slide)
> fasta <- read.alignment(file = system.file("sequences/Anouk.fasta", package = "seqinr"), format ="fasta")
> fasta
$nb
[1] 2
$nam
[1] "LmjF01.0030" "LinJ01.0030"
$seq
$seq[[1]]
[1] "atgatgtcggccgagccgccgtcgtcgcagccgtacatcagcgacgtgctgcggcggtaccagc...truncated..."
$seq[[2]]
[1] "atgatgtcggccgagccgccgtcgtcgcagccgtacatcagcgacgtgctgcggcggtaccagc...truncated..."
$com
[1] NA
attr(,"class")
[1] "alignment"

# The consensus() function aligns the two sequences, producing a consensus sequences. IUPAC symbology is used.
> fixed_align = consensus(fasta, method="IUPAC")

> table(fixed_align)
fixed_align
a c g k m r s t w y
411 636 595 3 5 20 13 293 2 20

Usage:
rea d.a lig nm ent(file, format, forceToLower = TRUE)

Arguments:
file - The name of the file which the aligned sequences are to be read from. If it does not contain an absolute or relative
path, the file name is relative to the current working directory, getwd.
format - A character string specifying the format of the file: mas e, clus tal, phylip, fas ta or ms f
forceToLower - A logical defaulting to TRUE stating whether the returned characters in the sequence should be in
lower case

Value:
An object is created of class alignment which is a list with the following components:
nb ->the number of aligned sequences
nam ->a vector of strings containing the names of the aligned sequences
seq ->a vector of strings containing the aligned sequences
com ->a vector of strings containing the commentaries for each sequence or NA if there are no comments

Access a remote server:
> choosebank()
[1] "genbank" "embl" "emblwgs" "swissprot" "ensembl" "hogenom"
[7] "hogenomdna" "hovergendna" "hovergen" "hogenom5" "hogenom5dna" "hogenom4"
[13] "hogenom4dna" "homolens" "homolensdna" "hobacnucl" "hobacprot" "phever2"
[19] "phever2dna" "refseq" "greviews" "bacterial" "protozoan" "ensbacteria"
[25] "ensprotists" "ensfungi" "ensmetazoa" "ensplants" "mito" "polymorphix"
[31] "emglib" "taxobacgen" "refseqViruses"

#Access a bank and see complementary information:
> choosebank(bank="genbank", infobank=T)
> ls()
[1] "banknameSocket"
> str(banknameSocket)
List of 9
$ socket :Classes 'sockconn', 'connection' atomic [1:1] 3
.. ..- attr(*, "conn_id")=<externalptr>
$ bankname: chr "genbank"
$ banktype: chr "GENBANK"
$ totseqs : num 1.65e+08
$ totspecs: num 968157
$ totkeys : num 3.1e+07
$ release : chr " GenBank Rel. 189 (15 April 2012) Last Updated: May 1, 2012"
$ status :Class 'AsIs' chr "on"
$ details : chr [1:4] " **** ACNUC Data Base Content **** " "
GenBank Rel. 189 (15 April 2012) Last Updated: May 1, 2012" "139,677,722,280 bases; 152,280,170
sequences; 12,313,982 subseqs; 684,079 refers." "Software by M. Gouy, Lab. Biometrie et Biologie Evolutive,
Universite Lyon I "
> banknameSocket$details
[1] " **** ACNUC Data Base Content **** "
[2] " GenBank Rel. 189 (15 April 2012) Last Updated: May 1, 2012"
[3] "139,677,722,280 bases; 152,280,170 sequences; 12,313,982 subseqs; 684,079 refers."
[4] "Software by M. Gouy, Lab. Biometrie et Biologie Evolutive, Universite Lyon I "

Make a query:
# query (see next slide) all sequences that contain the words "virus" and "dengue" in the taxonomy field and
# that are not partial sequences
> system.time(query("All_Dengue_viruses_NOTpartial", ""sp=@virus@" AND "sp=@dengue@" AND
NOT "k=partial""))
user system elapsed
0.78 0.00 6.72

> All_Dengue_viruses_NOTpartial[1:4]
$call
query(listname = "All_Dengue_viruses_NOTpartial", query = ""sp=@virus@" AND "sp=@dengue@" AND
NOT "k=partial"")
$name
[1] "All_Dengue_viruses_NOTpartial"
$nelem
[1] 7741
$typelist
[1] "SQ"

> All_Dengue_viruses_NOTpartial[[5]][[1]]
name length frame ncbicg
"A13666" "456" "0" "1"

> myseq = getSequence(All_Dengue_viruses_NOTpartial[[5]][[1]])
> myseq[1:20]
[1] "a" "t" "g" "g" "c" "c" "a" "t" "g" "g" "a" "c" "c" "t" "t" "g" "g" "t" "g" "a"

> closebank()

Usage:
query(listname, query, socket = autosocket(), invisible = T, verbose = F, virtual = F)

Arguments:
listname - The name of the list as a quoted string of chars
query - A quoted string of chars containing the request with the syntax given in the details section
socket - An object of class sockconn connecting to a remote ACNUC database (default is a socket to the last opened
database).
invisible - if FALSE, the result is returned visibly.
verbose - if TRUE, verbose mode is on
virtual - if TRUE, no attempt is made to retrieve the information about all the elements of the list. In this case, the req
component of the list is set to NA.

Value:
The result is a list with the following 6 components:

call - the original call
name - the ACNUC list name
nelem - the number of elements (for instance sequences) in the ACNUC list
typelist - the type of the elements of the list. Could be SQ for a list of sequence names, KW for a list of keywords, SP for
a list of species names.
req - a list of sequence names that fit the required criteria or NA when called with parameter virtual is TRUE
socket - the socket connection that was used

SeqinR - biological data handling

More Related Content

Viewers also liked

Similar to SeqinR - biological data handling

Recently uploaded

In this document

SeqinR - biological data handling