bch441-work-abc-units/RPR-Biostrings.R

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# tocID <- "RPR-Biostrings.R"
#
# ---------------------------------------------------------------------------- #
# PATIENCE ... #
# Do not yet work wih this code. Updates in progress. Thank you. #
# boris.steipe@utoronto.ca #
# ---------------------------------------------------------------------------- #
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#
# Purpose: A Bioinformatics Course:
# R code accompanying the RPR-Biostrings unit.
#
# Version: 1.1
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#
# Date: 2017 10 - 2019 01
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# Author: Boris Steipe (boris.steipe@utoronto.ca)
#
# Versions:
# 1.1 Change from require() to requireNamespace(),
# use <package>::<function>() idiom throughout,
# use Biocmanager:: not biocLite()
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# 1.0 2017 Revisions
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# 0.1 First code copied from 2016 material.
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#
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#
# TODO:
#
#
# == DO NOT SIMPLY source() THIS FILE! =======================================
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#
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# If there are portions you don't understand, use R's help system, Google for an
# answer, or ask your instructor. Don't continue if you don't understand what's
# going on. That's not how it works ...
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#
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# ==============================================================================
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#TOC> ==========================================================================
#TOC>
#TOC> Section Title Line
#TOC> ---------------------------------------------------------------
#TOC> 1 The Biostrings Package 55
#TOC> 2 Getting Data into Biostrings Objects 86
#TOC> 3 Working with Biostrings Objects 108
#TOC> 3.1 Properties 125
#TOC> 3.2 Subsetting 163
#TOC> 3.3 Operators 175
#TOC> 3.4 Transformations 182
#TOC> 4 Getting Data out of Biostrings Objects 189
#TOC> 5 More 198
#TOC> 5.1 Views 200
#TOC> 5.2 Iranges 214
#TOC> 5.3 StringSets 220
#TOC>
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#TOC> ==========================================================================
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# This is a very brief introduction to the biostrings package, other units will
# be using more of the biostrings functions.
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# = 1 The Biostrings Package ==============================================
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# First, we install and load the Biostrings package from bioconductor
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if (! requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
if (! requireNamespace("Biostrings", quietly = TRUE)) {
BiocManager::install("Biostrings")
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}
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# Examine the package information:
library(help = Biostrings) # basic information
browseVignettes("Biostrings") # available vignettes
data(package = "Biostrings") # available datasets
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# At its core, Biostrings objects are "classes" of type XString (you can think
# of a "class" in R as a special kind of list), that can take on particular
# flavours for RNA, DNA or amino acid sequence information.
class(Biostrings::RNAString("AUG"))
class(Biostrings::DNAString("ATG"))
class(Biostrings::AAString("M"))
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# An essential property of Biostrings objects is that they only allow letters
# from the applicable IUPAC alphabet:
Biostrings::RNAString("AUG")
Biostrings::DNAString("AUG") # Error! No "U" in IUPAC DNA codes
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# = 2 Getting Data into Biostrings Objects ================================
# Example: read FASTA. Extract sequence. Convert to DNAString object.
rawSeq <- readLines("./data/S288C_YDL056W_MBP1_coding.fsa")
rawSeq <- dbSanitizeSequence(rawSeq)
biosDNAseq <- Biostrings::DNAString(rawSeq) # converts the nucleotide sequence
# into an object of class DNAstring
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# Multi FASTA files can be read directly as a "XStringSet) ...
rawMFAfile <- "./data/S288C_YDL056W_MBP1_coding.fsa"
(biosDNASet <- Biostrings::readDNAStringSet(rawMFAfile))
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# ... and if you subset one sequence from the set, you get an XString object
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# back again.
(Xseq <- biosDNASet[[1]])
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biosDNAseq == Xseq # the comparison evaluates to TRUE ...
identical(biosDNAseq, Xseq) # ... and indeed the objects are deemed identical.
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# = 3 Working with Biostrings Objects =====================================
# Biostrings is a highly engineered package that is tightly integrated into
# the Bioconductor world - unfortunately that brings with it a somewhat
# undesirable level of computational overhead and dependencies. Using the
# package as we normally do - i.e. calling required functions with their
# explicit package prefix is therefore not advisable. There are generics
# that won't be propery dispatched. If you only need a small number of
# functions for a very specific context, you will probably get away with
# Biostrings::<function>() - but even in the demonstration code of this script
# not everything works out of the box. We'll therefore load the library,
# but we'll (redundantly) use the prefix anyway so as to emphasize where
# the functions come from.
library(Biostrings)
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# == 3.1 Properties ========================================================
str(rawSeq)
str(biosDNAseq)
length(rawSeq) # ... is 1: one string only. To get the number of
# characters in a string, you need nchar().
length(biosDNAseq) # but the length of a "Bstring" is the number of elements
nchar(rawSeq)
nchar(biosDNAseq) # ... but nchar() works too.
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(uL <- Biostrings::uniqueLetters(biosDNAseq))
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# Count frequencies - with strings, you would strsplit() into a character
# vector and then use table(). biost
Biostrings::alphabetFrequency(biosDNAseq)
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# letterFrequency() works with a defined alphabet - such as what uniqueLetters()
# returns.
Biostrings::letterFrequency(biosDNAseq, uL)
sum(Biostrings::letterFrequency(biosDNAseq, c("G", "C"))) /
length(biosDNAseq) # GC contents
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Biostrings::dinucleotideFrequency(biosDNAseq)
barplot(sort(Biostrings::dinucleotideFrequency(biosDNAseq)), cex.names = 0.5)
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(triNuc <- Biostrings::trinucleotideFrequency(biosDNAseq))
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barplot(sort(triNuc), col="#4499EE33")
triNuc[triNuc == max(triNuc)]
triNuc[triNuc == min(triNuc)]
max(triNuc) / min(triNuc) # AAA is more than 13 times as frequent as CGT
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# compare to a shuffled sequence:
(triNuc <- Biostrings::trinucleotideFrequency(sample(biosDNAseq)))
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barplot(sort(triNuc), col="#EEEE4433", add = TRUE)
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# Interpret this plot.
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# == 3.2 Subsetting ========================================================
# Subsetting any XString object works as expected:
biosDNAseq[4:15]
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# ... well - maybe not expected, because rawSeq[4:15] would not work.
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# Alternatively to the "[" operator, use the subseq() function - especially for
# long sequences. This is far more efficient.
Biostrings::subseq(biosDNAseq, start = 1, end = 30)
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# == 3.3 Operators =========================================================
# RNAstring() and DNAstring() objects compare U and T as equals!
Biostrings::RNAString("AUGUCUAACCAAAUAUACUCAGCGAGAUAU") ==
Biostrings::DNAString("ATGTCTAACCAAATATACTCAGCGAGATAT")
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# == 3.4 Transformations ===================================================
biosDNAseq[4:15]
Biostrings::reverseComplement(biosDNAseq[4:15])
Biostrings::translate(biosDNAseq[4:15])
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# = 4 Getting Data out of Biostrings Objects ==============================
# If you need a character object, use toString():
Biostrings::toString(biosDNAseq[4:15])
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# saveRDS() and readRDS() works like on all other R objects.
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# = 5 More ================================================================
# == 5.1 Views =============================================================
# Biostring "Views" are objects that store multiple substrings of one
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# Biostring object.
(myView <- Biostrings::Views(biosDNAseq,
start = c(1, 19, 37),
end = c(15, 30, 45)))
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# Views are convenient to store feature annotations
names(myView) <- c("Feature-A", "Feature-B", "Feature-C")
cat(sprintf("\n%s\t(%d)\t%s", names(myView), width(myView), myView ))
# == 5.2 Iranges ===========================================================
# Biostrings Iranges are like Views with a common start point. These can be
# useful for feature annotations. Instead of start/end you store start/width.
# == 5.3 StringSets ========================================================
# Biostring "StringSets" store multiple sequences.
#
ompA <- Biostrings::AAString("MKKTAIAIAVALAGFATVAQA")
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sample(ompA) # sample can work directly on a Biostring object to shuffle it
x <- Biostrings::toString(ompA)
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for (i in 2:10) {
x[i] <- Biostrings::toString(sample(ompA))
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}
shuffledPeptideSet <- Biostrings::AAStringSet(x)
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names(shuffledPeptideSet) <- c("ompA", paste("shuffle.", 1:9, sep=""))
shuffledPeptideSet
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length(shuffledPeptideSet)
Biostrings::width(shuffledPeptideSet)
Biostrings::alphabetFrequency(shuffledPeptideSet)
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# [END]