Package 'leeBamViews'

BamViews instance construction related to yeast RNA-seq

Description

BamViews instance construction related to yeast RNA-seq

Format

The format is: Formal class 'BamViews' [package "Rsamtools"] with 5 slots
..@ bamPaths : chr [1:8] "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/isowt5_13e.bam" "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/isowt6_13e.bam" "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/rlp5_13e.bam" "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/rlp6_13e.bam" ...
..@ bamIndicies : chr [1:8] "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/isowt5_13e.bam" "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/isowt6_13e.bam" "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/rlp5_13e.bam" "/Users/stvjc/ExternalSoft/R-devel/library/leeBamViews/bam/rlp6_13e.bam" ...
..@ bamSamples :Formal class 'DataFrame' [package "IRanges"] with 6 slots
.. .. ..@ rownames : chr [1:8] "isowt.5" "isowt.6" "rlp.5" "rlp.6" ...
.. .. ..@ nrows : int 8
.. .. ..@ elementMetadata: NULL
.. .. ..@ elementType : chr "ANY
" .. .. ..@ metadata : list()
.. .. ..@ listData :List of 2
.. .. .. ..$ geno: chr [1:8] "isowt" "isowt" "rlp" "rlp" ...
.. .. .. ..$ lane: chr [1:8] "5" "6" "5" "6" ...
..@ bamRanges :Formal class 'GRanges' [package "GenomicRanges"] with 7 slots
.. .. ..@ seqnames :Formal class 'Rle' [package "IRanges"] with 5 slots
.. .. .. .. ..@ values : Factor w/ 1 level "Scchr13": 1
.. .. .. .. ..@ lengths : int 27
.. .. .. .. ..@ elementMetadata: NULL
.. .. .. .. ..@ elementType : chr "ANY"
.. .. .. .. ..@ metadata : list()
.. .. ..@ ranges :Formal class 'IRanges' [package "IRanges"] with 6 slots
.. .. .. .. ..@ start : int [1:27] 798517 801771 804455 808999 810465 811088 818826 820255 822762 832338 ...
.. .. .. .. ..@ width : int [1:27] 2862 933 636 234 114 108 1122 2199 1869 915 ...
.. .. .. .. ..@ NAMES : NULL
.. .. .. .. ..@ elementMetadata: NULL
.. .. .. .. ..@ elementType : chr "integer"
.. .. .. .. ..@ metadata : list()
.. .. ..@ strand :Formal class 'Rle' [package "IRanges"] with 5 slots
.. .. .. .. ..@ values : Factor w/ 3 levels "+","-","*": 1
.. .. .. .. ..@ lengths : int 27
.. .. .. .. ..@ elementMetadata: NULL
.. .. .. .. ..@ elementType : chr "ANY"
.. .. .. .. ..@ metadata : list()
.. .. ..@ seqlengths : Named int NA
.. .. .. ..- attr(*, "names")= chr "Scchr13"
.. .. ..@ elementMetadata:Formal class 'DataFrame' [package "IRanges"] with 6 slots
.. .. .. .. ..@ rownames : NULL
.. .. .. .. ..@ nrows : int 27
.. .. .. .. ..@ elementMetadata: NULL
.. .. .. .. ..@ elementType : chr "ANY"
.. .. .. .. ..@ metadata : list()
.. .. .. .. ..@ listData :List of 1
.. .. .. .. .. ..$ name: chr [1:27] "YMR266W" "YMR267W" "YMR269W" "YMRWdelta20" ...
.. .. ..@ elementType : chr "ANY"
.. .. ..@ metadata : list()
..@ bamExperiment:List of 1
.. ..$ annotation: chr "org.Sc.sgd.db"

Details

Illumina short reads from a very small segment of yeast chr XIII have been collected

Source

FASTQ data available at ftp://ftp.ncbi.nlm.nih.gov/sra/Studies/SRP000/SRP000632/

References

Albert Lee and Kasper Daniel Hansen and James Bullard and Sandrine Dudoit and Gavin Sherlock, Novel Low Abundance and Transient RNAs in Yeast Revealed by Tiling Microarrays and Ultra High–Throughput Sequencing Are Not Conserved Across Closely Related Yeast Species, PLoS Genet, v4, e1000299, Dec 2008

Examples

library(leeBamViews)  # bam files stored in package
bpaths = dir(system.file("bam", package="leeBamViews"), full=TRUE, patt="bam$")
#
# extract genotype and lane information from filenames
#
gt = gsub(".*/", "", bpaths)
gt = gsub("_.*", "", gt)
lane = gsub(".*(.)$", "\\1", gt)
geno = gsub(".$", "", gt)
#
# format the sample-level information appropriately
#
pd = DataFrame(geno=geno, lane=lane, row.names=paste(geno,lane,sep="."))
prd = new("DFrame")  # protocol data could go here
#
# create the views object, adding some arbitrary experiment-level information
#
bs1 = BamViews(bamPaths=bpaths, bamSamples=pd,
        bamExperiment=list(annotation="org.Sc.sgd.db"))
bs1
# add ranges and tabulate reads

START=c(861250, 863000)
END=c(862750, 864000)
exc = GRanges(IRanges(start=START, end=END), seqnames="Scchr13", strand="+")
values(exc)$name = c("intv1", "intv2")  # necessary
bamRanges(bs1) = exc
bs1
tabulateReads(bs1, "+")

---

supplemental data extract on RNA seq results in yeast

Description

supplemental data extract on RNA seq results in yeast

Usage

data(leeRPKM)

Format

A data frame with 6291 observations on the following 16 variables.

chr

a numeric vector

strand

a numeric vector

start

a numeric vector

end

a numeric vector

name

a factor with levels LSR1 NME1 YAL001C YAL002W YAL003W ...

feature

a factor with levels CDS CDS_unchar snRNA snoRNA

orf_classification

a factor with levels Uncharacterized Verified silenced_gene3AVerified

gene

a factor with levels AAC1 AAC3 AAD10 AAD14 AAD15 AAD16 AAD3 AAD4 ...

wt.reads

a numeric vector

rrp.reads

a numeric vector

ski.reads

a numeric vector

xrn.reads

a numeric vector

wt.rpkm

a numeric vector

rrp.rpkm

a numeric vector

ski.rpkm

a numeric vector

xrn.rpkm

a numeric vector

Source

imported from supplemental data

References

Lee et al PLOS genetics December 2008 ; Volume 4 ; Issue 12 ; e1000299

Examples

data(leeRPKM)
leeRPKM[1:5,]

---

supplemental data extracts on existing evidence of transcription in yeast

Description

supplemental data extracts on existing evidence of transcription in yeast

Usage

data(leeUnn)

Format

A data frame with 54822 observations on the following 11 variables.

chr

a numeric vector

start

a numeric vector

end

a numeric vector

strand

a numeric vector

lengthWithoutMask

a numeric vector

length

a numeric vector

lambda

a numeric vector

background5

a logical vector

background20

a logical vector

reads

a numeric vector

study

a factor with levels David Davis Miura Nagalakshmi

Source

from Lee et al PLoS genetics December 2008 Volume 4 Issue 12 e1000299 supplemental data

information on unnannotated transcripts for which some evidence of transcription was obtained in this experiment

Examples

data(leeUnn)
leeUnn[1:5,]

---

tabulate counts of alignments occurring in specified genomic regions

Description

tabulate counts of alignments occurring in specified genomic regions

Usage

tabulateReads(bv, strandmarker=NULL, as.GRanges=FALSE, applier=lapply)

Arguments

bv	BamViews-class instance
strandmarker	character atom: ‘+’ or ‘-’; if missing, ignore strand
as.GRanges	logical directive to return a GRanges instance instead of a matrix
applier	lapply-like function; if unspecified and multicore is attached will use mclapply

Details

readGAlignments is the basic engine for this task

Value

annotated matrix with start, end, and samples as rows, regions as columns, and read counts as cell entries

Author(s)

VJ Carey <[email protected]>

Examples

example(bs1)
#
# counts in a partition
#
myrn = GRanges(IRanges(start=seq(861250, 862750, 100), width=100),
    seqnames="Scchr13", strand="+")

values(myrn)$name = paste("til", 1:length(myrn), sep=".")
bamRanges(bs1) = myrn
tabulateReads(bs1, "+")
#
# a related computation based on countBam
lapply(bamPaths(bs1)[1:2], function(x) 
    countBam(x,  param=ScanBamParam(which=bamRanges(bs1))))

---

scan BAM files for total read counts

Description

scan BAM files for total read counts

Usage

totalReadCounts(x)

Arguments

x	BamViews-class instance

Details

slow procedure – does lightweight scan of entire file

Value

named integer vector of read counts per sample

Author(s)

VJ Carey <[email protected]>

Examples

example(bs1)
totalReadCounts(bs1)

---