Description Usage Arguments Details Value Author(s) Examples
groupRatio
takes a bamRange
and returns a data.frame
(128 rows, number of columns=length of the longest sequence in range).
groupRatio
counts occurrences for every sequence position (column) and
every phred value (row).
getQualQuantiles
takes a bamReader
and a vector of quantiles
(must be between 0 and 1) and returns a data.frame.
The data.frame contains one row for each quantile and also as many columns
as the maximum sequence length. plotQualQuant
plots the values
for quanties 0.1,0.25,0.5,0.75 and 0.9.
1 | groupRatio(object, lim=1.2, cut=0, order=NULL, f=mean)
|
object |
exonLoessModel |
lim |
numeric. Limit ratio. Must be > 1. The function returns the fraction of genetic position where AD-ratio between groups is > lim or the fraction of positions where AD-Ratio is < 1/lim (i.e the larger ratio). |
cut |
numeric. When >0 , the function uses |
order |
numeric. When given, the function reorders the sample groups. Can be used to provide ascending (or descending) group ordering, e.g. group1 < group2 < group3. |
f |
function. Function for calculation of group accumulates.
Defaults to |
The size of the returned value (abs(groupRatio)) indicates on which proportion of the genetic region, AD ratio between subsequent groups exceeds the given limit. For lim=1.1, group1<group2<group3, a returned value of 0.8 says that the AD ratios group2:group1 and group3:group2 are at least 1.1 (> 1) on 80 percent of the contained genomic positions. Negative values say that the relation is group1>group2>group3. This allows discrimination of up- and down-regulated genes.
numeric
Wolfgang Kaisers
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# Construct sampleBamFiles object
bam <- system.file("extdata", "accepted_hits.bam", package="rbamtools")
bs <- sampleBamFiles(1)
bamFiles(bs) <- bam
sampleLabels(bs) <- "s1"
sampleGroups(bs) <- "g1"
checkBamFiles(bs)
nAligns(bs) <- bamCountAll(bs)
bs
## - - - - - - - - - - - - - - - - - - - - - - ##
# Construct geneModel object
library(refGenome)
ucfile <- system.file("extdata", "hs.ucsc.small.RData", package="refGenome")
uc <- loadGenome(ucfile)
gt <- getGeneTable(uc)
gene_id <- as.character(gt$gene_id[1])
gm <- geneModel(uc, gene_id)
## - - - - - - - - - - - - - - - - - - - - - - ##
# Construct geneAlignDepth object
gad <- geneAlignDepth(bs, gm)
## - - - - - - - - - - - - - - - - - - - - - - ##
# Extract exonLoessModel object
ead <- exonAlignDepth(gad, ratioLim=5, infVal=1000)
elm <- exonLoessModel(ead)
celm <- cutFlatAlignDepth(elm, ratio=0.1)
groupRatio(celm, lim=1.2, cut=0, order=1)
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