samExplore: samExplore:

In shaileshtripathi/samExploreR: samExploreR package: high-performance read summarisation to count vectors with avaliability of sequencing depth reduction simulation

Description

samExplore: This function assigns mapped sequencing reads to genomic features and simulates a sample with reduced sequencing depth

Usage

samExplore(..., subsample_d=1, N_boot=1,
    countboot=c("all","Assigned", "Unassigned_Ambiguity",
    "Unassigned_MultiMapping",   "Unassigned_NoFeatures",
    "Unassigned_Unmapped",       "Unassigned_MappingQuality",
    "Unassigned_FragmentLength", "Unassigned_Chimera",
    "Unassigned_Secondary",      "Unassigned_Nonjunction",
    "Unassigned_Duplicate" ))

Arguments

...	These are the same arguments of featureCounts function of Rsubread package, for more details check featureCounts function.
subsample_d	numeric value which describes fraction of reads to be remained in subsampling.
N_boot	integer value for number of resample procedures to be run.
countboot	is a character vector which contains following options: all,Assigned, Unassigned_Ambiguity, Unassigned_MultiMapping, Unassigned_NoFeatures, Unassigned_Unmapped, Unassigned_MappingQuality, Unassigned_FragmentLength, Unassigned_Chimera, Unassigned_Secondary, Unassigned_Nonjunction, Unassigned_Duplicate A user can select any of theses options for resampling if user selects all then the resampling procedure will consider all assigned and unassigned reads. If a user selects Assigned option then resampling procedure will consider Assigned reads only for resampling. If a user selects any other option it will consider those unmapped reads along with Assigned reads. A user can selects more than one choices and input as a vector

Details

samExplore See featureCounts for details. Output is a list objects which has three components. 1) "bootres": is a list object of size of input files, each list object contains a resampling matrix of features.

2) "target.size": it is a numeric vector contains total feature counts of a certain sequence depth for each input file.

3) "feature main": returns a list object which is the ouptput of 'featureCounts' function of Rsubread package.

Value

returns a list object.

Examples

# Simulate a sample with sequencing depth 80% of initial for SAM format 
# single-end reads using built-in RefSeq annotation for hg19:
#### Consider all mapped and unmapped reads for resampling##
inpf <- RNAseqData.HNRNPC.bam.chr14_BAMFILES
res1 <- samExplore(files=inpf,annot.inbuilt="hg19", subsample_d = 0.8)

#### Consider Assigned and Unassigned Unmapped reads for resampling##
res2 <- samExplore(inpf, N_boot=10, subsample_d=.8,
    countboot=c("Assigned","Unassigned_Unmapped"))

#### Consider only Assigned reads for resampling##
res3 <- samExplore(inpf, N_boot=10, subsample_d=.8,
    countboot="Assigned")

shaileshtripathi/samExploreR documentation built on May 29, 2019, 8:06 p.m.