Estimate False Discovery Rate within the relative substitution frequency support by integrating PAR-CLIP data and RNA-Seq data

Description

Estimate upper and lower bounds for the False Discovery Rate within the relative substitution frequency (RSF) support by integrating PAR-CLIP data and RNA-Seq data (current version makes use of unstranded RNA-Seq)

Usage

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estimateFDR(countTable, RNASeq, substitution = 'TC', minCov = 20,
span = 0.1, cores = 1, plot = TRUE, verbose = TRUE, ...)

Arguments

countTable

A GRanges object, corresponding to a count table as returned by the getAllSub function

RNASeq

GRanges object containing aligned RNA-Seq reads as returned by readSortedBam

substitution

A character indicating which substitution is induced by the experimental procedure (e.g. 4-SU treatment - a standard in PAR-CLIP experiments - induces T to C transitions and hence substitution = 'TC' in this case.)

minCov

An integer defining the minimum coverage required at a genomic position exhibiting a substitution. Genomic positions of coverage less than minCov are discarded. Default is 20 (see Details).

span

A numeric indicating the width of RSF intervals to be considered for FDR computation. Defauls is 0.1 (i.e. 10 intervals are considered spanning the RSF support (0,1]

cores

An integer defining the number of cores to be used for parallel processing, if available. Default is 1.

plot

Logical, if TRUE a dotchart with cluster annotations is produced

verbose

Logical, if TRUE processing steps are printed

...

Additional parameters to be passed to the plot function

Details

For details on the FDR computation, please see Comoglio, Sievers and Paro.

Value

A list with three slots, containing upper and lower FDR bounds, and the total number of positive instances each RSF interval. If plot, these three vectors are depicted as a line plot.

Note

The approach used to compute the upper bound for the FDR is very conservative. See supplementary information in Comoglio et al. for details.

Author(s)

Federico Comoglio and Cem Sievers

See Also

readSortedBam, getAllSub Comoglio F, Sievers C and Paro R (2015) Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data, BMC Bioinformatics 16, 32.

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