Description Usage Arguments Details Value Author(s) References Examples
Use the BinQuasi algorithm to call peaks using ChIP-seq data with biological replicates.
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dir |
Directory where the sorted bam files (and their corresponding bam indices) are saved. |
ChIP.files |
File names (with file extensions) of the ChIP sample files in sorted bam format. |
control.files |
File names (with file extensions) of the control/input sample files in sorted bam format. |
alpha |
The desired significance threshold used to call peaks. Must be in (0, 0.5). |
bin.size |
Window size (constant across all samples) used to generate a
partition for counts. If |
frag.length |
Average length of the ChIP fragments in each sample
provided. Reads are extended to this length in the 5'-to-3' direction. If
|
minimum.count |
The count threshold used for filtering out windows with sparse counts. Any genomic window with a total count, across all samples, less than this value will be removed. |
Model |
Must be one of |
print.progress |
logical. If |
method |
Must be one of |
p.window.adjust |
FDR control method applied to the windows. Must be
either |
Dispersion |
Must be one of |
log.offset |
A vector of log-scale, additive factors used to adjust
estimated log-scale means for differences in library sizes across samples.
Commonly used offsets include |
NBdisp |
Used only when |
bias.fold.tolerance |
A numerical value no smaller than 1. If the bias
reduction of maximum likelihood estimates of (log) fold change is likely to
result in a ratio of fold changes greater than this value, then bias
reduction will be performed on such windows. Setting
|
This function calls peaks in replicated ChIP-seq data using the BinQuasi algorithm of Goren, Liu, Wang, and Wang.
A list containing:
peaks |
Dataframe of the called peaks with columns for the start and end location, width, chromosome, p-value, and q-value computed using the Benjamini and Hochberg method. |
bin.size |
The window width used to create the counts dataframe. |
fragment.length |
Vector of the fragment lengths used to extend the reads in each sample. |
filter |
The count threshold used to create the counts dataframe. Windows with counts below this value were removed. |
Emily Goren (emily.goren@gmail.com)
Goren, Liu, Wang and Wang (2018) "BinQuasi: a peak detection method for ChIP-sequencing data with biological replicates" Bioinformatics.
Shimazaki and Shinomoto (2007) "A method for selecting the bin size of a time histogram" Neural computation, 19(6), 1503-27.
Ramachandran, Palidwor, Porter, and Perkins (2013) "MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data" Bioinformatics 29(4), 444-50.
Benjamini and Hochberg (1995) "Controlling the false discovery rate: a practical and powerful approach to multiple testing" Journal of the Royal Statistical Society Series B, 57: 289-300.
Benjamini and Yekutieli (2001) "The control of the false discovery rate in multiple testing under dependency" Annals of Statistics. 29: 1165-1188.
Lund, Nettleton, McCarthy and Smyth (2012) "Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates" SAGMB, 11(5).
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