Package DNaseR. November 1, 2013
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1 Package DNaseR November 1, 2013 Version Date Type Package Title DNase I footprinting analysis of DNase-seq data Author Pedro Madrigal <pm@engineering.com> Description Strand-specific digital genomic footprinting in DNase-seq data. The cumulative Skellam distribution function (package 'skellam') is used to detect significant normalized count differences of opposed sign at each DNA strand. This is done in order to determine the proteinbinding footprint flanks. Preprocessing of the mapped reads is recommended before running DNaseR (e.g., quality checking and removal of sequence-specific bias). Depends R (>= ), IRanges Maintainer Pedro Madrigal <pm@engineering.com> Imports Rsamtools, GenomicRanges Suggests RUnit, BiocGenerics License GPL-2 + file LICENSE biocviews Transcription, Genetics LazyLoad yes LazyData yes R topics documented: DNaseR-package footprints Index 6 1
2 2 DNaseR-package DNaseR-package DNase I footprinting analysis of DNase-seq data Description Details Strand-specific digital genomic footprinting in DNase-seq data. The cumulative Skellam distribution function (package skellam ) is used to detect significant normalized count differences of opposed sign at each DNA strand. This is done in order to determine the protein-binding footprint flanks. Preprocessing of the mapped reads is recommended before running DNaseR (e.g., quality checking and removal of sequence specific bias). Package: DNaseR Type: Package Version: Date: License: GPL-2 + file LICENSE LazyLoad: yes Author(s) Pedro Madrigal, Maintainer: Pedro Madrigal <pm@engineering.com> References Madrigal P, Krajewski P (2012) Current bioinformatic approaches to identify DNase I hypersensitive sites and genomic footprints from DNase-seq data. Front Genet 3: 230. Neph S, Vierstra J, Stergachis AB, Reynolds AP, Haugen E, Vernot B, Thurman RE, John S, Sandstrom R, Johnson AK, Maurano MT, Humbert R, Rynes E, Wang H, Vong S, Lee K, Bates D, Diegel M, Roach V, Dunn D, Neri J, Schafer A, Hansen RS, Kutyavin T, Giste E, Weaver M, Canfield T, Sabo P, Zhang M, Balasundaram G, Byron R, MacCoss MJ, Akey JM, Bender MA, Groudine M, Kaul R, Stamatoyannopoulos JA (2012) An expansive human regulatory lexicon encoded in transcription factor footprints. Nature 489: Skellam JG (1946) The frequency distribution of the difference between two Poisson variates belonging to different populations. J R Stat Soc Ser A 109: 296. Song L, Crawford GE (2010) DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb Protoc 2:pdb.prot5384.
3 footprints 3 Examples ## hg18. chry:1-3000kb reads from DNase-seq dataset wgencodeuwdgfth1aln.bam ## from the ENCODE Project. ## ## Downloaded from: ## ## release1/wgencodeuwdgfth1aln.bam owd <- setwd(tempdir()) bamfile <- "chry_3kb_wgencodeuwdgfth1aln.bam" f <- system.file("extdata", bamfile, package="dnaser",mustwork = TRUE) dgf <- footprints(bam=f, chrn="chry", chrl=3e6, p=1e-9, width=c(6,40), N=2e6) setwd(owd) footprints DNase I footprinting analysis of DNase-seq data Description DNase I footprinting analysis of DNase-seq data. Usage footprints(bam, chrn, chrl, p=1e-9, width=c(6,40), N=5e6, correction="bh") Arguments bam chrn chrl p width N correction BAM file of DNase-seq mapped reads. Vector of chromosome names. Vector of chromosome sizes (bp). p-value cutoff for the footprint events (default 1e-9). Max. and min. footprint width (bp). Genome is divided in blocks of N bp. for processing. N must be not higher than the size of the smallest chromosome. Multiple comparison adjustment method for the p-values at each flank of a footprint. Allowed values are same as in p.adjust: "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none" (default "BH").
4 4 footprints Details Strand-specific digital genomic footprinting in DNase-seq data. The cumulative Skellam distribution function (package skellam ) is used to detect significant normalized count differences of opposed sign at each DNA strand. This is done in order to determine the footprint flanks. Preprocessing of the mapped reads is recommended before running DNaseR (e.g., quality checking and removal of sequence-specific bias). Initially, one p-value is calculated at each flank of the footprint. To control for multiple testing, the p-values delimiting each flank of the footprint (pval.forward and pval.reverse) are corrected using Benjamini-Hochberg procedure ("BH", default). The column pval.footprint.event stores the sum pval.forward + pval.reverse. The internal functions pskellam and pskellam.sp from the Jerry W. Lewis skellam R package (version ) are used to calculate the cumulative Skellam distribution (see LICENSE file). Value footprints.events A data.frame with the location of each footprint ("chr","start","end"), the width of the footprint ("length"), the corrected p-values at each flank ("pval.forward","pval.reverse"), the final p-value of the footprint ("pval.footprint.event") and its -log10 ("log10.pval.footprint.event"). Author(s) Pedro Madrigal, <pm@engineering.com> References Madrigal P, Krajewski P (2012) Current bioinformatic approaches to identify DNase I hypersensitive sites and genomic footprints from DNase-seq data. Front Genet 3: 230. Neph S, Vierstra J, Stergachis AB, Reynolds AP, Haugen E, Vernot B, Thurman RE, John S, Sandstrom R, Johnson AK, Maurano MT, Humbert R, Rynes E, Wang H, Vong S, Lee K, Bates D, Diegel M, Roach V, Dunn D, Neri J, Schafer A, Hansen RS, Kutyavin T, Giste E, Weaver M, Canfield T, Sabo P, Zhang M, Balasundaram G, Byron R, MacCoss MJ, Akey JM, Bender MA, Groudine M, Kaul R, Stamatoyannopoulos JA (2012) An expansive human regulatory lexicon encoded in transcription factor footprints. Nature 489: Skellam JG (1946) The frequency distribution of the difference between two Poisson variates belonging to different populations. J R Stat Soc Ser A 109: 296. Song L, Crawford GE (2010) DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb Protoc 2:pdb.prot5384. See Also DNaseR-package
5 footprints 5 Examples ## hg18. chry:1-3000kb reads from DNase-seq dataset wgencodeuwdgfth1aln.bam ## from the ENCODE Project. ## ## Downloaded from: ## ## release1/wgencodeuwdgfth1aln.bam owd <- setwd(tempdir()) bamfile <- "chry_3kb_wgencodeuwdgfth1aln.bam" f <- system.file("extdata", bamfile, package="dnaser",mustwork = TRUE) dgf <- footprints(bam=f, chrn="chry", chrl=3e6, p=1e-9, width=c(6,40), N=2e6) setwd(owd)
6 Index DNaseR (DNaseR-package), 2 DNaseR-package, 2 footprints, 3 6
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Type Package Package mosaics July 3, 2018 Title MOSAiCS (MOdel-based one and two Sample Analysis and Inference for ChIP-Seq) Version 2.19.0 Depends R (>= 3.0.0), methods, graphics, Rcpp Imports MASS, splines,
Analyzing ChIP- Seq Data in Galaxy
Analyzing ChIP- Seq Data in Galaxy Lauren Mills RISS ABSTRACT Step- by- step guide to basic ChIP- Seq analysis using the Galaxy platform. Table of Contents Introduction... 3 Links to helpful information...