Bioconductor version: 3.7
This article describes a computational workflow for performing a DB analysis with sliding windows. The aim is to facilitate the practical implementation of window-based DB analyses by providing detailed code and expected output. The workflow described here applies to any ChIP-seq experiment with multiple experimental conditions and with multiple biological samples within one or more of the conditions. It detects and summarizes DB regions between conditions in a *de novo* manner, i.e., without making any prior assumptions about the location or width of bound regions.Detected regions are then annotated according to their proximity to annotated genes. In addition, the code can be easily adapted to accommodate batch effects, covariates and multiple experimental factors.
Author: Aaron Lun [aut, cre], Gordon Smyth [aut]
Maintainer: Aaron Lun <alun at wehi.edu.au>
Citation (from within R,
enter citation("chipseqDB")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("chipseqDB")
To view available workflows for the version of this package installed in your system, start R and enter:
browseVignettes("chipseqDB")
HTML | R Script | Detecting differential binding of CBP in mouse fibroblasts |
HTML | R Script | Detecting differential enrichment of H3K9ac in murine B cells |
HTML | R Script | From reads to regions: a Bioconductor workflow to detect differential binding in ChIP-seq data |
biocViews | EpigeneticsWorkflow, Workflow |
Version | 1.2.0 |
License | Artistic-2.0 |
Depends | R (>= 3.3.0), BiocStyle, ChIPpeakAnno, Gviz, Rsamtools, Rsubread, TxDb.Mmusculus.UCSC.mm10.knownGene, csaw, edgeR, knitr, locfit, org.Mm.eg.db, rtracklayer, statmod |
Imports | |
LinkingTo | |
Suggests | knitr, rmarkdown |
SystemRequirements | |
Enhances | |
URL | https://www.bioconductor.org/help/workflows/chipseqDB/ |
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