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Analysis of Variation in ChIP-seq using Functional PCA Statistics

Bioconductor version: 2.13

The double aim of the package is to apply a functional version of principal component analysis (FPCA) to: (1) Process data in wiggle track format (WIG) commonly produced by ChIP-seq peak finders by applying FPCA over a set of selected candidate enriched regions. This is done in order to shorten the genomic locations accounting for a given proportion of variation among the enrichment-score profiles. The function 'narrowpeaks' allows the user to discriminate between binding regions in close proximity to each other and to narrow down the length of the putative transcription factor binding sites while preserving the information present in the variability of the dataset and capturing major sources of variation. (2) Analyze differential variation when multiple ChIP-seq samples need to compared. The function 'narrowpeaksDiff' quantifies differences between the tag-enrichment, and uses non-parametric tests on the FPC scores for testing differences between conditions.

Author: Pedro Madrigal <pm at>, with contributions from Pawel Krajewski <pkra at>

Maintainer: Pedro Madrigal <pm at>

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PDF R Script NarrowPeaks Vignette I. Intra-sample variability: Splitting and narrowing down ChIP-seq peaks in a single experiment.
PDF R Script NarrowPeaks Vignette II. Inter-sample variability: Analysis of variation in differential binding across ChIP-seq samples.
PDF   Reference Manual
Text   NEWS


biocViews ChIPseq, Genetics, Software, Transcription, Visualization
Version 1.6.0
In Bioconductor since BioC 2.10 (R-2.15)
License Artistic-2.0
Depends R (>= 2.10.0), splines
Imports GenomicRanges, IRanges, fda, CSAR
Suggests rtracklayer, GenomicRanges, CSAR
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