DOI: 10.18129/B9.bioc.exomePeak2    

This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see exomePeak2.

Bias-aware Peak Calling and Quantification for MeRIP-Seq

Bioconductor version: 3.14

exomePeak2 provides bias-aware quantification and peak detection for Methylated RNA immunoprecipitation sequencing data (MeRIP-Seq). MeRIP-Seq is a commonly applied sequencing technology that can measure the location and abundance of RNA modification sites under given cell line conditions. However, quantification and peak calling in MeRIP-Seq are sensitive to PCR amplification biases, which generally present in next-generation sequencing (NGS) technologies. In addition, the count data generated by RNA-Seq exhibits significant biological variations between biological replicates. exomePeak2 collectively address the challenges by introducing a series of robust data science tools tailored for MeRIP-Seq. Using exomePeak2, users can perform peak calling, modification site quantification and differential analysis through a straightforward single-step function. Alternatively, multi-step functions can be used to generate diagnostic plots and perform customized analyses.

Author: Zhen Wei [aut, cre]

Maintainer: Zhen Wei <zhen.wei10 at icloud.com>

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biocViews Coverage, DifferentialExpression, ExomeSeq, MethylSeq, Normalization, Preprocessing, RNASeq, Sequencing, Software
Version 1.6.1
In Bioconductor since BioC 3.11 (R-4.0) (2 years)
License GPL (>= 2)
Depends R (>= 3.5.0), SummarizedExperiment, cqn
Imports Rsamtools, GenomicAlignments, GenomicRanges, GenomicFeatures, DESeq2, ggplot2, mclust, genefilter, Biostrings, BSgenome, BiocParallel, IRanges, S4Vectors, reshape2, rtracklayer, apeglm, methods, stats, utils, Biobase, GenomeInfoDb, BiocGenerics
Suggests knitr, rmarkdown, RMariaDB
BugReports https://github.com/ZW-xjtlu/exomePeak2/issues
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