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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("methylPipe")
In most cases, you don't need to download the package archive at all.
methylPipe
Base resolution DNA methylation data analysis
Bioconductor version: 3.0
Memory efficient analysis of base resolution DNA methylation data in both the CpG and non-CpG sequence context. Integration of DNA methylation data derived from any methodology providing base- or low-resolution data.
Author: Kamal Kishore
Maintainer: Kamal Kishore <kamal.fartiyal84 at gmail.com>
Citation (from within R,
enter citation("methylPipe")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("methylPipe")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("methylPipe")
| R Script | methylPipe.pdf | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Coverage, DNAMethylation, MethylSeq, Sequencing, Software |
| Version | 1.0.5 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL(>=2) |
| Depends | R (>= 3.1.1), methods, grDevices, graphics, stats, utils, GenomicRanges, Rsamtools |
| Imports | marray, gplots, IRanges, BiocGenerics, Gviz, GenomicAlignments, Biostrings, parallel, data.table, GenomeInfoDb, S4Vectors |
| LinkingTo | |
| Suggests | BSgenome.Hsapiens.UCSC.hg18, TxDb.Hsapiens.UCSC.hg18.knownGene, knitr, MethylSeekR |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | ListerEtAlBSseq |
| Imports Me | compEpiTools |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | methylPipe_1.0.5.tar.gz |
| Windows Binary | methylPipe_1.0.5.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | methylPipe_1.0.5.tgz |
| Mac OS X 10.9 (Mavericks) | methylPipe_1.0.5.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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