To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GOTHiC")
In most cases, you don't need to download the package archive at all.
GOTHiC
Binomial test for Hi-C data analysis
Bioconductor version: 3.0
This is a Hi-C analysis package using a cumulative binomial test to detect interactions between distal genomic loci that have significantly more reads than expected by chance in Hi-C experiments. It takes mapped paired NGS reads as input and gives back the list of significant interactions for a given bin size in the genome.
Author: Borbala Mifsud and Robert Sugar
Maintainer: Borbala Mifsud <Borbala.Mifsud at cancer.org.uk>
Citation (from within R,
enter citation("GOTHiC")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GOTHiC")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GOTHiC")
| package_vignettes.pdf | ||
| Reference Manual |
Details
| biocViews | Epigenetics, Preprocessing, Sequencing, Software |
| Version | 1.2.2 |
| In Bioconductor since | BioC 2.14 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 2.15.1), methods, utils, GenomicRanges, Biostrings, BSgenome, data.table |
| Imports | BiocGenerics, S4Vectors, IRanges, ShortRead, rtracklayer, ggplot2 |
| LinkingTo | |
| Suggests | HiCDataLymphoblast |
| SystemRequirements | |
| Enhances | parallel |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | HiCDataLymphoblast |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | GOTHiC_1.2.2.tar.gz |
| Windows Binary | GOTHiC_1.2.2.zip |
| Mac OS X 10.6 (Snow Leopard) | GOTHiC_1.2.2.tgz |
| Mac OS X 10.9 (Mavericks) | GOTHiC_1.2.2.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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