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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("HTSFilter")
In most cases, you don't need to download the package archive at all.
HTSFilter
Filter replicated high-throughput transcriptome sequencing data
Bioconductor version: 3.0
This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions.
Author: Andrea Rau, Melina Gallopin, Gilles Celeux, and Florence Jaffrezic
Maintainer: Andrea Rau <andrea.rau at jouy.inra.fr>
Citation (from within R,
enter citation("HTSFilter")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("HTSFilter")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("HTSFilter")
| R Script | HTSFilter Vignette | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, Preprocessing, RNASeq, Sequencing, Software |
| Version | 1.6.0 |
| In Bioconductor since | BioC 2.12 (R-3.0) |
| License | Artistic-2.0 |
| Depends | methods, Biobase(>= 2.16.0), R (>= 2.10.0) |
| Imports | DESeq(>= 1.8.3), edgeR(>= 2.6.12), DESeq2(>= 1.2.8), GenomicRanges, IRanges |
| LinkingTo | |
| Suggests | EDASeq(>= 1.2.0) |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | HTSFilter_1.6.0.tar.gz |
| Windows Binary | HTSFilter_1.6.0.zip |
| Mac OS X 10.6 (Snow Leopard) | HTSFilter_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | HTSFilter_1.6.0.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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