To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("TSSi")
In most cases, you don't need to download the package archive at all.
TSSi
Transcription Start Site Identification
Bioconductor version: 3.0
Identify and normalize transcription start sites in high-throughput sequencing data.
Author: Clemens Kreutz, Julian Gehring
Maintainer: Julian Gehring <julian.gehring at embl.de>
Citation (from within R,
enter citation("TSSi")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("TSSi")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("TSSi")
| R Script | Introduction to the TSSi package: Identification of Transcription Start Sites | |
| Reference Manual |
Details
| biocViews | Genetics, Preprocessing, RNASeq, Sequencing, Software |
| Version | 1.12.0 |
| In Bioconductor since | BioC 2.9 (R-2.14) |
| License | GPL-3 |
| Depends | R (>= 2.13.2), BiocGenerics(>= 0.3.2), IRanges |
| Imports | methods, BiocGenerics, S4Vectors, Hmisc, minqa, stats, Biobase(>= 0.3.2), plyr, IRanges |
| LinkingTo | |
| Suggests | rtracklayer |
| SystemRequirements | |
| Enhances | parallel |
| URL | http://julian-gehring.github.com/TSSi/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | TSSi_1.12.0.tar.gz |
| Windows Binary | TSSi_1.12.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | TSSi_1.12.0.tgz |
| Mac OS X 10.9 (Mavericks) | TSSi_1.12.0.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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