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https://github.com/slowkow/centipede.tutorial
:bug: How to use CENTIPEDE to determine if a transcription factor is bound.
https://github.com/slowkow/centipede.tutorial
bioinformatics dnase-seq enrichment rstats transcription-factors tutorial
Last synced: 2 months ago
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:bug: How to use CENTIPEDE to determine if a transcription factor is bound.
- Host: GitHub
- URL: https://github.com/slowkow/centipede.tutorial
- Owner: slowkow
- Created: 2015-07-03T17:57:24.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2018-03-18T14:39:30.000Z (almost 7 years ago)
- Last Synced: 2024-05-09T10:27:54.453Z (8 months ago)
- Topics: bioinformatics, dnase-seq, enrichment, rstats, transcription-factors, tutorial
- Language: R
- Homepage: https://slowkow.github.io/CENTIPEDE.tutorial
- Size: 3.76 MB
- Stars: 25
- Watchers: 4
- Forks: 13
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
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README
# CENTIPEDE Tutorial
> CENTIPEDE fits a bayesian hierarchical mixture model to learn TF-specific
> distribution of experimental data on a particular cell-type for a set of
> candidate binding sites described by a motif.This is a practical tutorial for running [CENTIPEDE] with [DNase-Seq] data. It
explains how to prepare the data and how to run the analysis. The goal is to
predict if a putative transcription factor binding site is actually bound or
not. For details about the statistical models underlying the methods, please
see ([Pique-Regi, et al. 2011][1]).[CENTIPEDE]: http://centipede.uchicago.edu/
[DNase-Seq]: https://en.wikipedia.org/wiki/DNase-Seq
[1]: http://genome.cshlp.org/content/21/3/447Read the tutorial online or download the PDF:
-
- [centipede-tutorial.pdf][2][2]: https://github.com/slowkow/CENTIPEDE.tutorial/raw/master/vignettes/centipede-tutorial.pdf
This repository has functions to ease the use of CENTIPEDE:
- `centipede_data()` converts data to the format required for CENTIPEDE.
- `parse_region()` parses a string like "chr1:123-456".
- `read_bedGraph()` reads a bedGraph file with 4 columns: chrom, start, end, score.
- `read_fimo()` reads a text file output by FIMO and selects sites that meet a
significance threshold.I also provide example data that you can use to follow the tutorial:
- `cen` is a list with two items:
- `cen$mat` is a matrix of read-start counts for 3,337 genomic regions.
- `cen$regions` is a dataframe describing those regions.
- `site_cons` is a vector with mean conservation scores for the 3,337 regions,
computed across 100 vertebrates.# Installation
Install CENTIPEDE by running this in your shell (not within an R session):
```bash
wget http://download.r-forge.r-project.org/src/contrib/CENTIPEDE_1.2.tar.gz
R CMD INSTALL CENTIPEDE_1.2.tar.gz
```Next, install the tutorial package:
```r
# This command didn't work for me.
# install.packages("CENTIPEDE", repos="http://R-Forge.R-project.org")install.packages("devtools")
devtools::install_github("slowkow/CENTIPEDE.tutorial")
```