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1.4-1 2015-03-17 11 weekly downloads
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1.3-0 2012-08-29 11 weekly downloads
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README 2015-03-17 3.7 kB 11 weekly downloads
ChIP-Seq Project ============================================================================ The ChIP-seq software provides methods for the analysis of ChIP-seq data and other types of mass genome annotation data. Giovanna Ambrosini EPFL SV/ISREC GR-BUCHER Rel: 1.4-1 - 17.03.2015 - A few bug fixes in the chipcor program Rel: 1.4 - 07.01.2015 - ChIP-seq tools read from stdin as well - Add compactsga, counts_filter, and featreplace to main programs - Upgrade bed2sga.pl and sga2fps.pl tools Rel: 1.3 - 29-08-2012 - Correct a bug in the chippart program - Upgrade auxiliary tools Rel: 1.2 - 17-12-2010 - Correct a bug in the chippeak program Rel: 1.1 - 09-04-2009 - Update Man pages - Add auxiliary tools Rel: 1.0 - 11-11-2008 - Initial Release DESCRIPTION OF THE TOOLS ---------------------------------------------------------------------------- We propose a set of useful tools performing common ChIP-Seq data analysis tasks, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. These tools exist as stand-alone programs and perform the following tasks: 1. Positional correlation (chipcor), 2. Tag centering (chipcenter), 3. Signal peaks detection (chippeak), 4. Identification of signal-enriched regions (chippart), 5. Feature extraction tool. The programs use their own compact format for ChIP-Seq data representation called SGA (Simplified Genome Annotation). SGA is a single-line-oriented and tab-delimited format with the following five obligatory fields: 1. Sequence name (Char String), 2. Feature (Char String), 3. Sequence Position (Integer), 4. Strand (+/- or 0), 5. Tag Counts (Integer). Any number of additional fields may be added containing application-specific information. SGA files represent genome-wide tag count distributions for one ore more features. The 'feature' field (identified by field 2) is used to identify the molecular species targeted by antibody of a ChIP-seq experiment. Sequences are identified by NCBI/RefSeq chromosome ids, which are assembly specific in order to prevent mixing of different assemblies. Tag counts represent the number of tag reads that have been mapped to a specific position in the genome. Input features may be ChIP-Seq tag positions, peaks found by ChIP-peak, or any type of genome annotation that can be mapped to a single base on a chromosome. An example of SGA-formatted file is shown here below: NC_000001.9 H3K4me3 4794 + 1 NC_000001.9 H3K4me3 6090 + 1 NC_000001.9 H3K4me3 6099 + 1 NC_000001.9 H3K4me3 6655 + 1 NC_000001.9 H3K4me3 18453 - 1 NC_000001.9 H3K4me3 19285 + 1 NC_000001.9 H3K4me3 44529 + 1 NC_000001.9 H3K4me3 46333 + 1 NC_000001.9 H3K4me3 46349 - 1 NC_000001.9 H3K4me3 52929 + 1 NC_000001.9 H3K4me3 59412 + 1 ... Chip-Seq programs require SGA intput files to be sorted by sequence name, position, and strand. WEB SITE ---------------------------------------------------------------------------- ChIP-Seq has a web interface which is freely available at: http://ccg.vital-it.ch/chipseq/ PROGRAM INSTALLATION ============================================================================ Untar the file containing the source code (e.g. chip-seq.3.1-0.tar.gz). For code compilation a suitable makefile is provided. To create the executable files, type: make To delete the excutable files and all the object files from the directory, type: make clean To install the man pages you should have root permissions and type: make man
Source: README, updated 2015-03-17