Elementolab/ChIPseeqerReadCountMatrix
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| Available options are: | Available options are: | ||
| - | --intervals FILE file containing the peaks | + | --peakfile FILE file containing the peaks |
| --chipdirfile FILE file containing the paths to the ChIP reads folders | --chipdirfile FILE file containing the paths to the ChIP reads folders | ||
| --chrdata STR to run for organisms other that human (default is hg18), point to files: | --chrdata STR to run for organisms other that human (default is hg18), point to files: | ||
Revision as of 16:23, 29 January 2011
Back to Elementolab/ChIPseeqer_Tutorial
ChIPseeqerGetReadCountInPeaksMatrix
To run the tools directly from any folder, you need to add the $CHIPSEEQERDIR and $CHIPSEEQERDIR/SCRIPTS to your $PATH variable. Read How to set the CHIPSEEQERDIR variable.
In this analysis you can get the average or maximum reads count for each peak, across multiple ChIP-seq datasets.
The input of this script are:
- a file with peaks (option: peakfile) (i.e., typical output of ChIPseeqer)
- a file (option: chipdirfile) with a label of the CHIP-seq dataset and the whole path to the directory with the splitted reads (i.e., after running ChIPseeqerSplitReadFiles)
Example of the chipdirfile.
BCL6 /DATASETS/BCL6/CHIP Pol2_2P /DATASETS/POL2_2P/CHIP/ Pol2_5P /DATASETS/POL2_5P/CHIP BCOR /DATASETS/BCOR/CHIP/ PAX5 /DATASETS/PAX5/CHIP/
1. To run the script type the command:
ChIPseeqerGetReadCountInPeaksMatrix --peakfile=peaks.txt --chipdirfile=chipdirfile.txt --chrdata=DATA/hg18.chrdata --outfile=matrix.txt
Available options are:
--peakfile FILE file containing the peaks
--chipdirfile FILE file containing the paths to the ChIP reads folders
--chrdata STR to run for organisms other that human (default is hg18), point to files:
DATA/mm9.chrdata for mouse,
DATA/dm3.chrdata for drosophila or
DATA/sacser.chrdata for Saccharomyces cerevisiae
--outfile STR indicates the output file (provide full path)
--format STR format of the read files: sam, mit, bed, eland. Default is eland.
2. See the results.
The result will be a peaks-based matrix. Each column contains the max reads count for the corresponding ChIP-seq dataset (indicated by the column name).
For example,
Pol2_2P Pol2_5P BCL6 BCOR PAX5 chrY-57398943-57399486 2.406 1.857 8.112 1.832 1.119 chr1-2211998-2212341 0.344 0.309 23.178 0.234 0.000 chrY-57412321-57413102 1.375 0.928 5.215 1.234 0.000 chrX-13074532-13074581 0.344 0.619 18.543 0.198 0.000 chrY-57415332-57415537 0.344 0.309 3.477 3.546 0.000 chrX-12159949-12159898 0.000 0.309 4.056 4.098 1.789 chrX-12105587-12105784 0.000 0.309 6.954 1.987 4.327
