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README
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#####################################
# #
# ChIPSeq Scoring #
# #
#####################################
-- DEPENDENCIES
+ MACS 1.4
http://liulab.dfci.harvard.edu/MACS/Download
+ MACS 2
https://github.com/taoliu/MACS/downloads
+ SPP 1.10 [modified]
http://code.google.com/p/phantompeakqualtools/
+ IDR
https://sites.google.com/site/anshulkundaje/projects/idr
+ SJM 1.2.0
http://sourceforge.net/projects/hpcsjm/
+ R 2.15.1
+ SUN GRID ENGINE
-- INSTALLATION
Unpack scripts and add directory to $PYTHONPATH. Modify globals.conf
configuration file to input the particulars of your system. See wiki
(https://github.com/StanfordBioInformatics/Scoring/wiki) for details.
-- USAGE
Create control.conf and sample.conf configuration files. Sample config
files are included. Further details are available on the wiki
(https://github.com/StanfordBioInformatics/Scoring/wiki). Use the config
files as input to pipeline.py
Usage: pipeline.py [-f] [-p] [-h] [-s] [-a] [-m <email address>]
[-l <directory>] [-n <run_name>] [-c <peakcaller>] <control_config_file>
[<sample_config_file>]
Arguments:
-c, --peakcaller <peakcaller>
specify the peakcaller to be used. Current options are peakseq, macs,
macs2, spp. Defaults to macs2.
-a, --no_archive
does not archive the control and sample results.
-f, --force
forces running of pipeline, even if results already exist
-p, --print
prints the job commands, but does not dispatch them to the cluster
-d, --no_duplicates
runs cross correlation analysis assuming duplicated reads have
already been filtered out of the mapped reads. Uncommon, so
defaults to false.
-h, --help
displays this usage information and exits
-l <directory>, --log <directory>
log directory, current working directory if not specified
-n <run_name>, --name <run_name>
name for the pipeline run
-m <email_address>, --mail <email_address>
email address to send summary and result location
-s, --snap
make a call to the SNAP LIMS after completion
--filtchr <chromosome>
SPP option to ignore a chromosome during analysis. Used to fix bug that
chrs with low read counts causes SPP to fail.
--rmdups
Filter out all duplicate reads in sample read files before peakcalling. Use
when PCR amplification errors are present. (i.e., PBC value is low)
<control_config_file>
(required) configuration file for the experiment's control
<sample_config_file>
configuration file for the sample replicates in the experiment. Optional,
but in most cases this is specified.