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PIGEON: a pipeline for GEO
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INSTALL
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Pigeon is a Python 3 script that requires the following programs:
- Bowtie 2
- RSEM
- Samtools
- STAR
These programs do not need to be in the $PATH, as their binary path can be defined in a configuration file.
However, sort (GNU coreutils) and gzip are expected to be in the $PATH, as they are installed on most UNIX-based systems.
Two C programs have to be compiled. Use the make command in the utils/ directory to generate the binaries.
You will also need to generate aligners indexes to align FASTQ files. Please refer to the aligners manual to know how to generate indexes.
CONFIGURATION
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Pigeon needs a configuration file to run. This file contains :
- paths to binaries (e.g. Bowtie2)
- Pigeon API connection details
- working/output directories
- alignment/processing details
An empty config.ini file can be found in this directory.
RUNNING PIGEON
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Run Pigeon with the pigeon.py script.
Required options:
- c FILE path the configuration file
- d DATATYPES one or more data types; available data types are ChIP, HiC, RNA;
this option defines which data sets are going to be processed
Ohter options:
- i FILE JSON file containing the data sets to process; do not use the API
- a ASSEMBLIES genome assemblies to process
--download INT number of workers that download SRA files (default: 1)
--extract INT number of workers that extract FASTQ files from SRA files (default: 1)
--align INT number of workers that align FASTQ files (default: 1)
--merge INT number of workers that merge BED files (default: 1)
--analyze INT number of workers that analyze merged BED files (default: 1)
-m, --maxmem INT buffer size for sorting (in Mb)
--threads-aln number of threads that each alignment worker is allowed to use (default: 1)
--threads-alz number of threads that each analyze worker is allowed to use (default: 1)
WORKERS
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There are five types of worker.
1. Download: use wget to download a remote SRA file.
2. Extract: use the SRA fastq-dump to extract FASTQ files from an SRA file.
3. Align: use Bowtie2 or STAR to align sequences against a reference genome.
4. Merge: merge and sort data sets
5. Analyze: run, if implemented, analysis programs on data sets.
For RNA-seq data sets, RSEM is run to calculare the gene expression.
For ChIP-seq and Hi-C data sets, nothing is run.