44 lines
1.6 KiB
Plaintext
44 lines
1.6 KiB
Plaintext
The pyCRAC package is a collection of python scripts to analyse high
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throughput data generated by RNA-sequencing, especially of molecules
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crosslinked by UV to an immunoprecipitated protein of interest (i.e.
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data generated by CLIP or CRAC protocols).
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It can be used to remove duplicate reads,tackles directional libraries
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and reports sense and anti-sense hits.
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Included is the pipeline used for the analysis of a group of CRAC data
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sets.
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References
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Genome Biol. 2014 Jan 7;15(1):R8. doi: 10.1186/gb-2014-15-1-r8.
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PAR-CLIP data indicate that Nrd1-Nab3-dependent transcription
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termination regulates expression of hundreds of protein coding genes in
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yeast. Webb S, Hector RD, Kudla G, Granneman S.
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Nature Communications, 2017; DOI: 10.1038/s41467-017-00025-5
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Kinetic CRAC uncovers a role for Nab3 in determining gene expression
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profiles during stress. van Nues R, Schweikert G, de Leau E, Selega
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A, Langford A, Franklin R, Iosub I, Wadsworth P, Sanguinetti G,
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Granneman S.
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If you want to run the test suite after installation, see README.tests.
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Note on the Crac pipelines:
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Use the -h flag to get a detailed help menu.
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The CRAC_pipeline_PE.py script needs to be run from the folder that
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contains the fastq files
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The barcode list file should contain two tab-separated columns in which
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the first column is the barcode sequence and the second column is the
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name of the experiment
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The file containing the adapter sequences should be in the fasta format.
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The chromosome_lengths file should contain two tab-separated columns in
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which the first column has the chromosome name and the second the
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chromosome length.
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