CHIP-RNA-SEQPRO specifications

Unique identifier:
OMICS_07344
Interface:
Command line interface
Output data:
A Matrix file summarizing across all samples compared, variable counts and attribute data useful for graphs or statistical analysis, a detailed report of all of the annotated RNA editing sites identified in the analysis, all of the known and novel transcripts overlapping the target genes of interest and annotated according to their estimated FPKM abundance and variant files processed for RNA editing annotations.
Programming languages:
Python
Computer skills:
Advanced
Maintained:
No
Software type:
Package/Module
Restrictions to use:
None
Operating system:
Unix/Linux
License:
GNU General Public License version 2.0
Requirements:
glob, collections, csv, pprint, shutil, fnmatch, pandas, numpy, itertools, operator

versioning

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CHIP-RNA-SEQPRO distribution

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CHIP-RNA-SEQPRO support

Documentation

Maintainer

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Credits

Institution(s)

Division of Biomedical Statistics and Informatics, Mayo Clinic, Scottsdale, AZ, USA; Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA; Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA; Translational Program Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA; Division of Hematology and Oncology, Mayo Clinic, Scottsdale, AZ, USA; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA; Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA; Division of Hematology and Oncology, Mayo Clinic, Jacksonville, FL, USA; Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

Funding source(s)

Supported by funding from the ASCO Young Investigator Award from the Kidney Cancer Association, the Action to Cure Kidney Cancer Organization, the MD Anderson Hematology Oncology Fellowship, a Mayo Clinic CR5 grant, Mayo Clinic Center for Individualized Medicine Epigenomics Translational Program, a Kathryn H. and Roger Penske Career Development Award to Support Medical Research and in part by the Mayo Clinic Center for Individualized Medicine Epigenomics Translational Program.

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