An accessible proteogenomics informatics resource for cancer researchers

Chambers, Matthew C., Jagtop, Pratik D., Johnson, James E., McGowan, Thomas, Kumar, Praveen, Onsongo, Getiria, Guerrero, Candace R., Barsnes, Harald, Vaudel, Marc, Martens, Lennart, Grüning, Björn, Cooke, Ira, Heydarian, Mohammad, Reddy, Karen L., and Griffin, Timothy J. (2017) An accessible proteogenomics informatics resource for cancer researchers. Cancer Research, 77 (21). E43-E46.

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Abstract

Proteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry-based proteomics data to directly identify expressed, variant protein sequences that may have functional roles in cancer. This approach is computationally intensive, requiring integration of disparate software tools into sophisticated workflows, challenging its adoption by nonexpert, bench scientists. To address this need, we have developed an extensible, Galaxy-based resource aimed at providing more researchers access to, and training in, proteogenomic informatics. Our resource brings together software from several leading research groups to address two foundational aspects of proteogenomics: (i) generation of customized, annotated protein sequence databases from RNA-Seq data; and (ii) accurate matching of tandem mass spectrometry data to putative variants, followed by filtering to confirm their novelty. Directions for accessing software tools and workflows, along with instructional documentation, can be found at z.umn.edu/canresgithub. (C) 2017 AACR.

Item ID: 51625
Item Type: Article (Research - C1)
ISSN: 1538-7445
Funders: Ghent University (GU), Bergen Research Foundation, Research Council of Norway, BMBF, NCI, National Science Foundation, USA (NSF)
Projects and Grants: GU concentrated research action BOF12/GOA/014, BMBF grant 031 A538A RBC, NCI ITCR grant 1U24CA199347, NSF grant 1458524
Date Deposited: 22 Nov 2017 07:55
FoR Codes: 06 BIOLOGICAL SCIENCES > 0601 Biochemistry and Cell Biology > 060102 Bioinformatics @ 100%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920102 Cancer and Related Disorders @ 100%
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