Boekel, Jorrit, Chilton, John, Cooke, Ira, Horvatovich, Peter, Jagtap, Pratik, Kall, Lukas, Lehtiö, Janne, Lukasse, Pieter, Moerland, Perry, and Griffin, Timothy (2015) Multi-omic data analysis using Galaxy. Nature Biotechnology, 33. pp. 137-139.

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Abstract

[Extract] Comprehensive multi-omic data acquisition has become a reality, largely driven by the availability of high-throughput sequencing technologies for genomes and transcriptomes1, and high-resolution mass spectrometry (MS)2,3 for the in-depth characterization of proteomes and metabolomes. Integrating genomic and proteomic data enables proteogenomic 4 and metaproteomic approaches 4, whereas integrating metabolomic and transcriptomic or proteomic data links biochemical activity profiles to expressed genes and proteins 6. Despite the potential for new discoveries, integrated analysis of raw multi-omic data is an often overlooked challenge 7, demanding the use of disparate software programs and requiring computational resources beyond the capacity of most biological research laboratories. For these reasons, multi-omic approaches remain out of reach for many. Here, we describe how Galaxy 8 can be used as one solution to this problem.

Item ID:	43793
Item Type:	Article (Short Note)
ISSN:	1087-0156
Funders:	Netherlands Bioinformatics Centre, Netherlands Proteomic Centre (NPC)
Projects and Grants:	NPC GM WP3.2
Date Deposited:	19 May 2016 02:28
FoR Codes:	06 BIOLOGICAL SCIENCES > 0601 Biochemistry and Cell Biology > 060102 Bioinformatics @ 100%
SEO Codes:	97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 50% 97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 50%
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