Genome modeling system: A knowledge management platform for genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms

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Circos plot of HCC1395 tumor/normal comparison.

<p>Circos is a popular tool for summarizing genomic events in a tumor genome. This is just one of many automatically generated visualizations made possible by the GMS. In this example, the WGS, exome and RNA-seq data for HCC1395 are displayed in several tracks along with additional visualizations illustrating individual events. Moving inwards, SNVs and Indels are plotted on the outermost track, then highly expressed genes, CNVs, and finally chromosomal translocations at the center. For events predicted to affect protein coding genes, additional plots are auto-generated to display the mutation position relative to protein domains and previously reported mutations from the Cosmic database, as illustrated in the topmost plot. Moving clockwise, a screenshot of IGV demonstrates one of the somatic deletions identified. IGV XML sessions are automatically generated to allow rapid manual review of all predicted events. Next, a histogram illustrates the expression of a single highly expressed gene relative to the distribution of expression for all genes. Then, a CNV plot is shown for an amplified portion of one chromosome. Finally, the coverage and supporting reads for a chromosomal translocation are depicted.</p