Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies

Continued fraction expansions of rational expressions with irreducible denominators in characteristic 2

AbstractGiven any irreducible polynomial q of degree n over the field with two elements, there is a sequence of polynomials pn, pn…1,…, p0 with pn = q, with p0 = 1, with the degree of pi equal to i, and with pi ≡ pi…2 (mod pi−1). In other words, given an irreducible q there is a p, relatively prime to q, with degree one less and such that the degrees of the remainders in Euclid's Algorithm for the greatest common divisor of p and q go down by exactly 1 at each step

The Limitations of Simple Gene Set Enrichment Analysis Assuming Gene Independence

Since its first publication in 2003, the Gene Set Enrichment Analysis (GSEA) method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach, using a one sample t test score to assess enrichment and ignoring gene-gene correlations was proposed by Irizarry et al. 2009 as a serious contender. The argument criticizes GSEA's nonparametric nature and its use of an empirical null distribution as unnecessary and hard to compute. We refute these claims by careful consideration of the assumptions of the simplified method and its results, including a comparison with GSEA's on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored due to the significant variance inflation they produced on the enrichment scores and should be taken into account when estimating gene set enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods.Comment: Submitted to Statistical Methods in Medical Researc

Cytoscape: the network visualization tool for GenomeSpace workflows.

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013

ISMB 2008 Toronto

The International Society for Computational Biology (ISCB) presents the Sixteenth International Conference on Intelligent Systems for Molecular Biology (ISMB 2008), to be held in Toronto, Canada, July 19–23, 2008. Now in the final phases of scheduling selected presentations, demonstrations, and posters, the organizers are preparing what will likely be recognized as the premier conference on computational biology in 2008. ISMB 2008 (http://www.iscb.org/ismb2008/) will follow the road paved by the ISMB/ ECCB 2007 (http://www.iscb.org/ ismbeccb2007/) in Vienna in the attempt to specifically encourage increased participation from previously under-represented disciplines of computational biology. This conference will feature the best of the computer and life sciences through a variety of core sessions running in multiple parallel tracks, along with single-tracked Keynote Presentations, posters on display throughout the duration of the conference, and an extensive commercial exposition. The first day (July 18) of the meeting is reserved for two-day Special Interest Group (SIG) and Satellite meetings, the second day (July 19) runs SIGs for the first time in parallel with Tutorials and the Student Council Symposium, and for the first time two SIGs are running in parallel with the main ISMB meeting (July 20–23)Other Research Uni

Sashimi plots: Quantitative visualization of RNA sequencing read alignments

We introduce Sashimi plots, a quantitative multi-sample visualization of mRNA sequencing reads aligned to gene annotations. Sashimi plots are made using alignments (stored in the SAM/BAM format) and gene model annotations (in GFF format), which can be custom-made by the user or obtained from databases such as Ensembl or UCSC. We describe two implementations of Sashimi plots: (1) a stand-alone command line implementation aimed at making customizable publication quality figures, and (2) an implementation built into the Integrated Genome Viewer (IGV) browser, which enables rapid and dynamic creation of Sashimi plots for any genomic region of interest, suitable for exploratory analysis of alternatively spliced regions of the transcriptome. Isoform expression estimates outputted by the MISO program can be optionally plotted along with Sashimi plots. Sashimi plots can be used to quickly screen differentially spliced exons along genomic regions of interest and can be used in publication quality figures. The Sashimi plot software and documentation is available from: http://genes.mit.edu/burgelab/miso/docs/sashimi.htmlComment: 2 figure

Subclass Mapping: Identifying Common Subtypes in Independent Disease Data Sets

Whole genome expression profiles are widely used to discover molecular subtypes of diseases. A remaining challenge is to identify the correspondence or commonality of subtypes found in multiple, independent data sets generated on various platforms. While model-based supervised learning is often used to make these connections, the models can be biased to the training data set and thus miss inherent, relevant substructure in the test data. Here we describe an unsupervised subclass mapping method (SubMap), which reveals common subtypes between independent data sets. The subtypes within a data set can be determined by unsupervised clustering or given by predetermined phenotypes before applying SubMap. We define a measure of correspondence for subtypes and evaluate its significance building on our previous work on gene set enrichment analysis. The strength of the SubMap method is that it does not impose the structure of one data set upon another, but rather uses a bi-directional approach to highlight the common substructures in both. We show how this method can reveal the correspondence between several cancer-related data sets. Notably, it identifies common subtypes of breast cancer associated with estrogen receptor status, and a subgroup of lymphoma patients who share similar survival patterns, thus improving the accuracy of a clinical outcome predictor

An accessible GenePattern notebook for the copy number variation analysis of Illumina Infinium DNA methylation arrays [version 1; peer review: 2 approved]

Illumina Infinium DNA methylation arrays are a cost-effective technology to measure DNA methylation at CpG sites genome-wide and across cohorts of normal and cancer samples. While copy number alterations are commonly inferred from array-CGH, SNP arrays, or whole-genome DNA sequencing, Illumina Infinium DNA methylation arrays have been shown to detect copy number alterations at comparable sensitivity. Here we present an accessible, interactive GenePattern notebook for the analysis of copy number variation using Illumina Infinium DNA methylation arrays. The notebook provides a graphical user interface to a workflow using the R/Bioconductor packages minfi and conumee. The environment allows analysis to be performed without the installation of the R software environment, the packages and dependencies, and without the need to write or manipulate code

A Genome-Wide siRNA Screen in Mammalian Cells for Regulators of S6 Phosphorylation

mTOR complex1, the major regulator of mRNA translation in all eukaryotic cells, is strongly activated in most cancers. We performed a genome-wide RNAi screen in a human cancer cell line, seeking genes that regulate S6 phosphorylation, readout of mTORC1 activity. Applying a stringent selection, we retrieved nearly 600 genes wherein at least two RNAis gave significant reduction in S6-P. This cohort contains known regulators of mTOR complex 1 and is significantly enriched in genes whose depletion affects the proliferation/viability of the large set of cancer cell lines in the Achilles database in a manner paralleling that caused by mTOR depletion. We next examined the effect of RNAi pools directed at 534 of these gene products on S6-P in TSC1 null mouse embryo fibroblasts. 76 RNAis reduced S6 phosphorylation significantly in 2 or 3 replicates. Surprisingly, among this cohort of genes the only elements previously associated with the maintenance of mTORC1 activity are two subunits of the vacuolar ATPase and the CUL4 subunit DDB1. RNAi against a second set of 84 targets reduced S6-P in only one of three replicates. However, an indication that this group also bears attention is the presence of rpS6KB1 itself, Rac1 and MAP4K3, a protein kinase that supports amino acid signaling to rpS6KB1. The finding that S6 phosphorylation requires a previously unidentified, functionally diverse cohort of genes that participate in fundamental cellular processes such as mRNA translation, RNA processing, DNA repair and metabolism suggests the operation of feedback pathways in the regulation of mTORC1 operating through novel mechanisms