Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.

Recurrent targets of aberrant somatic hypermutation in lymphoma.

Somatic hypermutation (SHM) in the variable region of immunoglobulin genes (IGV) naturally occurs in a narrow window of B cell development to provide high-affinity antibodies. However, SHM can also aberrantly target proto-oncogenes and cause genome instability. The role of aberrant SHM (aSHM) has been widely studied in various non-Hodgkin's lymphoma particularly in diffuse large B-cell lymphoma (DLBCL). Although, it has been speculated that aSHM targets a wide range of genome loci so far only twelve genes have been identified as targets of aSHM through the targeted sequencing of selected genes. A genome-wide study aiming at identifying a comprehensive set of aSHM targets recurrently occurring in DLBCL has not been previously undertaken. Here, we present a comprehensive assessment of the somatic hypermutated genes in DLBCL identified through an analysis of genomic and transcriptome data derived from 40 DLBCL patients. Our analysis verifies that there are indeed many genes that are recurrently affected by aSHM. In particular, we have identified 32 novel targets that show same or higher level of aSHM activity than genes previously reported. Amongst these novel targets, 22 genes showed a significant correlation between mRNA abundance and aSHM.

B cells with high side scatter parameter by flow cytometry correlate with inferior survival in diffuse large B-cell lymphoma.

Despite advances in the understanding of diffuse large B-cell lymphoma (DLBCL) biology, only the clinically based International Prognostic Index (IPI) is used routinely for risk stratification at diagnosis. To find novel prognostic markers, we analyzed flow cytometric data from 229 diagnostic DLBCL samples using an automated multiparameter data analysis approach developed in our laboratory. By using the developed automated data analysis pipeline, we identified 71 of 229 cases as having more than 35% B cells with a high side scatter (SSC) profile, a parameter reflecting internal cellular complexity. This high SSC B-cell feature was associated with inferior overall and progression-free survival (P = .001 and P = .01, respectively) and remained a significant predictor of overall survival in multivariate Cox regression analysis (IPI, P = .001; high SSC, P = .004; rituximab, P = .53). This study suggests that high SSC among B cells may serve as a useful biomarker to identify patients with DLBCL at high risk for relapse. This is of particular interest because this biomarker is readily available in most clinical laboratories without significant alteration to existing routine diagnostic strategies or incurring additional costs.

Human variation database: an open-source database template for genomic discovery.

MOTIVATION: Current public variation databases are based upon collaboratively pooling data into a single database with a single interface available to the public. This gives little control to the collaborator to mine the database and requires that they freely share their data with the owners of the repository. We aim to provide an alternative mechanism: providing the source code and application programming interface (API) of a database, enabling researchers to set up local versions without investing heavily in the development of the resource and allowing for confidential information to remain secure. RESULTS: We describe an open-source database that can be installed easily at any research facility for the storage and analysis of thousands of next-generation sequencing variations. This database is built using PostgreSQL 8.4 (The PostgreSQL Global Development Group. postgres 8.4: http://www.postgresql.org) and provides a novel method for collating and searching across the reported results from thousands of next-generation sequence samples, as well as rapidly accessing vital information on the origin of the samples. The schema of the database makes rapid and insightful queries simple and enables easy annotation of novel or known genetic variations. A modular and cross-platform Java API is provided to perform common functions, such as generation of standard experimental reports and graphical summaries of modifications to genes. Included libraries allow adopters of the database to quickly develop their own queries. AVAILABILITY: The software is available for download through the Vancouver Short Read Analysis Package on Sourceforge, http://vancouvershortr.sourceforge.net. Instructions for use and deployment are provided on the accompanying wiki pages. CONTACT: afejes@bcgsc.ca.

Per-channel basis normalization methods for flow cytometry data.

Between-sample variation in high-throughput flow cytometry data poses a significant challenge for analysis of large-scale data sets, such as those derived from multicenter clinical trials. It is often hard to match biologically relevant cell populations across samples because of technical variation in sample acquisition and instrumentation differences. Thus, normalization of data is a critical step before analysis, particularly in large-scale data sets from clinical trials, where group-specific differences may be subtle and patient-to-patient variation common. We have developed two normalization methods that remove technical between-sample variation by aligning prominent features (landmarks) in the raw data on a per-channel basis. These algorithms were tested on two independent flow cytometry data sets by comparing manually gated data, either individually for each sample or using static gating templates, before and after normalization. Our results show a marked improvement in the overlap between manual and static gating when the data are normalized, thereby facilitating the use of automated analyses on large flow cytometry data sets. Such automated analyses are essential for high-throughput flow cytometry.

Inverse protein folding in 3D hexagonal prism lattice under HPC model.

The inverse protein folding problem is that of designing an amino acid sequence which has a prescribed native protein fold. This problem arises in drug design where a particular structure is necessary to ensure proper protein-protein interactions. Previously, tubular structures for a three-dimensional (3D) hexagonal prism lattice were introduced and their stability was formally proved for simple instances under the hydrophobic-polar (HP) model of Dill. In this article, we generalize the design of tubular structures to allow for much larger variety of designable structures by allowing branching of tubes. Our generalized design could be used to roughly approximate given 3D shapes in the considered lattice. Although the generalized tubular structures are not stable under the HP model, we can prove that a simple instance of generalized tubular structures is structurally stable (all native folds have the designed shape) under a refined version of the HP model, called the HPC model. We conjecture that there is a way to choose which hydrophobic monomers are cysteines in all generalized tubular structures such that the designed proteins are structurally stable under the HPC model.

Stable structure-approximating inverse protein folding in 2D hydrophobic-polar-cysteine (HPC) model.

The inverse protein folding problem is that of designing an amino acid sequence which folds into a prescribed conformation/structure. This problem arises in drug design where a particular structure is necessary to ensure proper protein-protein interactions. Gupta et al. (2005) introduced a design in the two-dimensional (2D) hydrophobic-polar (HP) model of Dill that can be used to approximate any given (2D) shape. They conjectured that the protein sequences of their design are stable but only proved the stability for an infinite class of very basic structures. We introduce a refinement of the HP model, in which the cysteine and non-cysteine hydrophobic monomers are distinguished and SS-bridges, which two cysteines can form, are taken into account in the energy function. We call this model the HPC model. We consider a subclass of linear structures designed in Gupta et al. (2005) which is rich enough to approximate (although more coarsely) any given structure. We refine these structures for the HPC model by setting approximately a half of H amino acids to cysteine ones and call them snake structures. We first prove that the proteins of the snake structures are stable under the strong HPC model in which we make an additional assumption that non-cysteine amino acids act as cysteine ones, i.e., they can form their own bridges to reduce the energy. Then we consider a subclass of snake structures called wave structures that can still approximate any given shape and prove that their proteins are stable under the proper HPC model. This partially confirms the conjecture stated in Gupta et al. (2005). To prove the above results we developed a computational tool, called 2DHPSolver, which we used to perform large case analysis required for the proofs. We conjecture that the proteins of snake structures are stable under the proper HPC model.