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Biostat Software

Biostatistics and bioinformatics software

The Biostatistics core at BSWRI has developed novel statistical software for biostatistics and bioinformatics research. We aim to provide the biomedical community with free tools covering broad research areas, including statistical methodologies, high-throughput data analysis, computational biology, and systems biology.

PEACH: Pareto Enrichment Analysis for Combining Heterogeneous datasets

PEACH is a "meta" gene set analysis tool developed based on principles of Pareto dominance. It is designed to combine gene set analysis p-values from multiple transcriptome datasets (e.g., microarray and RNA-Seq). The novel Pareto method for p-value combination allows PEACH to properly model heterogeneity and correlation in Omics datasets.

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Cerina: systematic circRNA functional annotation based on integrative analysis of ceRNA interactions

The Cerina application was developed as a resource for researchers to infer circRNA functions under the competing endogenous RNA (ceRNA) framework. Paired circRNA, linear RNA, and miRNA expression data across 11 human tissues from ENCODE were analyzed and integrated using Pareto optimality to rank circRNA-miRNA and miRNA-linear RNA interactions. These rankings are the driving force behind the Cerina methodology and many of the figures/tables users will encounter in the app.

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Drug connectivity mapping with Dr. Insight

Dr. Insight provides a novel systematic connectivity mapping method to connect drugs (compounds) in CMap database with query data (disease phenotype or new drug profile). The Dr. Insight package contains two components of drug repurposing analyses: (1) Drug identification analysis to identify drugs that may reverse the disease phenotype (negative connectivity) or have similar functions with a query drug (positive connectivity); (2) Pathway analysis reveals drug mechanism of action at the pathway and gene level.

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Citation: Jinyan Chan, Xuan Wang, Jacob A Turner, Nicole E Baldwin, Jinghua Gu, Breaking the paradigm: Dr Insight empowers signature-free, enhanced drug repurposing, Bioinformatics, Volume 35, Issue 16, 15 August 2019, Pages 2818–2826, https://doi.org/10.1093/bioinformatics/btz006

Phantom: Pareto front based statistical tool for detecting heterogeneity in gene sets and biological modules from time-course data.

The Phantom package is designed to investigate the heterogeneous gene sets in time-course data. There are two different modes of Phantom analysis: Individual gene set mode and batch-run mode.

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Citation: Jinghua Gu, Xuan Wang, Jinyan Chan, Nicole E Baldwin, Jacob A Turner, Phantom: investigating heterogeneous gene sets in time-course data, Bioinformatics, Volume 33, Issue 18, 15 September 2017, Pages 2957–2959, https://doi.org/10.1093/bioinformatics/btx348

Q-Gen: quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariates

Q-Gen is an extension to the gene set analysis method of QuSAGE, which allows for linear mixed models to be applied appropriately within a gene set analysis framework. It provides GSA an added layer of flexibility that was not currently available. This flexibility allows for more appropriate statistical modeling of complex data structures that are inherent to many microarray study designs and can provide more sensitivity.

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Citation: Turner, J.A., Bolen, C.R. & Blankenship, D.M. Quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariates. BMC Bioinformatics 16, 272 (2015). https://doi.org/10.1186/s12859-015-0707-9

BART: bio-statistical analysis reporting Tool

BART is a web-based application designed for researchers to interactively explore results from analyzed high-throughput Omics data. The tool walks users through the entire analysis workflow: sample level summary statistics, unsupervised hierarchical clustering and heatmaps, differential gene expression analysis, and visualization of Q-Gen gene set results. An R package, genBart, was developed to allow users to create a results file that can be uploaded into BART for exploration.

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