Computational Bioinformatics and Bioimaging Laboratory (CBIL)


Internal Use


BayesDenovo: An accurate de novo transcriptome assembler using a Bayesian model

Supplementary information on BayesDenovo: BayesDenovo User Manual and BayesDenovo Package


Identifying differentially expressed isoforms using a novel joint model of RNA-seq data

Supplementary information on BayesIso: BayesIso User Manual and BayesIso Package


Inferring intracellular signaling modules by exploring pathway landscape

Supplementary information on IMPALA: IMPALA User Manual and IMPALA Package


CRNET: An efficient sampling approach to infer functional regulatory networks by integrating large-scale ChIP-seq and time-course RNA-seq data

Supplementary information on CRNET: CRNET User Manual (V2.2) and CRNET R Scripts (V2.2)


SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data

The SparseIso package is available at Click Here


DM-BLD: differential methylation detection using a hierarchical Bayesian model exploiting local dependency

Supplementary information on DM-BLD: DM-BLD User Manual (V2.0) and DM-BLD Package (V2.0)


PSSV: A novel pattern-based probabilistic approach for somatic structural variation identification

Supplementary information on PSSV: PSSV User Manual (V2.1) and PSSV Package (V2.1)


ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profiles

Supplementary information on ChIP-BIT: ChIP-BIT Manual (V2.0), ChIP-BIT Package (V2.0), PBX1_chr1.bam, and Input_chr1.bam


BMRF-Net: a software tool for identification of protein interaction subnetworks by a bagging Markov random field-based method

The BMRF-Net package is available at Click Here


CAM-2THC: Unsupervised deconvolution of two-source mixed gene expressions

Supplementary information on CAM-2THC: CAM-2THC Package


BADGE: A novel Bayesian model for accurate abundance quantification and differential analysis of RNA-seq data

Supplementary information on BADGE: BADGE Manual and BADGE Package


The CAM Software for Nonnegative Blind Source Separation in R-Java

Supplementary information on CAM R-Java: CAM R-Java Manual and CAM R-Java Package


A bagging Markov random field (BMRF) approach for PPI subnetwork identification

Supplementary information on BMRF: BMRF Manual and BMRF Package


Robust identification of transcriptional regulatory networks using a Gibbs sampler on outlier sum statistic

Supplementary information - a Gibbs sampler on outlier sum statistic (GibbsOS): GibbsOS Manual and GibbsOS Package (Version 3)


Significant Aberrations in Cancer (SAIC)

Software Information on SAIC: SAIC Manual and SAIC Package


Bayesian Analysis of Copy Number Mixtures (BACOM)


CAM-CM Software for Application Note


Convex Analysis of Mixtures and Compartment Modeling (CAM-CM)




CNSuite: A caBIG analytical tool for copy number analysis

CNSuite (Copy Number Suite) is a caBIGTM (cancer Biomedical Informatics Grid) analytical tool for gene copy number change analysis. CNSuite consists of a Fused Margin Regression (FMR) method for detecting copy number changes in a single signal profile and consensus copy number changes in population data, and two feature indexing methods for analyzing chromosomal instabilities (CIN). CNSuite is applicable to analyzing germline copy number variations (CNV) in the study of population genetics and somatic copy number alterations (CNA) in tumor genomics.

Supplementary Information: free download CNSuite software - CNSuite Software


caBIG VIsual and Statistical Data Analyzer (VISDA)

VISDA (VIsual Statistical Data Analyzer) is a caBIG analytical tool for cluster modeling, visualization, and discovery. Being statistically-principled and visually-insightful, VISDA exploits human gift for pattern recognition and allows users to discover hidden clustered data structure within high dimensional and complex biomedical data sets. The unique features of VISDA include its hybrid algorithm, robust performance, and "tree of phenotype". With global and local biomarker identification and prediction functionalities, VISDA allows users across the cancer research community to analyze their genomic/proteomic data to define new cancer subtypes based on the gene expression patterns, construct hierarchical trees of multiclass cancer phenotypic composites, or to discover the correlation between cancer statistics and risk factors.


Multi-level Support Vector Regression (ml-SVR) Analysis to Identify Condition-Specific Regulatory Networks

Supplementary Information: free download ml-SVR software - ml-SVR Package


Motif-guided Sparse Decomposition (mSD) of Gene Expression Data for Regulatory Module Identification

Supplementary Information: free download mSD software - mSD Package


Phenotype Up-regulated Gene based One Versus Rest Support Vector Machine (PUG-OVRSVM) for Multicategory Molecular Classification

Supplementary Information: free download PUG-OVRSVM software and test datasets PUG-OVRSVM Package Part 1 and PUG-OVRSVM Package Part 2, PUG-OVRSVM Package Part 3, and PUGSVM-DEPLOYMENT-WINDOWS.rar, and caBIG PUG Package


Learning Maximum Entropy Probability Models for Characterizing Multilocus Genomic Interactions

Supplementary Information: free download MECPM-SNP software and test datasets MECPM-SNP Package


Coordinative Component Analysis (COCA)

Supplementary Information on Coordinative Component Analysis (COCA): COCA Manual and COCA Package


Differential Dependence Networks (DDN and kDDN)

Supplementary Information on Differential Dependence Networks (DDN): kDDN_Update, DDN_Manual, DDN Package, and caBIG DDN Package


VIsual and Statistical Data Analyzer (VISDA)

Supplementary Information #1 on caBIG VISDA: VISDA Installation Guide

Supplementary Information #2 on caBIG VISDA: VISDA Package


SNP Simulation

Supplementary Information on SNP Simulation: SNP Simulation SNP Simulator


Tissue Heterogeneity Correction (THC)

BSS-THC Software (supported by the NIH under Grants EB000830, CA109872): BSS Demo, BSS Demo Readme, and A Tutorial on BSS-1


Cross-Phenotype Normalization (CPN)

ISN-INR-CPN Software (supported by the NIH under Grants EB000830, CA109872): CPN Tutorial, and dchipCPN Package


Optimized Multilayer Perceptrons (oMLP)

Supplementary Information on oMLP (Bioinformatics-2005-1602): Appendices of oMLP (Bioinformatics), and Appendix A1 of oMLP (Bioinformatics)





Copyright ©2004, Computational Bioinformatics and Bioimaging Laboratory (CBIL), Advanced Research Institute, Virginia Tech.

Last Updated: 02/16/2009. Suggestions/Comments - Webmaster