WExT – Weighted Exact Test for Mutually Exclusive Mutations in Cancer

WExT

:: DESCRIPTION

WExT (Weighted Exclusivity Test) is computes a statistical score for mutually exclusive mutations using per gene, per sample weights.

::DEVELOPER

Raphael Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

WExT

:: MORE INFORMATION

Citation:

Leiserson MD, Reyna MA, Raphael BJ.
A weighted exact test for mutually exclusive mutations in cancer.
Bioinformatics. 2016 Sep 1;32(17):i736-i745. doi: 10.1093/bioinformatics/btw462. PMID: 27587696; PMCID: PMC5013919.

Dendrix 0.3 – Discovery of Mutated Driver Pathways in Cancer

Dendrix 0.3

:: DESCRIPTION

Dendrix (De novo Driver Exclusivity) is an algorithm for discovery of mutated driver pathways in cancer using only mutation data. It finds sets of genes, domains, or nucleotides whose mutations exhibit both high coverage and high exclusivity in the analyzed samples.

::DEVELOPER

Raphael Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 Dendrix

:: MORE INFORMATION

Citation:

F. Vandin, E. Upfal, B.J. Raphael. (2011)
De novo Discovery of Mutated Driver Pathways in Cancer.
Genome Res. 2011 Jul 11

GDISC – Gene-Drug Interactions for Survival in Cancer

GDISC

:: DESCRIPTION

GDISC presents Gene-Drug Interactions for Survival in Cancer identified from integrative omic and survival analysis of TCGA data.

::DEVELOPER

Peng Qiu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Spainhour JCG, Lim J, Qiu P.
GDISC: a web portal for integrative analysis of gene-drug interaction for survival in cancer.
Bioinformatics. 2017 May 1;33(9):1426-1428. doi: 10.1093/bioinformatics/btw830. PMID: 28453687; PMCID: PMC5859986.

Zodiac – Depiction of Genetic Interactions in Cancer by integrating TCGA data

Zodiac

:: DESCRIPTION

Zodiac is a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood model derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes “Prior interaction map + TCGA data → Posterior interaction map.”

::DEVELOPER

Yuan Ji Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

NO

:: MORE INFORMATION

Citation

Zhu Y, Xu Y, Helseth DL Jr, Gulukota K, Yang S, Pesce LL, Mitra R, Müller P, Sengupta S, Guo W, Silverstein JC, Foster I, Parsad N, White KP, Ji Y.
Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data.
J Natl Cancer Inst. 2015 May 8;107(8):djv129. doi: 10.1093/jnci/djv129. PMID: 25956356; PMCID: PMC4554190.

Q-IHC 2 – Cancer Imaging Analysis tools

Q-IHC 2

:: DESCRIPTION

Q-IHC (Quantum IHC) is a set of cancer imaging analysis tools to assess Quantum Dots (QD) and Immunohistochemistry (IHC) based molecular and tissue images for various cancers types.

::DEVELOPER

Bio-MIBLab

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows
  • MatLab

:: DOWNLOAD

 Q-IHC

:: MORE INFORMATION

Citation:

Xing Y, Chaudry Q, Shen C, Kong KY, Zhau HE, Chung LW, Petros JA, O.Regan RM, Yezhelyev MV, Simons JW, *Wang MD, and *Nie SM
Bioconjugated quantum dots for multiplexed and quantitative immunohistochemistry.
Nat Protoc. 2007 May 3; 2(5):1152-65.

PINCAGE – Probabilistic INTegration of CAncer GEnomics data

PINCAGE

:: DESCRIPTION

PINCAGE is a method that uses probabilistic integration of cancer genomics data for combined evaluation of RNA-seq gene expression and 450K array DNA methylation measurements of promoters as well as gene bodies.

::DEVELOPER

PINCAGE team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

  PINCAGE

:: MORE INFORMATION

Citation

PINCAGE: Probabilistic integration of cancer genomics data for perturbed gene identification and sample classification.
Świtnicki MP, Juul M, Madsen T, Sørensen KD, Pedersen JS.
Bioinformatics. 2016 Jan 6. pii: btv758.

LILY – Detection of Super-enhancers in Cancer Samples

LILY

:: DESCRIPTION

LILY is a pipeline for detection of super-enhancers using H3K27ac ChIP-seq data, which includes explicit correction for copy number variation inherent to cancer samples.

::DEVELOPER

Boeva lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX/ Windows
  • R

:: DOWNLOAD

LILY

:: MORE INFORMATION

Citation

Boeva V, et al.
Heterogeneity of neuroblastoma cell identity defined by transcriptional circuitries.
Nat Genet. 2017 Sep;49(9):1408-1413. doi: 10.1038/ng.3921. Epub 2017 Jul 24. PMID: 28740262.

SV-Bay – Detection of Structural Variants in Cancer Mate-pair and Paired-end data

SV-Bay

:: DESCRIPTION

SV-Bay is a computational method to detect structural variants from whole genome sequencing mate-pair or paired-end data using a probabilistic Bayesian approach.

::DEVELOPER

Boeva lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • Python

:: DOWNLOAD

 SV-Bay

:: MORE INFORMATION

Citation

SV-Bay: structural variant detection in cancer genomes using a Bayesian approach with correction for GC-content and read map-pability.
Iakovishina D, Janoueix-Lerosey I, Barillot E, Regnier M, Boeva V.
Bioinformatics. 2016 Jan 6. pii: btv751.

HMCan 1.39 / HMCan-diff – Detection of (Differential) Chromatin Modifications in ChIP-seq data

HMCan 1.39 / HMCan-diff

:: DESCRIPTION

HMCan is Hidden Markov Model based tool that is developed to detect histone modification in cancer ChIP-seq data. It applies three correction steps to the data: copy number correction, GC bias correction and noise level correction.

HMCan-diff is a method designed specially to detect changes of histone modifications in ChIP-seq cancer samples or between a cancer sample and a normal control. HMCan-diff explicitly corrects for copy number bias as well as for other ChIP-seq technical biases such as GC-content and mappability biases, and variable levels of signal-to-noise in different samples. HMCan-diff uses a three state hidden Markov model to detect regions of differential histone modifications.

::DEVELOPER

Boeva lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 HMCan , HMCan-diff

:: MORE INFORMATION

Citation

Ashoor H, Louis-Brennetot C, Janoueix-Lerosey I, Bajic VB, Boeva V.
HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics.
Nucleic Acids Res. 2017 May 5;45(8):e58. doi: 10.1093/nar/gkw1319. PMID: 28053124; PMCID: PMC5416852.

Bioinformatics. 2013 Dec 1;29(23):2979-86. doi: 10.1093/bioinformatics/btt524. Epub 2013 Sep 9.
HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data.
Ashoor H1, Hérault A, Kamoun A, Radvanyi F, Bajic VB, Barillot E, Boeva V.

VIC – Variant Interpretation for Cancer

VIC

:: DESCRIPTION

VIC is a Computational Tool for Assessing Clinical Impacts of Somatic Variants Following the AMP-ASCO-CAP 2017 Guidelines

::DEVELOPER

Wang Genomics Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

VIC

:: MORE INFORMATION

Citation

He MM, Li Q, Yan M, Cao H, Hu Y, He KY, Cao K, Li MM, Wang K.
Variant Interpretation for Cancer (VIC): a computational tool for assessing clinical impacts of somatic variants.
Genome Medicine, 11:53, 2019