ls-snp.icm.jhu.edu
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Karchin Lab Johns Hopkins University
http://karchinlab.org/people.html
The William R. Brody Faculty Scholar, Johns Hopkins University. Institute for Computational Medicine, Department of Biomedical Engineering, Department of Oncology. About the Karchin Lab. Dave Masica, Ph.D. Department of Biomedical Engineering. Institute for Computational Medicine. Department of Biomedical Engineering. Institute for Computational Medicine. Department of Biomedical Engineering. Institute for Computational Medicine. Department of Biomedical Engineering. Institute for Computational Medicine.
Karchin Lab Johns Hopkins University POSE
http://karchinlab.org/apps/appPose.html
POSE @ Karchin lab. POSE (Phenotype-optimized Sequence Ensembles). Is a supervised learning method that predicts the functional significance of missense mutations in a specific protein. Current release is POSE 0.60, last updated on 01/12/2015. POSE software is intended for those with substantial bioinformatics and Python expertise. POSE is free for non-commercial use. Commercial users should contact the Johns Hopkins Technology Transfer office. Documentation for the developer.
Karchin Lab Johns Hopkins University SNVBox
http://karchinlab.org/apps/appSnvBox.html
SNVBox @ Karchin lab. SNVBox is intended for those with substantial bioinformatics and Linux system expertise and access to a large-memory Linux server. It is free for non-commercial use. For more details please refer to our Software License. Commercial users should contact the Johns Hopkins Technology Transfer office. SNVBox can be used independently of CHASM and VEST software, however these tools use SNVBox as a source of predictive features, and SNVBox currently shares a Wiki site with them.
Karchin Lab Johns Hopkins University
http://karchinlab.org/publications.html
Tokheim C, Papdopoulis N, Kinzler KW, Vogelstein B, Karchin R (2016) Evaluating the evaluation of cancer driver genes. J Am Med Inform Assoc Jun 21 pii: ocw069. doi: 10.1093/jamia/ocw069. [Epub ahead of print]. Mascia DL, Karchin R (2016) Towards increasing the clinical relevance of in silico methods to predict pathogenic missense variants. PLoS Computational Biology. May 12;12(5):e1004725. Cancer Research. Apr. 28.pii: canres.3190.2015. [Epub ahead of print]. Douville C, Masica DL, Stenson PD, Cooper DN...
Karchin Lab Johns Hopkins University SCHISM
http://karchinlab.org/apps/appSchism.html
SCHISM @ Karchin lab. SCHISM (SubClonal Hierarchy Inference from Somatic Mutations). Is a computational framework that reconstructs tumor subcolonal phylogenies using somatic mutation cellularities in patient's tumor sample(s). SCHISM combines information about somatic mutation cellularity (aka mutation cancer cell fraction) across all tumor sample(s) available from a patient in a hypothesis testing framework to identify the statistical support for the lineage relationship between each pair of mutations ...
Karchin Lab Johns Hopkins University VEST
http://karchinlab.org/apps/appVest.html
VEST @ Karchin lab. VEST (Variant Effect Scoring Tool). Is a machine learning method that predicts the functional significance of missense mutations observed through genome sequencing, allowing mutations to be prioritized in subsequent functional studies, based on the probability that they impair protein activity. It is free for non-commercial use. For more details please refer to our Software License. Commercial users should contact the Johns Hopkins Technology Transfer office. Documentation for the user.
Karchin Lab Johns Hopkins University POSE
http://karchinlab.org/apps/appMoca.html
MOCA @ Karchin lab. MOCA (Multivariate Organization of Combinatorial Alterations). Is a non-parametric algorithm to discover constellations of dichotomous features that predict a phenotype of interest with high sensitivity and specficity. Current release is MOCA 0.75, last updated on 02/04/2014. MOCA software is intended for those with substantial bioinformatics and Python expertise. MOCA is free for non-commercial use. Commercial users should contact the Johns Hopkins Technology Transfer office.
Karchin Lab Johns Hopkins University SCHISM
http://karchinlab.org/apps/appClump.html
CLUMP @ Karchin lab. CLUMP (CLustering by Mutation Position). Is a method that performs unsupervised clustering of amino acid residue positions where variants occur, without any prior knowledge of their functional importance. CLUMP is free for non-commercial use. For more details please refer to our Software License. Commercial users should contact the Johns Hopkins Technology Transfer office. Current release is CLUMP.1.0.0, last updated on 04/26/2015. CLUMP-1.0.0.tar.gz. Documentation for the user.
Karchin Lab Johns Hopkins University BOMP
http://karchinlab.org/apps/appBomp.html
BOMP @ Karchin lab. BOMP (Burden or Mutation Position gene scoring tool). Software uses a novel hybrid likelihood model to identify phenotype-associated genes from sequencing data in case/control study designs. BOMP runs on Java = 1.6.0 Current release is BOMP 1.0. last updated on 01/23/2013. BOMP is free for non-commercial use. Commercial users should contact the Johns Hopkins Technology Transfer office. Documentation for the user. Download BOMP jar file here. R) How is BOMP different from VT and SKAT?
Karchin Lab Johns Hopkins University
http://karchinlab.org/datasets.html
Most requested datasets from our publications. If the dataset you are interested in is not listed here, contact Rachel Karchin karchin at jhu dot edu. Functional Impact of missense variants in BRCA1 predicted by supervised learning. PLoS Comput Biol. 2007 Feb 16;3(2):e26. Extreme phenotype yeast mutants in TP53 from Kato et al. (PNAS 2003). BRCA1 BRCT domain variants with transactivation assay labels. BRCA1 BRCT domain variants of undetermined significance in Breast Information Core (BIC) database.
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