CHASM statistics

info info

Citations per year

Number of citations per year for the bioinformatics software tool CHASM
info

Tool usage distribution map

info info

Associated diseases

info

Popular tool citations

chevron_left Variant effect prediction Driver mutation prioritization chevron_right
Want to access the full stats & trends on this tool?

Protocols

CHASM specifications

Information


Unique identifier OMICS_00127
Name CHASM
Alternative names Cancer-specific High-throughput Annotation of Somatic Mutations, CHASM/SNV-Box, CHASMplus
Software type Toolkit/Suite
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++, Python, R, Shell (Bash)
Database management system MySQL
Computer skills Advanced
Version 3.0
Stability Stable
Maintained Yes

Taxon


  • Primates
    • Homo sapiens

Versioning


No version available

Documentation


Maintainers


  • person_outline Rachel Karchin
  • person_outline Rachel Karchin

Publications for Cancer-specific High-throughput Annotation of Somatic Mutations

CHASM citations

 (15)
library_books

NIPS, a 3D network integrated predictor of deleterious protein SAPs, and its application in cancer prognosis

2018
Sci Rep
PMCID: 5902451
PMID: 29662108
DOI: 10.1038/s41598-018-24286-2

[…] tion, protein structural information is also helpful. PolyPhen-2 is a prominent tool that uses both sequence- and structure-based features in a naïve Bayes classification,. As a cancer-specific tool, CHASM (cancer-specific high-throughput annotation of somatic mutations) is a major machine-learning approach employing a random forest algorithm and was trained using 49 predictive features, including […]

call_split

Novel putative drivers revealed by targeted exome sequencing of advanced solid tumors

2018
PLoS One
PMCID: 5865730
PMID: 29570743
DOI: 10.1371/journal.pone.0194790
call_split See protocol

[…] nfidentiality. Variants were manually re-validated individually against HG-19 and then evaluated for a potential resulting cancer driver phenotype. Missense mutations were scored with two algorithms, CHASM and FATHMM, which are considered reliable predictors [, ]. Cancer-specific High-throughput Annotation of Somatic Mutations (CHASM) is a computational method based on a Random Forest classifier t […]

library_books

Dualistic Role of BARD1 in Cancer

2017
Genes
PMCID: 5748693
PMID: 29292755
DOI: 10.3390/genes8120375

[…] been included in the list of Cancer Gene Census in COSMIC database (http://cancer.sanger.ac.uk/census.). Here we have analyzed all somatic mutations of BARD1 deposited in COSMIC database by using the Cancer-specific High-throughput Annotation of Somatic Mutations (CHASM) [] tool to distinguish passenger variation events from driver ones across a cohort of tumors and the Variant Effect Scoring Tool […]

library_books

High confidence assessment of functional impact of human mitochondrial non synonymous genome variations by APOGEE

2017
PLoS Comput Biol
PMCID: 5501658
PMID: 28640805
DOI: 10.1371/journal.pcbi.1005628

[…] shold of 12 as harmful, as suggested by the authors. Variants were submitted to CADD in VCF-like data format. We further retrieved predictions from CRAVAT [], both for mendelian (VEST) [] and cancer (CHASM) [] diseases. Input variants were specified as Ensembl Transcript IDs and amino acid substitutions, using the one-letter encoding. It responded to our query with pairs of p-values and FDRs, one […]

library_books

iCAGES: integrated CAncer GEnome Score for comprehensively prioritizing driver genes in personal cancer genomes

2016
Genome Med
PMCID: 5180414
PMID: 28007024
DOI: 10.1186/s13073-016-0390-0

[…] analysis. Some batch analysis tools prioritize genes, such as MutSigCV [], MuSiC [], and Youn-Simon [], while others prioritize different kinds of mutations. For example, computational tools such as CHASM [], Mutation Assessor [], and FATHMM (for cancer) [] prioritize point-coding mutations, whereas FunSeq2 [] prioritizes non-coding mutations. While these tools paved the way for cancer driver pri […]

library_books

Genomic characterization of pediatric T cell acute lymphoblastic leukemia reveals novel recurrent driver mutations

2016
Oncotarget
PMCID: 5323170
PMID: 27602765
DOI: 10.18632/oncotarget.11796

[…] en 0.447 and 0.909 were predicted as possibly damaging (P) while a score > 0.909 was considered as damaging. Mutations with a MutationTaster score > 0.9 were also considered as damaging. Finally, for CHASM classification we used the Blood-Lymphocyte training set and a Benjamini and Hochberg's adjusted false discovery rate (FDR) ≤ 0.20, to prioritize mutations based on their predicted driver potent […]


Want to access the full list of citations?
CHASM institution(s)
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Oncology, Johns Hopkins University, Baltimore, MD, USA
CHASM funding source(s)
Supported by the National Cancer Institute (NCI) Grant F31CA200266 and NCI Grant U24CA204817.

CHASM reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review CHASM