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InVEx specifications

Information


Unique identifier OMICS_00151
Name InVEx
Alternative name Introns Vs Exons
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data A reference genome file.
Input format FASTA
Operating system Unix/Linux, Mac OS
Programming languages Python
Computer skills Advanced
Stability Stable
Requirements
NumPy, SciPy, Cython, PyFasta
Maintained No

Versioning


No version available

Maintainer


This tool is not available anymore.

Publication for Introns Vs Exons

InVEx citations

 (8)
library_books

Precision medicine driven by cancer systems biology

2017
PMCID: 5385204
PMID: 28265786
DOI: 10.1007/s10555-017-9662-4

[…] atic mutation calls (average rate of 18/Mbp; many individual specimens with rates above 1000/Mbp) than all other TCGA genomics studies combined [, ] (Fig. ). The bioinformatics tool Introns Vs Exons (InVEx) [], designed to identify driver genes by taking the specific background mutation rate per patient and per gene into consideration, is currently the gold standard in melanoma genomics. Genome-wi […]

library_books

Molecular characterisation of cutaneous melanoma: creating a framework for targeted and immune therapies

2016
Br J Cancer
PMCID: 4947706
PMID: 27336610
DOI: 10.1038/bjc.2016.195

[…] least 10% of the 121 melanomas sequenced – many of which were not expressed in melanocytes and melanoma cell lines. To address this problem, sophisticated statistical tools were developed, including InVEx, which uses sequencing data from intronic and untranslated regions (UTRs) to infer gene-specific mutation burdens (). Using this tool, genes that were found to be significantly mutated included […]

library_books

Somatic Copy Number Amplification and Hyperactivating Somatic Mutations of EZH2 Correlate With DNA Methylation and Drive Epigenetic Silencing of Genes Involved in Tumor Suppression and Immune Responses in Melanoma

2016
PMCID: 5005314
PMID: 26936398
DOI: 10.1016/j.neo.2016.01.003

[…] ng after cohort selection, mapping of human genome and patient specific somatic references, assessment of recurrence, evolutionary conversation, basal mutation rate based on frequency of mutations of introns vs exons, and structural analysis . TCGA patients showed recurring mutations TCGA-BF-A1PV-01 EZH2(Y641N), TCGA-D9-A1JW-06 EZH2(Y641F), and TCGA-EE-A3AF-06 EZH2(Y641N). EZH2 Y641 mutant melanom […]

library_books

Integrated genomics approach to identify biologically relevant alterations in fewer samples

2015
BMC Genomics
PMCID: 4647579
PMID: 26572163
DOI: 10.1186/s12864-015-2138-4

[…] SCC including CDKN2A, TP53, PIK3CA, NOTCH1, HRAS, FBXW7, PTEN, NFE2L2, FAT1, and CASP8 [–]. These landmark studies apply elegant statistical methodologies like MutSig [], Genome MuSiC [], Intogen [], InVEx [], ActiveDrive [] and GISTIC [] in identifying significantly altered genes across large sample cohorts by comparing rate of mutations of each gene with background mutation rate to determine an […]

library_books

Novel and rare functional genomic variants in multiple autoimmune syndrome and Sjögren’s syndrome

2015
J Transl Med
PMCID: 4450850
PMID: 26031516
DOI: 10.1186/s12967-015-0525-x

[…] ments or SREs). In brief, position weight matrices are constructed for the predicted sequence motifs, in order to measure the level of nucleotide sequence conservation, as well as their enrichment in introns vs. exons []. Sequences that have more enriched matrix scores in a given intronic region compared to other locations in the gene’s exons and introns are considered as candidate splicing regula […]

library_books

Cancer systems biology of TCGA SKCM: Efficient detection of genomic drivers in melanoma

2015
Sci Rep
PMCID: 4298731
PMID: 25600636
DOI: 10.1038/srep07857

[…] ructural rearrangement detection and mutation rate calculation. From 220,031 exonic mutations, Mutsig 2.0 produces a list of significantly mutated genes, covariates.txt. iv) The permutation algorithm InVEx 1.0.1, Intron vs Exon, was employed to efficiently model the somatic mutation rate among genes to identify the genes that most frequently harbor non-silent mutations. InVEx 1.0.1 permutes coding […]

Citations

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InVEx institution(s)
The Broad Institute of Harvard and MIT, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Biochemistry and Molecular Biology and Center for Biomolecular Structure and Function, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Institute for Applied Cancer Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, Boston, MA, USA; Division of Genetics, Brigham and Women’s Hospital, Boston, MA, USA; Department of Surgery, Massachusetts General Hospital, Boston, MA, USA; Department of Molecular Oncology, John Wayne Cancer Institute, Santa Monica, CA, USA; Melanoma Department, John Wayne Cancer Institute, Santa Monica, CA, USA; Division of Immunology, Allergy and Infectious Diseases, Department of Dermatology, Medical University of Vienna and CeMM-Research, Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria; Department of Dermatology, University Hospital Essen, Essen, Germany; Whitehead Institute for Biomedical Research, Cambridge Center, Cambridge, MA, USA
InVEx funding source(s)
Supported by the NHGRI Large Scale Sequencing Program; grant U54 HG003067; the Melanoma Research Alliance; The University of Texas MD Anderson Cancer Center Melanoma Specialized Programs of Research Excellence and Melanoma Informatics, Tissue Resource, and Pathology (core grant P50 CA93459); and the NCI Support Grant (CA-16672).

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