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通过基线耐受转化提高癌症突变功能影响的预测。

Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation.

机构信息

Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biomèdica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003 Barcelona, Spain.

Research Programme on Biomedical Informatics - GRIB. Universitat Pompeu Fabra - UPF, Hospital del Mar Medical Research Institute - IMIM. Parc de Recerca Biomèdica de Barcelona (PRBB). Dr. Aiguader, 88, E-08003 Barcelona, Spain ; Institució Catalana de Recerca i Estudis Avançats (ICREA). Passeig Lluís Companys, 23, E-08010, Barcelona, Spain.

出版信息

Genome Med. 2012 Nov 26;4(11):89. doi: 10.1186/gm390. eCollection 2012.

DOI:10.1186/gm390
PMID:23181723
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4064314/
Abstract

High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.

摘要

高通量优先排序致癌突变（驱动突变）是癌症基因组项目的一个关键挑战，这是由于在肿瘤中检测到的体细胞变体数量众多。该任务的一个重要步骤是评估肿瘤体细胞突变的功能影响。为此已经采用了许多计算方法，尽管大多数方法最初是为了将与疾病相关的非同义单核苷酸变异（nsSNV）与多态性区分开来而开发的。我们的新方法，转化的癌症功能影响评分（transFIC），通过考虑基因对功能变体的基线容忍度，改进了肿瘤 nsSNV 功能影响的评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/2ab926e525bc/gm390-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/26b48c0a6705/gm390-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/cb057fb2792f/gm390-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/8e6d46889933/gm390-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/2ab926e525bc/gm390-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/26b48c0a6705/gm390-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/cb057fb2792f/gm390-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/8e6d46889933/gm390-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6124/4064314/2ab926e525bc/gm390-4.jpg

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