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Journal ArticleDOI

MutationTaster evaluates disease-causing potential of sequence alterations

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TLDR
MutationTaster allows the efficient filtering of NGS data for alterations with high disease-causing potential and provides Perl scripts that can process data from all major platforms (Roche 454, Illumina Genome Analyzer and ABI SOLiD).
Abstract
(simple_aae) or at alterations causing complex changes in the amino acid sequence (complex_aae). To train the classifier, we generated a dataset with all available and suitable common polymorphisms and known diseasecausing mutations extracted from common databases and the literature. We cross-validated the classifier five times including all three prediction models and obtained an overall accuracy of 91.1 ± 0.1%. We also compared MutationTaster with similar applications (Panther3, Pmut4, PolyPhen and PolyPhen-2 (ref. 5) and ‘screening for non-acceptable polymorphisms’ (SNAP)6) and analyzed the identical 1,000 disease-linked mutations and 1,000 polymorphisms with all programs. For this comparison, we used only alterations causing single amino acid exchanges. MutationTaster performed best in terms of accuracy and speed (Table 1). A description of all training and validation procedures and detailed statistics are available in Supplementary Methods. MutationTaster can be used via an intuitive web interface to analyze single mutations as well as in batch mode. To streamline and to standardize the analysis of NGS data, we provide Perl scripts that can process data from all major platforms (Roche 454, Illumina Genome Analyzer and ABI SOLiD). MutationTaster hence allows the efficient filtering of NGS data for alterations with high disease-causing potential (see Supplementary Methods for an example). Present limitations of the software comprise its inability to analyze insertion-deletions greater than 12 base pairs and alterations spanning an intron-exon border. Also, analysis of non-exonic alterations is restricted to Kozak consensus sequence, splice sites and poly(A) signal. We will add tests for other sequence motifs in the near future. MutationTaster is available at http://www.mutationtaster.org/.

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Citations
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Journal ArticleDOI

Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.

TL;DR: Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends thatclinical molecular genetic testing should be performed in a Clinical Laboratory Improvement Amendments–approved laboratory, with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or the equivalent.
Journal ArticleDOI

MutationTaster2: mutation prediction for the deep-sequencing age

TL;DR: This method takes advantage of the high hybridization efficiency of FISH and the fact that base-pair resolution is usually not needed to uniquely identify a transcript, and will enable the transcriptome to be directly imaged at single-cell resolution in complex samples such as brain tissue.
Journal ArticleDOI

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Nilah M. Ioannidis, +45 more
TL;DR: This work developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, LRT, GERP, SiPhy, phyloP, and phastCons.
Journal ArticleDOI

The genetic landscape of high-risk neuroblastoma

Trevor J. Pugh, +76 more
- 01 Mar 2013 - 
TL;DR: The authors reported a low median exonic mutation frequency of 0.60 per Mb (0.48 nonsilent) and notably few recurrently mutated genes in high-risk neuroblastoma.
References
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Journal ArticleDOI

A method and server for predicting damaging missense mutations.

TL;DR: A new method and the corresponding software tool, PolyPhen-2, which is different from the early tool polyPhen1 in the set of predictive features, alignment pipeline, and the method of classification is presented and performance, as presented by its receiver operating characteristic curves, was consistently superior.
Journal ArticleDOI

Idiot's Bayes—Not So Stupid After All?

TL;DR: In this article, the authors examine the evidence for this, both empirical, as observed in real data applications, and theoretical, summarising explanations for why this simple rule might be effective.
Journal ArticleDOI

The PANTHER database of protein families, subfamilies, functions and pathways.

TL;DR: PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise, allowing more accurate association with function, as well as inference of amino acids important for functional specificity.
Journal ArticleDOI

SNAP: predict effect of non-synonymous polymorphisms on function

TL;DR: SNAP (screening for non-acceptable polymorphisms), a neural network-based method for the prediction of the functional effects of non-synonymous SNPs, introduced, introducing a well-calibrated measure for the reliability of each prediction.
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