An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome

Background Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is cr...

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Vydané v:	BMC bioinformatics Ročník 18; číslo 1; s. 442 - 8
Hlavní autori:	Ferlaino, Michael, Rogers, Mark F., Shihab, Hashem A., Mort, Matthew, Cooper, David N., Gaunt, Tom R., Campbell, Colin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 06.10.2017 BioMed Central Ltd Springer Nature B.V BMC
Predmet:	Algorithms Analysis Annotations Bioinformatics Biomedical and Life Sciences Computational Biology - methods Computational Biology/Bioinformatics Computer Appl. in Life Sciences Consortia Deoxyribonucleic acid DNA DNA, Intergenic - genetics Genetics, Population Genome, Human Genomes Genomics Human genome Humans INDEL Mutation - genetics Indels Internet Life Sciences Methods Microarrays Mutation Non-coding genome Nucleotide sequence Phenotype Physiological aspects Reproducibility of Results Research Article Results and data ROC Curve Servers Software State of the art Support vector machines Variant prioritisation United Kingdom Support vector machines Indels Variant prioritisation Non-coding genome
ISSN:	1471-2105, 1471-2105
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Shrnutí:	Background Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. Results We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk . Conclusions FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	1471-2105 1471-2105
DOI:	10.1186/s12859-017-1862-y