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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Bibliographic Details
Published in:BMC bioinformatics Vol. 18; no. 1; pp. 442 - 8
Main Authors: Ferlaino, Michael, Rogers, Mark F., Shihab, Hashem A., Mort, Matthew, Cooper, David N., Gaunt, Tom R., Campbell, Colin
Format: Journal Article
Language:English
Published: London BioMed Central 06.10.2017
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-017-1862-y