Abstract
BackgroundSmall 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.ResultsWe 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.ConclusionsFATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.
Highlights
Small insertions and deletions have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations
We considered variants recorded in individuals of African ancestry since European and Asian populations have been subject to bottlenecks which might have resulted in pathogenic indels with relatively high minor allele frequencies (MAFs) – see e.g. [7]
The vast majority of genetic alterations lie outside the exome, there is a lack of methods designed to predict the impact of indels throughout the whole non– coding genome
Summary
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. The advent of generation sequencing technologies has led to a rapid increase in identified genetic variation, including single nucleotide variants (SNVs), copy number variants, insertions and deletions (indels), in addition to larger scale DNA rearrangements. Interpretation of the functional impact of identified variants is of increasing importance This has led to the development of accurate methods for assessing genomic tolerance and predictive techniques for discriminating between harmful (pathogenic) and neutral mutations [1,2,3,4]. The vast majority of models for predicting the functional impact of indels have been restricted to their effect in the human exome – see e.g. [5,6,7]
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