Choice of transcripts and software has a large effect on variant annotation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Davis J McCarthy, Peter Humburg, Alexander Kanapin, Manuel A Rivas, Kyle Gaulton, The WGS500 Consortium, Jean-Baptiste Cazier, Peter Donnelly

ABSTRACT

BACKGROUND: Variant annotation is a crucial step in the analysis of genome sequencing data. Functional annotation results can have a strong influence on the ultimate conclusions of disease studies. Incorrect or incomplete annotations can cause researchers both to overlook potentially disease-relevant DNA variants and to dilute interesting variants in a pool of false positives. Researchers are aware of these issues in general, but the extent of the dependency of final results on the choice of transcripts and software used for annotation has not been quantified in detail. METHODS: This paper quantifies the extent of differences in annotation of 80 million variants from a whole-genome sequencing study. We compare results using the RefSeq and Ensembl transcript sets as the basis for variant annotation with the software Annovar, and also compare the results from two annotation software packages, Annovar and VEP (Ensembl's Variant Effect Predictor), when using Ensembl transcripts. RESULTS: We found only 44% agreement in annotations for putative loss-of-function variants when using the RefSeq and Ensembl transcript sets as the basis for annotation with Annovar. The rate of matching annotations for loss-of-function and nonsynonymous variants combined was 79% and for all exonic variants it was 83%. When comparing results from Annovar and VEP using Ensembl transcripts, matching annotations were seen for only 65% of loss-of-function variants and 87% of all exonic variants, with splicing variants revealed as the category with the greatest discrepancy. Using these comparisons, we characterised the types of apparent errors made by Annovar and VEP and discuss their impact on the analysis of DNA variants in genome sequencing studies. CONCLUSIONS: Variant annotation is not yet a solved problem. Choice of transcript set can have a large effect on the ultimate variant annotations obtained in a whole-genome sequencing study. Choice of annotation software can also have a substantial effect. The annotation step in the analysis of a genome sequencing study must therefore be considered carefully, and a conscious choice made as to which transcript set and software are used for annotation. More... »

PAGES

26

References to SciGraph publications

  • 2013-12. Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing in GENOME MEDICINE
  • 2014-10. Homozygous microdeletion of exon 5 in ZNF277 in a girl with specific language impairment in EUROPEAN JOURNAL OF HUMAN GENETICS
  • 2010-11. The GENCODE human gene set in GENOME BIOLOGY
  • 2006-08. GENCODE: producing a reference annotation for ENCODE in GENOME BIOLOGY
  • 2010-08. MutationTaster evaluates disease-causing potential of sequence alterations in NATURE METHODS
  • 2013-02. Germline mutations affecting the proofreading domains of POLE and POLD1 predispose to colorectal adenomas and carcinomas in NATURE GENETICS
  • 2010-10-28. A map of human genome variation from population-scale sequencing in NATURE
  • 2006-05. Intron gain and loss in segmentally duplicated genes in rice in GENOME BIOLOGY
  • 2013-12. Comparing a few SNP calling algorithms using low-coverage sequencing data in BMC BIOINFORMATICS
  • 2011-07. The GENCODE exome: sequencing the complete human exome in EUROPEAN JOURNAL OF HUMAN GENETICS
  • 2013-03. Mutations in TCF12, encoding a basic helix-loop-helix partner of TWIST1, are a frequent cause of coronal craniosynostosis in NATURE GENETICS
  • 2012-09. Landscape of transcription in human cells in NATURE
  • 2009-07. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm in NATURE PROTOCOLS
  • 2005-05. The Sequence Ontology: a tool for the unification of genome annotations in GENOME BIOLOGY
  • 2013-12. Benchmarking short sequence mapping tools in BMC BIOINFORMATICS
  • 2012-09. An integrated encyclopedia of DNA elements in the human genome in NATURE
  • 2012-05. Performance comparison of benchtop high-throughput sequencing platforms in NATURE BIOTECHNOLOGY
  • 2011-02. Charting a course for genomic medicine from base pairs to bedside in NATURE
  • 2010-04. A method and server for predicting damaging missense mutations in NATURE METHODS
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    URI

    http://scigraph.springernature.com/pub.10.1186/gm543

    DOI

    http://dx.doi.org/10.1186/gm543

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039764104

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/24944579


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