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Cited by 596

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

A survey of tools for variant analysis of next-generation genome sequencing data

Open access
Pabinger, S., Dander, A., Fischer, M., Snajder, R., Sperk, M., Efremova, M., Krabichler, B., Speicher, M. R., Zschocke, J., Trajanoski, Z.·2014·Briefings in Bioinformatics

Abstract

Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers.

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Metadata

Authors
Pabinger, S., Dander, A., Fischer, M., Snajder, R., Sperk, M., Efremova, M., Krabichler, B., Speicher, M. R., Zschocke, J., & Trajanoski, Z.
Venue
Briefings in Bioinformatics
Published
2013-01-21
Volume
15
Issue
2
Pages
256-278
ISSN
  • 1467-5463 (ISSN-L)
  • 1477-4054
OpenAlex
W2168440186
Cited by
596
References
27
FWCI
54.63
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: A survey of tools for variant analysis of next-generation genome sequencing data. https://app.cochat.ai/papers/10.1093/bib/bbs086
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Pabinger, S., Dander, A., Fischer, M., Snajder, R., Sperk, M., Efremova, M., Krabichler, B., Speicher, M. R., Zschocke, J., & Trajanoski, Z. (2014). A survey of tools for variant analysis of next-generation genome sequencing data. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbs086

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