FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies

PLoS Comput Biol. 2016 Jun 6;12(6):e1004980. doi: 10.1371/journal.pcbi.1004980. eCollection 2016 Jun.

Abstract

In disease studies, family-based designs have become an attractive approach to analyzing next-generation sequencing (NGS) data for the identification of rare mutations enriched in families. Substantial research effort has been devoted to developing pipelines for automating sequence alignment, variant calling, and annotation. However, fewer pipelines have been designed specifically for disease studies. Most of the current analysis pipelines for family-based disease studies using NGS data focus on a specific function, such as identifying variants with Mendelian inheritance or identifying shared chromosomal regions among affected family members. Consequently, some other useful family-based analysis tools, such as imputation, linkage, and association tools, have yet to be integrated and automated. We developed FamPipe, a comprehensive analysis pipeline, which includes several family-specific analysis modules, including the identification of shared chromosomal regions among affected family members, prioritizing variants assuming a disease model, imputation of untyped variants, and linkage and association tests. We used simulation studies to compare properties of some modules implemented in FamPipe, and based on the results, we provided suggestions for the selection of modules to achieve an optimal analysis strategy. The pipeline is under the GNU GPL License and can be downloaded for free at http://fampipe.sourceforge.net.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Computer Simulation
  • Genetic Association Studies
  • Genetic Predisposition to Disease / genetics*
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Internet
  • Sequence Analysis, DNA / methods*
  • Software*

Grants and funding

This study was supported by grants from the Ministry of Science and Technology (NSC 102-2221-E-400-001-MY2 and MOST 104-2221-E-400-004-MY2) and the National Health Research Institutes (PH-105-PP-10) in Taiwan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.