PBAP

PBAP processes pedigree-based dense genetic marker data to perform quality control, select marker subsets that reduce linkage disequilibrium for linkage analysis, and prepare input files for MORGAN.


Key Features:

  • Quality Control: Performs rigorous quality control on pedigree-derived genotype and sequence data to ensure data integrity for downstream analyses.
  • Marker Selection: Selects flexible subsets of markers from dense SNP panels and sequence data, including rare variants, to facilitate linkage analysis while reducing computational demands.
  • Linkage Disequilibrium Reduction: Minimizes linkage disequilibrium between SNPs through marker subset selection to improve suitability for linkage methods.
  • File Preparation for MORGAN: Formats output files specifically for compatibility with MORGAN to support analysis of small and large human pedigrees.
  • Support for Sequence Data and Rare Variants: Handles dense marker panels derived from sequence data and incorporates rare variant considerations in marker selection.

Scientific Applications:

  • Pedigree-based linkage analysis: Facilitates linkage analysis of human traits by providing QC, LD-aware marker selection, and MORGAN-formatted inputs.
  • Small pedigree studies using sequence data: Supports analyses of rare variants and dense marker panels in smaller family-based studies.
  • Preprocessing for MORGAN analyses: Supplies preprocessed and formatted datasets ready for downstream analysis with MORGAN on pedigrees of varying sizes.

Methodology:

Computational steps include quality control of genotype and sequence data, selection of marker subsets to minimize linkage disequilibrium for linkage analysis, and formatting of output files for MORGAN.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
R, Perl, C
Added:
8/3/2017
Last Updated:
12/10/2018

Operations

Publications

Nato AQ, et al. PBAP: a pipeline for file processing and quality control of pedigree data with dense genetic markers. Bioinformatics. 2015; 31:3790-8. doi: 10.1093/bioinformatics/btv444

PMID: 26231429

Documentation

Links