PiCall

PiCall detects and genotypes short insertion–deletion variants (short indels) directly from aligned sequence reads to improve indel discovery and genotyping accuracy in population-scale sequencing studies.

Key Features:

• Probabilistic Approach: PiCall employs a probabilistic method to distinguish true short indel variants from sequencing errors and improve detection and genotyping accuracy.
• Context-Specific Error Correction: It leverages aligned sequence reads from multiple individuals to model and correct context-specific sequencing errors associated with indels by integrating population-level data.
• High Sensitivity and Low False Discovery Rate: On 1000 Genomes exon pilot project datasets generated with Roche 454 and Illumina platforms, PiCall demonstrated higher sensitivity and consistent indel length patterns across populations indicative of a low false discovery rate.
• General Applicability: PiCall is applicable to small-scale DNA sequence variant detection workflows in population-scale sequencing projects for comprehensive indel discovery and genotyping.

Scientific Applications:

• Genetic diversity and population evolution: PiCall enables exploration of short indel diversity and length patterns across human populations to inform studies of population evolution.
• Disease association studies: PiCall provides precise short indel genotypes to support analyses of indel contributions to disease susceptibility.
• Population-scale variant discovery: PiCall facilitates accurate short indel discovery and genotyping in large-scale human sequencing projects.

Methodology:

Uses a probabilistic calling algorithm that analyzes aligned sequence reads from multiple individuals to model context-specific sequencing errors and genotype short indels.