ngsTools

ngsTools performs population-genetics analyses of next-generation sequencing (NGS) short-read data by modeling statistical uncertainty arising from low sequencing depth and from reads that are de novo assembled or mapped to reference genomes.

Key Features:

• Statistical Uncertainty Management: Models and accounts for statistical uncertainties at low sequencing depth, including random sampling errors of homologous base pairs in heterozygotes and sequencing or alignment inaccuracies.
• Probabilistic Methods: Implements probabilistic methods that allow inference from low-quality or low-coverage NGS data.
• Independence from SNP/Genotype Calling: Operates without relying on single-nucleotide polymorphism (SNP) or genotype calls, enabling analysis when such calls are unreliable due to low coverage.

Scientific Applications:

• Population Genetics Analyses: Enables analysis of genetic variation to investigate evolutionary dynamics, population structure, and genetic diversity from NGS datasets with low sequencing depth without conventional SNP/genotype calling.

Methodology:

Programs are implemented in C/C++.