Pcangsd

Description

pcangsd website  

Framework for analyzing low-depth next-generation sequencing (NGS) data in heterogeneous/structured populations using principal component analysis (PCA). Population structure is inferred by estimating individual allele frequencies in an iterative approach using a truncated SVD model. The covariance matrix is estimated using the estimated individual allele frequencies as prior information for the unobserved genotypes in low-depth NGS data.

The estimated individual allele frequencies can further be used to account for population structure in other probabilistic methods. PCAngsd can perform the following analyses:

   Covariance matrix
   Admixture estimation
   Inbreeding coefficients (both per-individual and per-site)
   HWE test
   Genome-wide selection scans
   Genotype calling
   Estimate NJ tree of samples

Environment Modules

Run module spider pcangsd to find out what environment modules are available for this application.

System Variables

• HPC_PCANGSD_DIR - installation directory