PISAD: reference-free intraspecies sample anomalies detection tool based on k-mer counting.

Abstract

Background: Genomic sequencing research often requires the simultaneous analysis of heterogeneous data types across single or multiple individuals, introducing a substantial risk of sample swaps (e.g., labeling errors). Existing methods primarily rely on reference information, requiring the preselection of informative variant sites with a population allele frequency around 0.5, which may be insufficient or unavailable for nonmodel organisms. As research expands to encompass a growing number of new species, a robust quality control tool will become increasingly important.

Finds: We developed PISAD (Phased Intraspecies Sample Anomalies Detection), a tool for validating sample identities in whole-genome sequencing (WGS) data without requiring reference information. It uses a 2-stage approach: first, it performs rapid, reference-free single nucleotide polymorphism (SNP) calling on low-error-rate data from the target individual to create a variant sketch; then, it assesses the concordance of other samples on this sketch to verify relationships. We assessed the performance and efficiency of PISAD on Homo sapiens, Bos taurus, Gallus gallus, Arctia plantaginis, and Pyrus species.

Conclusions: Our evaluation showed that PISAD achieves a lower data coverage requirement (0.5×) compared to the reference-based tool ntsm and is broadly applicable to multiple diploid species.