PySNV for complex intra-host variation detection.

Publication date: Feb 29, 2024

Intra-host variants refer to genetic variations or mutations that occur within an individual host organism. These variants are typically studied in the context of viruses, bacteria, or other pathogens to understand the evolution of pathogens. Moreover, intra-host variants are also explored in the field of tumor biology and mitochondrial biology to characterize somatic mutations and inherited heteroplasmic mutations. Intra-host variants can involve long insertions, deletions, and combinations of different mutation types, which poses challenges in their identification. The performance of current methods in detecting of complex intra-host variants is unknown. First, we simulated a dataset comprising ten samples with 1,869 intra-host variants involving various mutation patterns and benchmarked current variant detection software. The results indicated that though current software can detect most variants with F1-scores between 0. 76 and 0. 97, their performance in detecting long indels and low frequency variants was limited. Thus, we developed a new software, PySNV, for the detection of complex intra-host variations. On the simulated dataset, PySNV successfully detected 1,863 variant cases (F1-score: 0. 99) and exhibited the highest Pearson correlation coefficient (PCC: 0. 99) to the ground truth in predicting variant frequencies. The results demonstrated that PySNV delivered promising performance even for long indels and low frequency variants, while maintaining computational speed comparable to other methods. Finally, we tested its performance on SARS-CoV-2 replicate sequencing data and found that it reported 21% more variants compared to LoFreq, the best-performing benchmarked software, while showing higher consistency (62% over 54%) within replicates. The discrepancies mostly exist in low-depth regions and low frequency variants. https://github. com/bnuLyndon/PySNV/.

Open Access PDF

Concepts Keywords
Bacteria Complex
F1 Current
Genetic Detection
Viruses Frequency


Type Source Name
disease IDO host
disease VO Viruses
disease VO Bacteria
disease MESH tumor
drug DRUGBANK Pentaerythritol tetranitrate
disease VO frequency
drug DRUGBANK Factor IX Complex (Human)
drug DRUGBANK Coenzyme M

Original Article

(Visited 1 times, 1 visits today)