Back

Frequency Chaos Game Representation - Singular Value Decomposition for Alignment-Free Phylogenetic Analysis

A, V.; Mangsuli, D.; Sinha, N.; Ramdas, S.

2025-04-22 bioinformatics
10.1101/2025.04.16.649090 bioRxiv
Show abstract

This paper introduces "SVD-FCGR," a scalable and efficient frame-work for phylogenetic analysis using Singular Value Decomposition (SVD) on Frequency Chaos Game Representation (FCGR). Unlike traditional MSA techniques, SVD-FCGR handles large datasets with lower computational complexity. It supports both genome-wide and gene-specific analyses, as demonstrated with datasets of Japanese Encephalitis Virus (JEV), Hepatitis B Virus (HBV), Human Immunodeficiency Virus(HIV-1), and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). For COVID-19, gene-level analysis of surface glycoprotein highlighted mutations affecting viral adaptability, while the envelope gene remained conserved. The method produced detailed phylogenetic trees, surpassing tools like MEGA in resolution and scalability. Validation from the AF Project ranked it 11th among alignment-free methods, confirming its reliability and adaptability.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.