CD-MAWS: An Alignment-Free Phylogeny Estimation Method Using Cosine Distance on Minimal Absent Word Sets

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Traditional multiple sequence alignment is computationally intensive.
• Increasing sequencing data necessitates faster, accurate alignment-free methods.
• Alignment-free methods analyze genomic data by extracting numerical features.

Purpose of the Study:

• Introduce CD-MAWS, a novel alignment-free distance measure.
• Utilize Minimal Absent Words (MAW) for sequence representation.
• Develop a computationally inexpensive sequence analysis tool.

Main Methods:

• Construct composition vectors using Minimal Absent Words (MAW).
• Define CD-MAWS as the cosine of the angle between these vectors.
• Benchmark CD-MAWS on established datasets (Fish mtDNA, E.coli, Plants, Shigella, Yersinia).

Main Results:

• CD-MAWS demonstrated strong performance on AFProject datasets.
• Applied to mammal mtDNA, bacterial, and viral genomes, it resolved phylogenetic relationships effectively.
• Performance was comparable or superior to state-of-the-art alignment-free methods (Mash, Skmer, Co-phylog, kSNP3).

Conclusions:

• CD-MAWS offers a computationally efficient and accurate approach for sequence analysis.
• The method effectively captures sequence characteristics using Minimal Absent Words.
• CD-MAWS shows promise for phylogenetic analysis across various genomic datasets.