2024/01/01 by Jorge Miguel Silva, Armando J. Pinho, Diogo Pratas · 2 voices · 1 citation
Biochemistry, Genetics and Molecular Biology · Medicine · #Fractal and DNA sequence analysis #Genomics and Phylogenetic Studies #SARS-CoV-2 and COVID-19 Research
paper · doi:10.1093/gigascience/giae086
openalex publication_date 2024/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/11
BACKGROUND: Most viral genome sequences generated during the latest pandemic have presented new challenges for computational analysis. Analyzing millions of viral genomes in multi-FASTA format is computationally demanding, especially when using alignment-based methods. Most existing methods are not designed to handle such large datasets, often requiring the analysis to be divided into smaller parts to obtain results using available computational resources. FINDINGS: We introduce AltaiR, a toolkit for analyzing multiple sequences in multi-FASTA format using exclusively alignment-free methodologies. AltaiR enables the identification of singularity and similarity patterns within sequences and computes static and temporal dynamics without restrictions on the number or size of input sequences. It automatically filters low-quality, biased, or deviant data. We demonstrate AltaiR's capabilities by analyzing more than 1.5 million full severe acute respiratory virus coronavirus 2 sequences, revealing interesting observations regarding viral genome characteristics over time, such as shifts in nucleotide composition, decreases in average Kolmogorov sequence complexity, and the evolution of the smallest sequences not found in the human host. CONCLUSIONS: AltaiR can identify temporal characteristics and trends in large numbers of sequences, making it ideal for scenarios involving endemic or epidemic outbreaks with vast amounts of available sequence data. Implemented in C with multithreading and methodological optimizations, AltaiR is computationally efficient, flexible, and dependency-free. It accepts any sequence in FASTA format, including amino acid sequences. The complete toolkit is freely available at https://github.com/cobilab/altair.