PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification.

ABSTRACT: Features extraction methods, such as k-mer-based methods, have recently made up a significant role in classifying and analyzing approaches for metagenomics data. But, they are challenged by various bottlenecks, such as performance limitations, high memory consumption, and computational overhead. To deal with these challenges, we developed an innovative features extraction and sequence profiling method for DNA/RNA sequences, called PC-mer, taking advantage of the physicochemical properties of nucleotides. PC-mer in comparison with the k-mer profiling methods provides a considerable memory usage reduction by a factor of 2k while improving the metagenomics classification performance, for both machine learning-based and computational-based methods, at the various levels and also archives speed

SUBMITTER: Akbari Rokn Abadi S 

PROVIDER: S-EPMC11293629 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature