It would be an unimaginable scenario, a world without our all time favorite BLAST (Basic Local Alignment Search Tool). No matter which field we are working on, Molecular biology, Microbiology, Cell Biology, etc, there comes a time when we need to perform BLAST. However, Not writing much about BLAST (you all know about it anyway!), I would like to share with you a little jist about CLAST.
CLAST (CUDA implemented large-scale alignment search tool) enables analyses of millions of reads and thousands of reference genome sequences, and runs on NVIDIA Fermi architecture graphics processing units. But how is it different from existing alignment tools?
1] CLAST is capable of identifying sequence similarities ~80.8 times faster than BLAST and 9.6 times faster than BLAT.
2] CLAST executes global alignment as the default (local alignment is also an option), enabling CLAST to assign reads to taxonomic and functional groups based on evolutionarily distant nucleotide sequences with high accuracy.
3] CLAST does not need a preprocessed sequence database like Burrows–Wheeler Transform-based tools, and this enables CLAST to incorporate large, frequently updated sequence databases.
4] CLAST requires <2 GB of main memory, making it possible to run CLAST on a standard desktop computer or server node.
Major application of CLAST is in Metagenomics. Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets. CLAST may serve to be a good tool for metagenomics or so I suppose!
— By Ushanandini Mohanraj