GPU blast
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https://www.osc.edu/content/gpu_blast
osc 用的是 下面这个版本
https://pubmed.ncbi.nlm.nih.gov/21088027/
GPU-BLAST: using graphics processors to accelerate protein sequence alignment
源码：
https://sahinidis.coe.gatech.edu/gpublast
这个工具是gpu版本的blastp 对比的是蛋白序列 -
https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-07132-6
Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2 -
https://www.researchgate.net/post/Any_suggestions_for_a_fast_nucleotide_alignment_tool2
lastz blast的对比
I suppose you should decide what is the purpose of the alignment you are going to carry out and what datasets are used as a query and a subject. It will determine the alignment tools to be used.
Tools like LASTZ or LAST perform whole-genome alignments of large assembled genome fragments (chromosomes, scaffolds, contigs). They are optimized in the way to create so-called chained alignments, that is, alignments which consist of gap-free alignment blocks separated by large gaps. Such alignments are typically used in studying genome rearrangements, synteny blocks and homologous genome regions.
Alignment tools from the NCBI BLAST package (blastn, megablast and others) are used to align short nucleotide or amino acid sequences, like genes or proteins. For example, one may search for gene homologs in the genome of interest using blastn. The search is performed in three steps:
exact matches (seeds or words) are searched between query and subject sequences; the word size is specified by the -word_size option,
the seeds are expanded without using gaps (the -xdrop_ungap option),
the obtained gap-free alignments are expanded using gaps (the -xdrop_gap and -xdrop_gap_final options).
The general rule is that the smaller is the word size, the more sensitive but also slower is the alignment search.
The third group of alignment tools is read aligners like BWA or bowtie. They are optimized to align the large number of reads and usually do well with their default parameters. The read aligners are used in comparative genomics analysis, for example, to detect genomic variants between individuals of the same or related species by aligning the reads to the genome.
As far as I understand, you have an assembled reference genome and a pool of reads from related individuals and you are to study their genomic variability. For that analysis, the read aligners seem to be the most appropriate tools. I would advise you to use bowtie2 - it is a reliable, convenient and fast tool that supports running in parallel mode. Please find the link to the bowtie2 website below.
http://bowtie-bio.sourceforge.net/bowtie2/index.shtml -
https://www.comp.hkbu.edu.hk/~chxw/software/G-BLASTN.html
gpu版本的blastn
G-BLASTN is not yet suitable for databases with short sequences, such as NCBI nucleotide collection (nt) database.
https://github.com/OpenHero/gblastn