Login / Signup

KSNP: a fast de Bruijn graph-based haplotyping tool approaching data-in time cost.

Qian ZhouFahu JiDongxiao LinXianming LiuZexuan ZhuJue Ruan
Published in: Nature communications (2024)
Long reads that cover more variants per read raise opportunities for accurate haplotype construction, whereas the genotype errors of single nucleotide polymorphisms pose great computational challenges for haplotyping tools. Here we introduce KSNP, an efficient haplotype construction tool based on the de Bruijn graph (DBG). KSNP leverages the ability of DBG in handling high-throughput erroneous reads to tackle the challenges. Compared to other notable tools in this field, KSNP achieves at least 5-fold speedup while producing comparable haplotype results. The time required for assembling human haplotypes is reduced to nearly the data-in time.
Keyphrases
  • high throughput
  • electronic health record
  • endothelial cells
  • big data
  • convolutional neural network
  • copy number
  • high resolution
  • neural network
  • single molecule
  • adverse drug
  • artificial intelligence
  • deep learning