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Rapid and accurate alignment of nucleotide conversion sequencing reads with HISAT-3N.

Yun ZhangChanhee ParkChristopher BennettMicah ThorntonDaehwan Kim
Published in: Genome research (2021)
Sequencing technologies using nucleotide conversion techniques such as cytosine to thymine in bisulfite-seq and thymine to cytosine in SLAM seq are powerful tools to explore the chemical intricacies of cellular processes. To date, no one has developed a unified methodology for aligning converted sequences and consolidating alignment of these technologies in one package. In this paper, we describe hierarchical indexing for spliced alignment of transcripts-3 nucleotides (HISAT-3N), which can rapidly and accurately align sequences consisting of any nucleotide conversion by leveraging the powerful hierarchical index and repeat index algorithms originally developed for the HISAT software. Tests on real and simulated data sets show that HISAT-3N is faster than other modern systems, with greater alignment accuracy, higher scalability, and smaller memory requirements. HISAT-3N therefore becomes an ideal aligner when used with converted sequence technologies.
Keyphrases
  • single cell
  • rna seq
  • genome wide
  • machine learning
  • big data
  • electronic health record
  • deep learning
  • dna methylation
  • data analysis
  • mass spectrometry
  • artificial intelligence
  • amino acid