Unraveling the hidden complexity of cancer through long-read sequencing

Table 1.

Summary of software tools for analyzing long reads in cancer

Category Tool name Description Reference
Alignment NGMLR Convex gap-cost scoring model to achieve long-read alignment Sedlazeck et al. 2018
minimap2 Pairwise alignment method for long reads and large genomes Li 2018
Winnowmap Improvements in aligning long reads in repetitive regions Jain et al. 2020
Small variant detection ClairS Deep learning method designed for detecting somatic small variants, primarily for ONT long-read data Zheng et al. 2023
DeepSomatic Discovery of somatic small variants across multiple sequencing platforms Park et al. 2024
SV calling nanomonsv Identification of somatic SVs at single-nucleotide resolution Shiraishi et al. 2023
SAVANA Somatic SV and copy number aberrations caller for long reads Elrick et al. 2024
SVision-pro Neural network framework enabling somatic structural variant discovery and genotyping Wang et al. 2024
Sniffles2 Updated version of Sniffles; capable of identifying mosaic and population-level SVs using long reads Smolka et al. 2024
Severus Improved detection and characterization of somatic SVs in tumor genomes Keskus et al. 2024
Variant phasing WhatsHap Phasing of SNVs and smaller indels Martin et al. 2023
LongPhase Fast chromosome-scale phasing for both small and large variations Lin et al. 2022
Methylation identification DeepSignal Detection of DNA methylation states from ONT long reads Ni et al. 2019
Uncalled4 Toolkit for ONT signal alignment, analysis, and visualization, improving DNA and RNA modification detection Kovaka et al. 2024
ccsmeth DNA 5mCpGs caller for PacBio CCS data Ni et al. 2023
Methylation phasing NanoMethPhase Phasing of 5mCpGs from ONT sequencing data Akbari et al. 2021
MethPhaser Utilization of ONT methylation signals to extend SNV-based phasing Fu et al. 2024
ccsmethphase Nextflow pipeline for haplotype-aware methylation detection using PacBio CCS reads Ni et al. 2023

This Article

  1. Genome Res. 35: 599-620

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