ArticleBMC bioinformatics2020
smsMap: mapping single molecule sequencing reads by locating the alignment starting positions.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- pathMap: a path-based mapping tool for long noisy reads with high sensitivity.Briefings in bioinformatics · 2024Article
- invMap: a sensitive mapping tool for long noisy reads with inversion structural variants.Bioinformatics (Oxford, England) · 2023Article
- Article
- kngMap: Sensitive and Fast Mapping Algorithm for Noisy Long Reads Based on theFrontiers in genetics · 2022Article
- Nanopore sequencing technology, bioinformatics and applications.Nature biotechnology · 2021Review
- Comparison of Methods for Picking the Operational Taxonomic Units From Amplicon Sequences.Frontiers in microbiology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundSingle Molecule Sequencing (SMS) technology can produce longer reads with higher sequencing error rate. Mapping these reads to a reference genome is often the most fundamental and computing-intensive step for downstream analysis. Most existing mapping tools generally adopt the traditional seed-and-extend strategy, and the candidate aligned regions for each query read are selected either by counting the number of matched seeds or chaining a group of seeds. However, for all the existing mapping tools, the coverage ratio of the alignment region to the query read is lower, and the read alignment quality and efficiency need to be improved. Here, we introduce smsMap, a novel mapping tool that is specifically designed to map the long reads of SMS to a reference genome.
resultssmsMap was evaluated with other existing seven SMS mapping tools (e.g., BLASR, minimap2, and BWA-MEM) on both simulated and real-life SMS datasets. The experimental results show that smsMap can efficiently achieve higher aligned read coverage ratio and has higher sensitivity that can align more sequences and bases to the reference genome. Additionally, smsMap is more robust to sequencing errors.
conclusionssmsMap is computationally efficient to align SMS reads, especially for the larger size of the reference genome (e.g., H. sapiens genome with over 3 billion base pairs). The source code of smsMap can be freely downloaded from https://github.com/NWPU-903PR/smsMap .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.