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Cited by 3,760

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

SOAP2: an improved ultrafast tool for short read alignment

Li, Ruiqiang, Yu, Chang, Li, Yingrui, Lam, Tak-Wah, Yiu, Siu-Ming, Kristiansen, Karsten, Wang, Jun·2009·Bioinformatics

Abstract

Summary: SOAP2 is a significantly improved version of the short oligonucleotide alignment program that both reduces computer memory usage and increases alignment speed at an unprecedented rate. We used a Burrows Wheeler Transformation (BWT) compression index to substitute the seed strategy for indexing the reference sequence in the main memory. We tested it on the whole human genome and found that this new algorithm reduced memory usage from 14.7 to 5.4 GB and improved alignment speed by 20–30 times. SOAP2 is compatible with both single- and paired-end reads. Additionally, this tool now supports multiple text and compressed file formats. A consensus builder has also been developed for consensus assembly and SNP detection from alignment of short reads on a reference genome. Availability: http://soap.genomics.org.cn Contact: soap@genomics.org.cn

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Metadata

Authors
Li, R., Yu, C., Li, Y., Lam, T.-W., Yiu, S.-M., Kristiansen, K., & Wang, J.
Venue
Bioinformatics
Published
2009-06-03
Volume
25
Issue
15
Pages
1966-1967
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2097341408
Cited by
3,760
References
3
FWCI
62.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: SOAP2: an improved ultrafast tool for short read alignment. https://app.cochat.ai/papers/10.1093/bioinformatics/btp336
The paper
Li, R., Yu, C., Li, Y., Lam, T.-W., Yiu, S.-M., Kristiansen, K., & Wang, J. (2009). SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics. https://doi.org/10.1093/bioinformatics/btp336

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.