Abstract
Alignment of sequence reads is an important step of many bioinformatics workflows. While the alignment of short reads is well investigated, the alignment of long reads produced by third-generation sequencing technologies, such as Oxford Nanopore, is more challenging because they have high error rates (10-40%). Furthermore, due to their different algorithmic approaches, different tools produce varied alignments, significantly influencing the downstream analyses. In this study, we evaluated the performance of three alignment tools (LAST, GraphMap, and NanoBLASTer) using simulated nanopore reads. Although the three alignment strategies gave similar results (e.g., all close to 100% precision), GraphMap reported the longest alignments while LAST the shortest. However, GraphMap showed the lowest recall (90%) indicating high false negative rates. While GraphMap had the highest percentage of reads that were mapped to the correct reference regions, NanoBLASTer and especially LAST mapped the majority of the reads only partially correctly. Based on our multiple statistics, GraphMap had the best overall performance.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 |
| Editors | Illhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 169-174 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509030491 |
| DOIs | |
| State | Published - Dec 15 2017 |
| Event | 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States Duration: Nov 13 2017 → Nov 16 2017 |
Publication series
| Name | Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 |
|---|---|
| Volume | 2017-January |
Other
| Other | 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 |
|---|---|
| Country | United States |
| City | Kansas City |
| Period | 11/13/17 → 11/16/17 |
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Keywords
- Oxford Nanopore
- Third-generation sequencing
- error rates
- long-read alignment
- precision
- recall
- resources
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics
Cite this
Comparative analysis of alignment tools for nanopore reads. / Pavlovikj, Natasha; Moriyama, Etsuko N.; Deogun, Jitender S.
Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. ed. / Illhoi Yoo; Jane Huiru Zheng; Yang Gong; Xiaohua Tony Hu; Chi-Ren Shyu; Yana Bromberg; Jean Gao; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. p. 169-174 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Comparative analysis of alignment tools for nanopore reads
AU - Pavlovikj, Natasha
AU - Moriyama, Etsuko N.
AU - Deogun, Jitender S.
PY - 2017/12/15
Y1 - 2017/12/15
N2 - Alignment of sequence reads is an important step of many bioinformatics workflows. While the alignment of short reads is well investigated, the alignment of long reads produced by third-generation sequencing technologies, such as Oxford Nanopore, is more challenging because they have high error rates (10-40%). Furthermore, due to their different algorithmic approaches, different tools produce varied alignments, significantly influencing the downstream analyses. In this study, we evaluated the performance of three alignment tools (LAST, GraphMap, and NanoBLASTer) using simulated nanopore reads. Although the three alignment strategies gave similar results (e.g., all close to 100% precision), GraphMap reported the longest alignments while LAST the shortest. However, GraphMap showed the lowest recall (90%) indicating high false negative rates. While GraphMap had the highest percentage of reads that were mapped to the correct reference regions, NanoBLASTer and especially LAST mapped the majority of the reads only partially correctly. Based on our multiple statistics, GraphMap had the best overall performance.
AB - Alignment of sequence reads is an important step of many bioinformatics workflows. While the alignment of short reads is well investigated, the alignment of long reads produced by third-generation sequencing technologies, such as Oxford Nanopore, is more challenging because they have high error rates (10-40%). Furthermore, due to their different algorithmic approaches, different tools produce varied alignments, significantly influencing the downstream analyses. In this study, we evaluated the performance of three alignment tools (LAST, GraphMap, and NanoBLASTer) using simulated nanopore reads. Although the three alignment strategies gave similar results (e.g., all close to 100% precision), GraphMap reported the longest alignments while LAST the shortest. However, GraphMap showed the lowest recall (90%) indicating high false negative rates. While GraphMap had the highest percentage of reads that were mapped to the correct reference regions, NanoBLASTer and especially LAST mapped the majority of the reads only partially correctly. Based on our multiple statistics, GraphMap had the best overall performance.
KW - Oxford Nanopore
KW - Third-generation sequencing
KW - error rates
KW - long-read alignment
KW - precision
KW - recall
KW - resources
UR - http://www.scopus.com/inward/record.url?scp=85046288627&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046288627&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2017.8217645
DO - 10.1109/BIBM.2017.8217645
M3 - Conference contribution
AN - SCOPUS:85046288627
T3 - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
SP - 169
EP - 174
BT - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
A2 - Yoo, Illhoi
A2 - Zheng, Jane Huiru
A2 - Gong, Yang
A2 - Hu, Xiaohua Tony
A2 - Shyu, Chi-Ren
A2 - Bromberg, Yana
A2 - Gao, Jean
A2 - Korkin, Dmitry
PB - Institute of Electrical and Electronics Engineers Inc.
ER -