Short Sequence Aligner Benchmarking for Chromatin Research
Much of today’s molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner’s abi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/24/18/14074 |
| _version_ | 1797579697116151808 |
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| author | John Lawrence Carter Harlan Stevens Perry G. Ridge Steven Michael Johnson |
| author_facet | John Lawrence Carter Harlan Stevens Perry G. Ridge Steven Michael Johnson |
| author_sort | John Lawrence Carter |
| collection | DOAJ |
| description | Much of today’s molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner’s ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings. |
| first_indexed | 2024-03-10T22:40:47Z |
| format | Article |
| id | doaj.art-ec4231addba549eb8a2599a2fb3e2825 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T22:40:47Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-ec4231addba549eb8a2599a2fb3e28252023-11-19T11:07:30ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-09-0124181407410.3390/ijms241814074Short Sequence Aligner Benchmarking for Chromatin ResearchJohn Lawrence Carter0Harlan Stevens1Perry G. Ridge2Steven Michael Johnson3Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USADepartment of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USADepartment of Biology, Brigham Young University, Provo, UT 84602, USADepartment of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USAMuch of today’s molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner’s ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings.https://www.mdpi.com/1422-0067/24/18/14074alignment programsChIP-seqNGS |
| spellingShingle | John Lawrence Carter Harlan Stevens Perry G. Ridge Steven Michael Johnson Short Sequence Aligner Benchmarking for Chromatin Research International Journal of Molecular Sciences alignment programs ChIP-seq NGS |
| title | Short Sequence Aligner Benchmarking for Chromatin Research |
| title_full | Short Sequence Aligner Benchmarking for Chromatin Research |
| title_fullStr | Short Sequence Aligner Benchmarking for Chromatin Research |
| title_full_unstemmed | Short Sequence Aligner Benchmarking for Chromatin Research |
| title_short | Short Sequence Aligner Benchmarking for Chromatin Research |
| title_sort | short sequence aligner benchmarking for chromatin research |
| topic | alignment programs ChIP-seq NGS |
| url | https://www.mdpi.com/1422-0067/24/18/14074 |
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