Alignment Uncertainty and Genomic Analysis
Abstract
The statistical methods applied to the analysis of genomic data do not account for uncertainty in the sequence alignment. Indeed, the alignment is treated as an observation, and all of the subsequent inferences depend on the alignment being correct. This may not have been too problematic for many phylogenetic studies, in which the gene is carefully chosen for, among other things, ease of alignment. However, in a comparative genomics study, the same statistical methods are applied repeatedly on thousands of genes, many of which will be difficult to align. Using genomic data from seven yeast species, we show that uncertainty in the alignment can lead to several problems, including different alignment methods resulting in different conclusions.
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The choice of a similarity or diversity measure can impact the interpretation of results in genetic association studies.
“Exploiting sequence similarity or diversity in genetic association studies can be problematic due to the fact that the choice of a similarity or diversity measure can impact the interpretation of the results.”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [127]
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References 26 · Cited by 411
- Authors
- Wong, K. M., Suchard, M. A., & Huelsenbeck, J. P.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Huelsenbeck, John P.
- Venue
- Science
- Published
- 2008-01-25
- Volume
- 319
- Issue
- 5862
- Pages
- 473-476
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2127688908
- Cited by
- 411
- References
- 26
- Citations by year
- 2026: 11 · 2025: 9 · 2024: 14 · 2023: 10 · 2022: 14 · 2021: 23 · 2020: 14 · 2019: 15 · 2018: 20 · 2017: 17 · 2016: 15 · 2015: 19 · 2014: 23 · 2013: 25 · 2012: 22
- FWCI
- 21.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01gm069801-09)
- National Institute of General Medical Sciences (R01 GM-069801, GM069801)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Keywords
- comparative genomics, yeast genome, phylogenetic inference, genomic data analysis
- MeSH terms
- Algorithms, Amino Acid Sequence, Base Sequence, Monte Carlo Method, Phylogeny, Saccharomyces, Selection, Genetic, Software, Models, Statistical, Open Reading Frames, Sequence Alignment, Genome, Fungal, Evolution, Molecular, Computational Biology, Genomics, Uncertainty
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