ArticleGenome research2016
A flexible method for estimating the fraction of fitness influencing mutations from large sequencing data sets.
Article in Genome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Deep whole-genome sequencing reveals recent selection signatures linked to evolution and disease risk of Japanese.Nature communications · 2018Pooled it
- The ChinaMAP analytics of deep whole genome sequences in 10,588 individuals.Cell research · 2020Article
- Genome-Wide Natural Selection Signatures Are Linked to Genetic Risk of Modern Phenotypes in the Japanese Population.Molecular biology and evolution · 2020Article
- Korean Genome Project: 1094 Korean personal genomes with clinical information.Science advances · 2020Article
- Sperm competitive advantage of a rare mitochondrial haplogroup linked to differential expression of mitochondrial oxidative phosphorylation genes.Journal of evolutionary biology · 2019Article
- Adaptive Landscape of Protein Variation in Human Exomes.Molecular biology and evolution · 2018Article
- Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples.Genetics · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A continuing challenge in the analysis of massively large sequencing data sets is quantifying and interpreting non-neutrally evolving mutations. Here, we describe a flexible and robust approach based on the site frequency spectrum to estimate the fraction of deleterious and adaptive variants from large-scale sequencing data sets. We applied our method to approximately 1 million single nucleotide variants (SNVs) identified in high-coverage exome sequences of 6515 individuals. We estimate that the fraction of deleterious nonsynonymous SNVs is higher than previously reported; quantify the effects of genomic context, codon bias, chromatin accessibility, and number of protein-protein interactions on deleterious protein-coding SNVs; and identify pathways and networks that have likely been influenced by positive selection. Furthermore, we show that the fraction of deleterious nonsynonymous SNVs is significantly higher for Mendelian versus complex disease loci and in exons harboring dominant versus recessive Mendelian mutations. In summary, as genome-scale sequencing data accumulate in progressively larger sample sizes, our method will enable increasingly high-resolution inferences into the characteristics and determinants of non-neutral variation.
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Registered trials
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