ArticlePeerJ2022
Fast, low-memory detection and localization of large, polymorphic inversions from SNPs.
Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- A Multi-Approach for In Silico Detection of Chromosome Inversions in Mosquito Vectors.Microorganisms · 2025Article
- Replicate geographic transects across a hybrid zone reveal parallelism and differences in the genetic architecture of reproductive isolation.Evolution letters · 2025Article
- Genomic patterns of strain-specific genetic structure, linkage, and selection across fall armyworm populations.BMC genomics · 2025Article
- Panmixia in the American eel extends to its tropical range of distribution: Biological implications and policymaking challenges.Evolutionary applications · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLarge (>1 Mb), polymorphic inversions have substantial impacts on population structure and maintenance of genotypes. These large inversions can be detected from single nucleotide polymorphism (SNP) data using unsupervised learning techniques like PCA. Construction and analysis of a feature matrix from millions of SNPs requires large amount of memory and limits the sizes of data sets that can be analyzed.
methodsWe propose using feature hashing construct a feature matrix from a VCF file of SNPs for reducing memory usage. The matrix is constructed in a streaming fashion such that the entire VCF file is never loaded into memory at one time.
resultsWhen evaluated on
conclusionWith these changes, inversions in larger data sets can be analyzed easily and efficiently on common laptop and desktop computers. Our method is publicly available through our open-source inversion analysis software, Asaph.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.