ArticleMethods in molecular biology (Clifton, N.J.)2023
Genotyping of Transposable Element Insertions Segregating in Human Populations Using Short-Read Realignments.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- A unified framework to analyze transposable element insertion polymorphisms using graph genomes.Nature communications · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transposable element (TE) insertions are a major source of structural variation in the human genome. Due to the repetitive nature and biological importance of TEs, many bioinformatic tools have been developed to identify and genotype TE insertion polymorphisms using high-throughput short-reads. In this chapter, we outline recently developed methods to characterize TE insertion polymorphisms in human populations. We also provide detailed protocols to tackle this question primarily using three software: MELT2, ERVcaller, and TypeREF.
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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.