ArticleF1000Research2021
GARCOM: A user-friendly R package for genetic mutation counts.
Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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
0 citing papers in PubMed.
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Authors and funding
2 authors.
Funding
Abstract
Next-generation sequencing (NGS) has enabled analysis of rare and uncommon variants in large study cohorts. A common strategy to overcome these low frequencies and/or small effect sizes relies on collapsing strategies, i.e. to bin variants within genes/regions. Several tools are now available for advanced statistical analyses; however, tools to perform basic tasks such as obtaining allelic counts within defined gene/region boundaries are unavailable or require complex coding. GARCOM ("Gene And Region Count Of Mutations") library, an open-source freely available package in R language, returns a matrix with allelic counts within genes/regions per sample. GARCOM accepts input data in PLINK or VCF formats, with additional options to subset data for refined analyses.
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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 Socratic graph.