ArticleMethods in enzymology2021
Systematic refinement of gene annotations by parsing mRNA 3' end sequencing datasets.
Article in Methods in enzymology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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5 authors at 3 institutions in 1 country.
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Abstract
Alternative cleavage and polyadenylation generates mRNA 3' isoforms in a cell type-specific manner. Due to finite available RNA sequencing data of organisms with vast cell type complexity, currently available gene annotation resources are incomplete, which poses significant challenges to the comprehensive interpretation and quantification of transcriptomes. In this chapter, we introduce 3'GAmES, a stand-alone computational pipeline for the identification and quantification of novel mRNA 3'end isoforms from 3'mRNA sequencing data. 3'GAmES expands available repositories and improves comprehensive gene-tag counting by cost-effective 3' mRNA sequencing, faithfully mirroring whole-transcriptome RNAseq measurements. By employing R and bash shell scripts (assembled in a Singularity container) 3'GAmES systematically augments cell type-specific 3' ends of RNA polymerase II transcripts and increases the sensitivity of quantitative gene expression profiling by 3' mRNA sequencing. Public access: https://github.com/AmeresLab/3-GAmES.git.
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