ArticleBioinformatics (Oxford, England)2023
Pseudoalignment tools as an efficient alternative to detect repeated transposable elements in scRNAseq data.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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1 citing paper in PubMed.
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7 authors.
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Abstract
motivationTransposable elements (TE) have played a major role in configuring the structures of mammalian genomes through evolution. In normal conditions, the expression of these elements is repressed by different epigenetic regulation mechanisms such as DNA methylation, histone modification and regulation by small RNAs. TE re-activation is associated with stemness potential acquisition, regulation of innate immunity and disease, such as cancer. However, the vast majority of current knowledge in the field is based on bulk expression studies, and very little is known on cell-type- or state-specific expression of TE-derived transcripts. Therefore, cost-efficient single-cell-resolution TE expression analytical approaches are needed.
resultsWe have implemented an analytical approach based on pseudoalignment to consensus sequences to incorporate TE expression information to scRNAseq data. AVAILABILITY AND IMPLEMENTATION: All the data and code implemented are available as Supplementary data and in: https://github.com/jmzvillarreal/kallisto_TE_scRNAseq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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