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Dataset . 2020
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Data sources: ZENODO
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Gene expression counts from the Kremer et al study

Authors: Yepez, Vicente;

Gene expression counts from the Kremer et al study

Abstract

File description: Gene-level counts using the gtf file from the release 34 of GENCODE https://www.gencodegenes.org/human/release_34 Split counts spanning from one exon to another using an annotation-free algorithm, therefore capturing new splice sites Non-split counts covering exon-intron boundaries Sample annotation describing each sample from the dataset Description file with global information from the dataset Use: The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired end specifications match. Afterwards, the DROP pipeline can be used to compute expression and splicing outliers (https://github.com/gagneurlab/drop). Maintainer: Vicente A. Yépez, yepez@in.tum.de URL: https://github.com/gagneurlab/drop/ Number of samples: 119 Tissue: Fibroblast Organism: Homo sapiens Genome assembly: hg19 Gene annotation: gencode34 Disease (ICD-10: N): E75: 1, E79: 13, E88: 84, G31: 9, K72: 3, NONE: 9 Strand specific: FALSE Paired end: TRUE Cite as: RNA-Seq count tables were obtained from Zenodo (DOI: 10.5281/zenodo.3887451) based on the study of Kremer et al. [1] 1. Kremer, L., Bader, D., Mertes, C. et al. Genetic diagnosis of Mendelian disorders via RNA sequencing. Nat Commun 8, 15824 (2017). https://doi.org/10.1038/ncomms15824 Dataset contact: Vicente Yepez, yepez@in.tum.de

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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