Effects of transcriptional noise on estimates of gene and transcript expression in RNA sequencing experiments

RNA sequencing is widely used to measure gene expression across a vast range of animal and plant tissues and conditions. Most studies of computational methods for gene expression analysis use simulated data to evaluate the accuracy of these methods. In this work we present a dataset of 3 tissues each containing 10 samples of simulated short RNA-seq reads across 4 types of transcription characterized from the GTEx dataset. For each type of transcription: 1) known isoforms; 2) splicing noise; 3) intronic noise; 4) intergenic noise -we provide sets of reads in CRAM format along with corresponding expression matrices and annotations in the GTF format for downstream analysis. A copy of GRCh.38 used in our analysis is also provided along with the simulated data. Further details on the structure of each file is provided in the accompanying README document.

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Author Ales Varabyou
Last Updated June 24, 2024, 16:03 (UTC)
Created June 24, 2024, 16:03 (UTC)
Citation Ales Varabyou 2020. Effects of transcriptional noise on estimates of gene and transcript expression in RNA sequencing experiments. CyVerse Data Commons. DOI 10.25739/v903-wd86
Date created in discovery environment 2020-12-11 21:18:18
Date last modified in discovery environment 2020-12-14 16:51:52
contributor Steven Lloyd Salzberg, Mihaela Pertea
identifierType DOI
publisher CyVerse Data Commons
resourceType Simulated RNAseq with noise