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Wall clock times for analysis of 72 Pickrell et al 36 bp RNA-Seq samples.
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2015-12-02
相关数据集
Additional file 4: of Empirical assessment of the impact of sample number and read depth on RNA-Seq analysis workflow performance
Literature survey citations and average sample number. 200 studies containing RNA-Seq differential expression analysis, either from all species or limited to primary human samples. Average sample numb
NIAID Data Ecosystem40
Additional file 2: of Empirical assessment of the impact of sample number and read depth on RNA-Seq analysis workflow performance
Sample combinations for each iteration at varying sample numbers. The same sample combinations were run at all read depths and for all workflows. (XLSX 21 kb)
NIAID Data Ecosystem10
Detection Theory in Identification of RNA-DNA Sequence Differences Using RNA-Sequencing
Advances in sequencing technology have allowed for detailed analyses of the transcriptome at single-nucleotide resolution, facilitating the study of RNA editing or sequence differences between RNA and
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Additional file 7 of Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnostics
Additional file 7. Table S5. The performance comparison results of our RNA-Seq pipeline.
NIAID Data Ecosystem30
Additional file 2: of Empirical assessment of the impact of sample number and read depth on RNA-Seq analysis workflow performance
Sample combinations for each iteration at varying sample numbers. The same sample combinations were run at all read depths and for all workflows. (XLSX 21 kb)
Figshare2018-11-15 更新10
