Data-based filtering for replicated high-throughput transcriptome sequencing experiments
TL;DR: This work proposes a data-driven method based on the Jaccard similarity index to calculate a filtering threshold for replicated RNA sequencing data, and demonstrates the effectiveness of the proposed method to correctly filter lowly expressed genes, leading to increased detection power for moderately to highly expressed genes.
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Abstract: RNA sequencing is now widely performed to study differential expression among experimental conditions. As tests are performed on a large number of genes, very stringent false discovery rate control is required at the expense of detection power. Ad hoc filtering techniques are regularly used to moderate this correction by removing genes with low signal, with little attention paid to their impact on downstream analyses.
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Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells
Florian Klemm,Florian Klemm,Roeltje R. Maas,Robert L. Bowman,Mara Kornete,Mara Kornete,Klara Soukup,Klara Soukup,Sina Nassiri,Sina Nassiri,Sina Nassiri,Jean-Philippe Brouland,Christine A. Iacobuzio-Donahue,Cameron Brennan,Viviane Tabar,Philip H. Gutin,Roy Thomas Daniel,Monika E. Hegi,Johanna A. Joyce,Johanna A. Joyce +19 more
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TL;DR: In this article, the authors combined a highly synchronous photobioreactor culture system with frequent temporal sampling to characterize genome-wide diurnal gene expression in Chlamydomonas reinhardtii.
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Characterization of Rare, Dormant, and Therapy-Resistant Cells in Acute Lymphoblastic Leukemia
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Power analysis and sample size estimation for RNA-Seq differential expression
TL;DR: A power analysis tool is provided that captures the dispersion in the data and can serve as a practical reference under the budget constraint of RNA-Seq experiments and confirm a local optimal power is achievable for a given budget constraint.
DEBrowser: interactive differential expression analysis and visualization tool for count data
TL;DR: DEBrowser is a flexible, intuitive, web-based analysis platform that enables an iterative and interactive analysis of count data without any requirement of programming knowledge.
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