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A new APA-seq analysis method improves differential gene expression detection, helping researchers gain deeper insights from RNA sequencing data and alternative polyadenylation stu...
RNA sequencing from more than 22 million cells trained a model that predicts cell-type-specific gene expression and noncoding variant...
A new statistical framework improves microRNA sequencing analysis by increasing sensitivity, reducing false discoveries, and providing more accurate detection of differential micro...
by Zhexiao Lin, Yuanyuan Gao, Wei Sun Gene-by-gene differential expression analysis is a widely used supervised approach for interpreting single-cell RNA-sequencing (scRNA-seq) da...
RNA sequencing analysis with the USADAE deep learning framework improves detection of hidden confounders while preserving biological signals for transcriptomics studies... The post...
RNA sequencing supports space biology research by enabling transcriptome-wide analysis of gene expression changes associated with spaceflight and adaptation to space environments.....
Benchmarking five RNA velocity methods reveals how sequencing depth and biological complexity influence trajectory predictions from single-cell RNA sequencing data... The post Comp...
by David J. Warne, Xiangrun Zhu, Thomas P. Steele, Stuart T. Johnston, Scott A. Sisson, Matthew Faria, Ryan J. Murphy, Alexander P. Browning Biological systems exhibit substantial...
by Clemens Kohl, Martin Vingron Clustering for single-cell RNA-seq aims at finding similar cells and grouping them into biologically meaningful clusters. Many available clustering...
by Simo Kitanovski, Shannon Conroy, Justin Sonneck, Lukas Claas, Madeleine Dorsch, Sebastian Urban, Jianxu Chen, Markus Kaiser, Barbara M. Grüner, Daniel Hoffmann Cell migration i...
by Yan Shao, Yazhou Li, Hexin Zhai, Shimin Dong Predicting microRNA target genes is essential for understanding their biological functions. This study developed a miRNA target gen...
RNA sequencing quality improves with scQCenrich, which combines multiple biological and technical metrics to preserve valuable cells while reducing unnecessary filtering... The pos...
by Sarah Ancheta, Leah Dorman, Guillaume Le Treut, Abel Gurung, Greg Huber, Loïc A. Royer, Alejandro Granados, Merlin Lange Single-cell RNA sequencing is revolutionizing our under...
by Araf Mahmud, Chen Huang Alternative splicing affects 95% of multi-exon genes, generating protein isoforms with distinct functions. While current alternative splicing analyses e...
RNA sequencing with the miND pipeline supports standardized small RNA analysis for biomarker discovery across tissues, plasma, extracellular vesicles, and other sample types...
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