Mouse RNA-Seq data with two conditions, four samplesPanagiotis Moulos
RNA sequencing (RNA-seq) is the leading technology for genome-wide transcript quantification. However, publicly available RNA-seq data is currently provided mostly in raw form, a significant barrier for global and integrative retrospective analyses.
Gene functionality is closely connected to its expression specificity across tissues and cell types. RNA-Seq is a powerful quantitative tool to explore genome wide expression. The aim of this study is to provide a comprehensive RNA-Seq dataset across the same 13 tissues for mouse and rat, two ...
A bar graph produced using the RNA sequencing (RNA-seq) data showed that the average fold changes of solute carrier family 22 member 2 (Slc22a2) and neuromedin S (NM’s) were significantly reduced in PFF-injected TRPV1flox/flox; Cx3cr1cre mice compared with PFF-injected TRPV1flox/...
As of June 18, 2021, we have evaluated 16,983 mouse microarray or RNA-seq data sets (including bulk and single-cell RNA-seq data), identified 3199 data sets as relevant for GXD, and completed the metadata annotation for 3188 data sets. The searchable index is available via the RNA-Seq ...
We identified 696 poly(A)- genes by bulk RNA sequencing, of which around 30 % could be recovered in a single cell by SUPeR-seq (for details, see Additional file 3). When merged the SUPeR-seq data of the seven single cell samples together, over 50 % of these 696 genes could be ...
ChIP-seq data, combined with RNA-seq revealed a striking correlation between the level of transcripts and that of H3.3 accumulation in expressed genes. Finally, we demonstrate that H3.3 deposition is markedly enhanced upon stimulation by interferon on interferon stimulated genes, highlighting ...
Integration of RNA-Seq data with results of QTL mapping from an advanced intercross reduced the number of positional candidates from 1099 genes residing throughout QTL regions to 49 candidate genes differentially expressed or with the coding polymorphisms (with likely functional consequences) between the...
3 Filtering of scRNAseq samples based on per sample count data. a, Histograms showing total counts, total features per counts as well as the percentage of mitochondrial counts for each of the 12 single-cell RNA-seq samples. b, Scatter plot showing total counts (x-axis) and total features ...
Differential gene expression analysis of RNA-seq data Reads were aligned to the mouse reference genome (mm10) with STAR v2.5.0a using default parameters18. Raw read counts were calculated with STAR using the GeneCounts option of the quantMode parameter since the libraries were unstranded. Librar...