Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples.
You can learn more about ARCHS4 and its pipeline here.
Select conditions below to toggle them from the plot:
| GROUP | CONDITION | SAMPLES |
|---|---|---|
| Pancreatic islets |
GSM2328743 GSM2328744 GSM2328745 GSM2328746
|
|
|
GSM2328739 GSM2328740 GSM2328741 GSM2328742
|
Submission Date: Sep 26, 2016
Summary: Purpose: To gain further mechanistic insight into phenotypic differences between wild type pancreatic islets and islets with loss of function of 4 Box C/D snoRNAs from the Rpl13a locus (U32a, U33, U34 and U35a).
Methods:High quality total RNA (RIN ≥ 8.5) was prepared from hand-picked islets (n = 4 mice/genotype) using TRIZOL reagent, treated with Turbo DNAse (Thermo Fisher), and used to prepare SeqPlex RNAseq libraries (Sigma). Sequencing was performed by the Washington University Genome Technology Access Center using two lanes of Illumina HiSeq 2500, 1x50. Reads were demultiplexed and trimmed, and STAR alignment and quantification analysis was carried out using the Partek Flow platform. Uniquely aligned reads were quantified to identify genes with at least a two-fold change between genotypes with p < 0.05 and FDR step-up of 0.05.
Results:We observed 2-fold or greater differences in the expression of only six genes.
Conclusions: Our data indicate that loss-of-function of snoRNAs from the Rpl13a locus is associated with modest changes in mRNA abundance.
GEO Accession ID: GSE87354
PMID: 27820699
Submission Date: Sep 26, 2016
Summary: Purpose: To gain further mechanistic insight into phenotypic differences between wild type pancreatic islets and islets with loss of function of 4 Box C/D snoRNAs from the Rpl13a locus (U32a, U33, U34 and U35a).
Methods:High quality total RNA (RIN ≥ 8.5) was prepared from hand-picked islets (n = 4 mice/genotype) using TRIZOL reagent, treated with Turbo DNAse (Thermo Fisher), and used to prepare SeqPlex RNAseq libraries (Sigma). Sequencing was performed by the Washington University Genome Technology Access Center using two lanes of Illumina HiSeq 2500, 1x50. Reads were demultiplexed and trimmed, and STAR alignment and quantification analysis was carried out using the Partek Flow platform. Uniquely aligned reads were quantified to identify genes with at least a two-fold change between genotypes with p < 0.05 and FDR step-up of 0.05.
Results:We observed 2-fold or greater differences in the expression of only six genes.
Conclusions: Our data indicate that loss-of-function of snoRNAs from the Rpl13a locus is associated with modest changes in mRNA abundance.
GEO Accession ID: GSE87354
PMID: 27820699
Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.
Differential expression signatures are automatically computed using the limma R package.
More options for differential expression are available to compute below.
Signatures:
Control Condition
Perturbation Condition
Only conditions with at least 1 replicate are available to select
Differential expression signatures can be computed using DESeq2 or characteristic direction.
This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.