refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 206 results
Sort by

Filters

Technology

Platform

accession-icon GSE2331
Rat mammary expression in individuals and pools
  • organism-icon Rattus norvegicus
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

Rat mammary glands were obtained from individual rats in RXR treated (a) and control (b) conditions (12 rats in each condition). The 24 samples were hybridized individually. Also, in each condition, samples were combined into different pools of 2, pools of 3, pools of 12. Technical replicates were also run.

Publication Title

On the utility of pooling biological samples in microarray experiments.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE62204
Transcription in wounded rat vocal folds and vocal fold fibroblasts
  • organism-icon Rattus norvegicus
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

We used microarrays to characterize transcriptome profiles of rat vocal fold tissue following surgical injury (vs. naive tissue); rat vocal fold fibroblasts harvested from scar tissue at the 60 d time point (vs. naive fibroblasts); rat vocal fold scar fibroblasts treated with siRNA against the collagen chaperone protein rat gp46 (vs. scramble siRNA).

Publication Title

Microarray-based characterization of differential gene expression during vocal fold wound healing in rats.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE6323
Expression data from skeletal muscle of young, old and old calorie restricted mice
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

We investigated age-related changes in the transcriptional profile of skeletal muscle in 5 month old (young) and 25 month old (old) C57BL/6NHsd mice using high density oligonucleotide arrays (22,690 transcripts probed). We identified 712 transcripts that are differentially expressed in young (5 month old) and old (25-month old) mouse skeletal muscle. Caloric restriction (CR) completely or partially reversed 87% of the changes in expression. Examination of individual genes revealed a transcriptional profile indicative of increased p53 activity in the older muscle. To determine whether the increase in p53 activity is associated with transcriptional activation of apoptotic targets, we performed RT-PCR on four well known mediators of p53-induced apoptosis: puma, noxa, tnfrsf10b and bok. Expression levels for these proapoptotic genes increased significantly with age (P<0.05), while CR significantly lowered expression levels for these genes as compared to control fed old mice (P<0.05). Age-related induction of p53-related genes was observed in multiple tissues, but was not observed in SOD2+/- and GPX4+/- mice, suggesting that oxidative stress does not mediate the observed age-related increase in expression. Western blot analysis confirmed that protein levels for both p21 and GADD45a, two established transcriptional targets of p53, were higher in the older muscle tissue. These observations support a role for p53-mediated apoptotic activity in mammalian aging.

Publication Title

Gene expression profiling of aging reveals activation of a p53-mediated transcriptional program.

Sample Metadata Fields

Age

View Samples
accession-icon GSE49958
Gene expression in human umbilical cord vein and artery endothelial cells under physiological chronic normoxia (3% O2, PCN) and standard culture normoxia (21% O2, SCN)
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Endothelial cells, and many other types of cells too, physiologically reside in low O2 environments (~ 2-13% O2 or 15-60 mmHg pO2; [PCN]) relevantly to atmospheric O2 (~ 21% or 160 mmHg pO2 at sea level) in vivo. Such PCN is critical for endothelial functions. The majority of our current knowledge regarding the cellular and signaling mechanisms governing endothelial functions, however, is built on endothelial models established under atmospheric O2 (~21% O2). Herein, we comapred the transcriptional profiles between HUVE and HUAE cells cultured and expanded under PCN (3% oxygen) and standard culture normoxia (21% O2).

Publication Title

Transcriptional and functional adaptations of human endothelial cells to physiological chronic low oxygen.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE9361
Functional interaction between a PIP2 novel polyA polymerase and type 1 PIPKIalpha
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A loss of StarPap would be predicted to result in a decrease in cellular levels of mRNAs which it polyadenylates. Moreover, if PIPKIalpha has a function relationship with StarPap, knockdown of PIPKIalpha should cause a decrease in a pool of target mRNAs which require both StarPap and PIPKIalpha for their maturation. To test this, we independently knocked down StarPap and PIPKIalpha, and performed microarray analysis of total polyadenylated mRNAs from each group.

Publication Title

A PtdIns4,5P2-regulated nuclear poly(A) polymerase controls expression of select mRNAs.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE2531
JEG3 vs BeWo
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

In this experiment we compared total RNA from two commonly used choriocarcinoma cell lines, JEG3 and BeWo, to identify differentially expressed transcripts.

Publication Title

Microarray analysis of BeWo and JEG3 trophoblast cell lines: identification of differentially expressed transcripts.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP050992
Single cell RNA-seq data of human hESCs to evaluate Oscope - a statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-Seq
  • organism-icon Homo sapiens
  • sample-icon 460 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Oscillatory gene expression is fundamental to mammalian development, but technologies to monitor expression oscillations are limited. We have developed a statistical approach called Oscope to identify and characterize the transcriptional dynamics of oscillating genes in single-cell RNA-seq data from an unsynchronized cell population. Applications to a number of data sets, include a single-cell RNA-seq data set of human embroyonic stem cells (hESCs), demonstrate advantages of the approach and also identify a potential artifact in the Fluidigm C1 platform. Overall design: Total 213 H1 single cells and 247 H1-Fucci single cells were sequenced. The 213 H1 cells were used to evaluate Oscope in identifying oscillatory genes. The H1-Fucci cells were used to confirm the cell cycle gene cluster identified by Oscope in the H1 hESCs. Normalized expected counts are provided in GSE64016_H1andFUCCI_normalized_EC.csv.gz

Publication Title

Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP082529
Single cell RNA-seq data of human hESCs to evaluate SCnorm: robust normalization of single-cell rna-seq data
  • organism-icon Homo sapiens
  • sample-icon 414 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Normalization of RNA-sequencing data is essential for accurate downstream inference, but the assumptions upon which most methods are based do not hold in the single-cell setting. Consequently, applying existing normalization methods to single-cell RNA-seq data introduces artifacts that bias downstream analyses. To address this, we introduce SCnorm for accurate and efficient normalization of scRNA-seq data. Overall design: Total 183 single cells (92 H1 cells, 91 H9 cells), sequenced twice, were used to evaluate SCnorm in normalizing single cell RNA-seq experiments. Total 48 bulk H1 samples were used to compare bulk and single cell properties. For single-cell RNA-seq, the identical single-cell indexed and fragmented cDNA were pooled at 96 cells per lane or at 24 cells per lane to test the effects of sequencing depth, resulting in approximately 1 million and 4 million mapped reads per cell in the two pooling groups, respectively.

Publication Title

SCnorm: robust normalization of single-cell RNA-seq data.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP043590
Chromatin and signaling pathways in reprogramming
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Reprogramming intermediates (pre-iPSCs) were subjected to control DMSO, ascorbic acid (AA), 2i ( MAP kinase inhibitor + GSKinhibitor) or AA+2i conditions to assess conversion to the iinduced pluripotent stem cell state (iPSC) after 10days. Overall design: Pre-iPSC cells exposed to control DMSO, AA, 2i or AA+2i were harvested on day 2 for RNA sequencing after treatment, in biological triplicate.

Publication Title

Collaborative rewiring of the pluripotency network by chromatin and signalling modulating pathways.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP067036
Snapshot and temporal scRNA-seq of progenitor cells to dissect human embryonic stem cells entry into endoderm progenitors
  • organism-icon Homo sapiens
  • sample-icon 1810 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Human pluripotent stem cells (hPSCs) offer a unique cellular model to study lineage specifications of the primary germ layers during human development. We profiled single-cell RNA-seq (scRNA-seq) on four lineage-specific progenitor cells derived from hESCs. Our scRNA-seq analyses revealed each type of progenitors display various extend of heterogeneity. Specifically, definitive endoderm cells (DECs) not only show a greater degree of heterogeneity, but are also enriched in metabolic signatures. Followed by detailed temporal scRNA-seq profiling along DEC differentiation, we reconstructed a differentiation trajectory using a novel statistical pipeline named Wave-Crest. Wave-Crest further identifies candidate regulators during the transitioning phase from Brachyury (T)+ mesendoderm towards CXCR4+ DEC state. To functionally test identified novel regulators; we generated a live cell monitoring system, a T-2A-EGFP knock-in reporter cell line via CRISPR/CAS9. We demonstrated that, among the top candidate genes, KLF8 plays a pivotal role modulating mesendoderm to DEC differentiation. In this submission, 1810 raw fastq files are provided; 212 are re-analysis from GSE64016. Four expected count matrices are provided - 1) 1018 single cells from snapshot progenitors; 2) 758 single cells from time couse profiling; 3) 19 bulk RNA-seq sample from snapshot progenitors; 4) 15 bulk RNA-seq sample from time course profiling. Overall design: Total 1018 single cells from snapshot progenitors and 758 single cells from time couse profiling. Matchd population bulk RNA-seq samples for both the progenitors snapshot (19 samples) and time course profiling (15 samples) also included in this submission. These data set are used to detect the transitioning phase from mesendoderm to definitive endoderm.

Publication Title

Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm.

Sample Metadata Fields

No sample metadata fields

View Samples
...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

BSD 3-Clause LicensePrivacyTerms of UseContact