refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 159 results
Sort by

Filters

Technology

Platform

accession-icon GSE17700
Factorial study for evaluating the effect of Affy platform and lab on gene expression measurements
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Comparison of concordance in single and multi-gene genomic indices from data generated by two different laboratories (MD Anderson Cancer Center (MDA) and Jules Bordet Institute (JBI)) and on two different Affymetrix platforms (U113A and U133_Plus2).

Publication Title

Genomic index of sensitivity to endocrine therapy for breast cancer.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE11277
A2B5/OTMP+ rat perineuronal oligodendrocytes
  • organism-icon Rattus norvegicus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

Oligodendrocytes are cells from the central nervous system that can be grouped into precursors, myelin-forming, and non-myelinating perineuronal. The function of perineuronal oligodendrocytes is unknown; it was suggested that they can ensheath denuded axons. We tested this hypothesis. Using cell-specific tags, microarray technology and bioinformatics tools to identify gene expression differences between these subpopulations allowed us to capture the genetic signature of perineuronal oligodendrocytes. Here we report that perineuronal oligodendrocytes are configured for a dual role. As perineuronal, they integrate a repertoire of transcripts designed to create a cell with its own physiological agenda. But they maintain a reservoir of untranslated transcripts encoding the major myelin proteins for we speculate a pathological eventuality. We posit that the signature molecules PDGFR-, cytokine PDGF-CC, and the transcription factor Pea3 used among others - to define the non-myelinating phenotype, may be critical for mounting a myelinating programme during demyelination. Harnessing this capability is of therapeutic value for diseases such as multiple sclerosis. This is the first molecular characterization of perineuronal oligodendrocytes.

Publication Title

The genetic signature of perineuronal oligodendrocytes reveals their unique phenotype.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP125882
Transcriptomic analysis to map mechanisms of viral replication control in HIV-1 positive Elite Controllers
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In order to understand the underlying mechanisms, which ensure that disease progression is prevented in EC, a comprehensive analysis of clinical phenotypes coupled to genetics and biomolecular mechanisms is required. The rapidly increasing accessibility of genetic and biomolecular expression data from new high-throughput technologies is the foundation to shift the traditional phenotype-first approach to explorative genetic or molecular data-first approaches. In this study, we aimed to explore a comprehensive analysis of host transcriptomics and proteomics data coupled to clinical phenotypes in a well-defined Swedish EC cohort with up to 20 years of clinical follow-up data.

Publication Title

Transcriptomics and Targeted Proteomics Analysis to Gain Insights Into the Immune-control Mechanisms of HIV-1 Infected Elite Controllers.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Treatment, Race

View Samples
accession-icon GSE87732
Expression data from Daxx knockout MEFs
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Neuroendocrine tumors (NETs) often harbor loss-of-function mutations in Daxx gene. Daxx interacts with several partners to regulate cellular processes and gene expression.

Publication Title

Menin and Daxx Interact to Suppress Neuroendocrine Tumors through Epigenetic Control of the Membrane Metallo-Endopeptidase.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE87733
Expression data from Men1 knockout MEFs
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

Multiple endocrine neoplasia type1 (MEN1), an inherited autosomal dominant syndrome characterized by the development of endocrine tumors including NETs, results from mutation in the MEN1 gene that encodes the protein menin. In mouse models, heterozygous loss of Men1 leads to multiple endocrine tumors with loss of heterozygocity at the Men1 locus. Men1 interacts with several partners to regulate cellular processes and gene expression through regulating histone modification.

Publication Title

Menin and Daxx Interact to Suppress Neuroendocrine Tumors through Epigenetic Control of the Membrane Metallo-Endopeptidase.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP151120
RNA-seq profiling of patient-derived xenograft models in Urothelial Cancer
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To probe the tissue source (cancer cell VS stromal cell) of gene expression in the mixed tumor samples, we took advantage of a set of Urothelial Cancer patient-derived xenograft (PDX) models given that the transcriptome in these models is a mixture of human RNA (derived from cancer cells) and mouse RNA (derived from stromal cells). Overall design: The cohort includes 5 different patient-derived PDX models, 3 replicates for each model, and thus a total of 15 samples

Publication Title

EMT- and stroma-related gene expression and resistance to PD-1 blockade in urothelial cancer.

Sample Metadata Fields

Subject

View Samples
accession-icon SRP108341
TrapSeq: An RNA Sequencing-based pipeline for the identification of genetrap insertions in mammalian cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Current pipelines used to map genetrap insertion sites are based on inverse- or splinkerette-PCR methods, which despite their efficacy are prone to artifacts and do not provide information on the impact of the genetrap on the expression of the targeted gene. We developed a new method, which we named TrapSeq, for the mapping of genetrap insertions based on paired-end RNA sequencing. By recognizing chimeric mRNAs containing genetrap sequences spliced to an endogenous exon, our method identifies insertions that lead to productive trapping. Overall design: We conducted two independent screenings for sensitivity against 6-thioguanine (6TG) and an ATR inhibitor (ATRi). We applied our RNAseq-based pipeline (TrapSeq) to identify mutations that provide resistance to these reagents. Importantly, and besides its use for screenings, when applied to individual clones our method provides a fast and cost-effective way that not only identifies the insertion site of the genetrap but also reveals the impact of the insertion on the expression of the trapped gene. Please note that HAP1, haploid for all chromosomes, derives from near-haploid KBM7 parent line which was in turn obtained from a chronic myeloid leukemia patient in blast crisis phase (Carette et al. Nature 477:340-343, 2011).

Publication Title

Trap<sup>Seq</sup>: An RNA Sequencing-Based Pipeline for the Identification of Gene-Trap Insertions in Mammalian Cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066612
5''RNA-seq analysis of soleus, tibialis anterior (TA), diaphragm and left ventricle myocardial tissue from adult wild-type mice.
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

We applied a 5''RNA-seq methodology to assess gene and differential isoform expression in striated muscle tissues extracted from adult wild-type mice. Overall design: 5''RNA-seq analysis of transcriptomes from mouse soleus, tibialis anterior (TA), diaphragm and left ventricle myocardial tissues. Three biological replicates per tissue were pooled into a single sequencing run. 5''RNA-seq methodology consists of enhanced sequencing of 5'' ends and computational assessment of changes at start-sites of genes.

Publication Title

Tropomodulin 1 directly controls thin filament length in both wild-type and tropomodulin 4-deficient skeletal muscle.

Sample Metadata Fields

Sex, Specimen part, Cell line, Subject

View Samples
accession-icon SRP081553
Characterization of genetic loss-of-function of Fus in zebrafish
  • organism-icon Danio rerio
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

The RNA-binding protein FUS is implicated in transcription, alternative splicing of neuronal genes and DNA repair. Mutations in FUS have been linked to human neurodegenerative diseases such as ALS (amyotrophic lateral sclerosis). We genetically disrupted fus in zebrafish (Danio rerio) using the CRISPR-Cas9 system. The fus knockout animals are fertile and did not show any distinctive phenotype. Mutation of fus induces mild changes in gene expression on the transcriptome and proteome level in the adult brain. We observed a significant influence of genetic background on gene expression and 3’UTR usage, which could mask the effects of loss of Fus. Unlike published fus morphants, maternal zygotic fus mutants do not show motoneuronal degeneration and exhibit normal locomotor activity. Overall design: We performed paired-end sequencing (100bp reads) of the polyA+ transcriptome from brains of five individuals with Fus-/- genotype and four with Fus wild type genotype. Note on RNA-Seq replicates: after performing first RNA sequencing on four replicates of Fus-/- and WT (labeled with the prefix "Sample_imb_ketting_2014_13_") we received a notice from Illumina stating a problem with the library preparation kit lot that was used to prepare the libraries. Due to that, we performed RNA sequencing a second time, using the same input RNA, except for the Fus knockout replicate #3, because there was not enough input RNA left. Instead, a different Fus knockout replicate (#1) was sequenced. However, we compared the mapped reads from sequencing run 1 and sequencing run 2 using plotCorrelaction from DeepTools, and the samples are highly correlated (at least 0.97 and 0.95, Spearman and Pearson correlation respectively). Therefore, we considered first ("Sample_imb_ketting_2014_13_") and second sequencing runs as technical replicates.

Publication Title

Characterization of genetic loss-of-function of Fus in zebrafish.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE71312
Expression data from WT Col-0 and the pdx1.3 ko mutant of Arabidopsis
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

We performed a microarray experiment to assess the global changes in transcription occurring in leaves and roots of the vitamin B6 deficient pdx1.3 knockout mutant in comparison to WT. Vitamin B6 (pyridoxal 5-phosphate) is an essential cofactor of many metabolic enzymes. Plants biosynthesize the vitamin de novo employing two enzymes, pyridoxine synthase1 (PDX1) and PDX2. In Arabidopsis (Arabidopsis thaliana), there are two catalytically active paralogs of PDX1 (PDX1.1 and PDX1.3) producing the vitamin at comparable rates. Since single mutants are viable but the pdx1.1 pdx1.3 double mutant is lethal, the corresponding enzymes seem redundant.

Publication Title

Consequences of a deficit in vitamin B6 biosynthesis de novo for hormone homeostasis and root development in Arabidopsis.

Sample Metadata Fields

Specimen part

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