refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 690 results
Sort by

Filters

Technology

Platform

accession-icon GSE42641
A Top-down Systems Analysis Identifies an Innate Feed-forward Inflammatory Circuit Leading to Lethal Influenza Infection
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A systems analysis identifies a feedforward inflammatory circuit leading to lethal influenza infection.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE42639
Transcriptomic comparison of 5 cell types during lethal and non-lethal influenza infection
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

Transcriptomic comparison of 5 cell types during lethal and non-lethal influenza infection and further use of these signatures in a top-down systems analysis investigating the relative pathogenic contributions of direct viral damage to lung epithelium vs. dysregulated immunity during lethal influenza infection.

Publication Title

A systems analysis identifies a feedforward inflammatory circuit leading to lethal influenza infection.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon SRP170747
Deciphering the 'm6A code' via quantitative profiling of m6A at single-nucleotide resolution [II]
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

N6-methyladenosine (m6A) is the most abundant modification on mRNA, and is implicated in critical roles in development, physiology and disease. A major challenge in the field has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MASTER-seq for systematic quantitative profiling of m6A at single nucleotide resolution, building on differential cleavage by an RNAse at methylated sites. MASTER-seq permitted validation and de novo discovery of m6A sites, calibration of the performance of antibody based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is 'hard-coded' in cis via a simple and predictable code. This code accounts for ~50% of the variability in methylation levels and allows accurate prediction of m6A loss/acquisition events across evolution. MASTER-seq will allow quantitative investigation of m6A regulation in diverse cell types and disease states. Overall design: 10 samples were analyzed: EBS WT and Metll3 -/- with two replicates each and ESC WT and Mettld -/- with three replicates

Publication Title

Deciphering the "m<sup>6</sup>A Code" via Antibody-Independent Quantitative Profiling.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon SRP170748
De novo detection of m6A modification in Saccharomyces cerevisiae at single nucleotide resolution
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

N6-methyladenosine (m6A) is the most abundant modification on mRNA, and is implicated in critical roles in development, physiology and disease. A major challenge in the field has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MASTER-seq for systematic quantitative profiling of m6A at single nucleotide resolution, building on differential cleavage by an RNAse at methylated sites. MASTER-seq permitted validation and de novo discovery of m6A sites, calibration of the performance of antibody based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is 'hard-coded' in cis via a simple and predictable code. This code accounts for ~50% of the variability in methylation levels and allows accurate prediction of m6A loss/acquisition events across evolution. MASTER-seq will allow quantitative investigation of m6A regulation in diverse cell types and disease states. Overall design: 8 samples are analyzed: IP and background for IME4 mutant and WT with 2 biological replicates for each condition

Publication Title

Deciphering the "m<sup>6</sup>A Code" via Antibody-Independent Quantitative Profiling.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon SRP078795
Single-cell spatial reconstruction reveals global division of labor in the mammalian liver
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

The mammalian liver consists of hexagonal-shaped lobules, radially polarized by blood flow and morphogens. Key liver genes have been shown to be differentially expressed along the lobule axis, a phenomenon termed zonation, but a detailed genome-wide reconstruction of this spatial division of labor has not been achieved. Here we measure the whole transcriptome of thousands of single mouse liver cells and infer their lobule coordinates using a panel of zonated landmark genes, characterized with single-molecule FISH. We obtain a genome-wide reconstruction of liver zonation profiles with unprecedented spatial resolution. We find that more than 50% of liver genes are significantly zonated and uncover abundant non-monotonic profiles that peak at the mid-lobule layers. Our approach can facilitate reconstruction of similar spatial genomic blueprints for other mammalian organs. Overall design: mRNA profiles from single cells extracted from mouse liver were generated by deep sequencing of 1736 of single cells, sequenced in several batches in an Illumina NextSeq.

Publication Title

Single-cell spatial reconstruction reveals global division of labour in the mammalian liver.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE28750
Development and Validation of a Novel Molecular Biomarker Diagnostic Test for the Early Detection of Sepsis
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing.

Publication Title

Development and validation of a novel molecular biomarker diagnostic test for the early detection of sepsis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE57338
RNA-Seq Identifies Novel Myocardial Gene Expression Signatures of Heart Failure [microarray]
  • organism-icon Homo sapiens
  • sample-icon 313 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

We have utilized the RNA-Seq technology to identify genes with distinct expression patterns between failing and non-failing hearts. In an era of next-generation sequencing studies, our study demonstrates how knowledge gained from a small set of samples with accurately measured gene expressions using RNA-Seq can be leveraged as a complementary strategy to discern the genetics of complex disorders.

Publication Title

RNA-Seq identifies novel myocardial gene expression signatures of heart failure.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

View Samples
accession-icon GSE10961
Gene expression profiling of liver metastases from colorectal cancer
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

At present, medical treatments of synchronous and metachronous liver metastases from colorectal cancer are not differentiated. The aim of the study was to analyze the gene expression profiling of synchronous and metachronous lesions in order to identify molecular signatures as possible basis for choice of systemic therapies. Fresh tissues specimens from metastases of 18 patients undergone liver surgery were collected (10 synchronous and 8 metachronous lesions). Gene expression profiling was studied using Affymetrix platform. Two different profiles were identified. Pathway related to the Epidermal Growth Factor receptor (EGFr) was upregulated in metachronous lesions whereas pathways mainly related to inflammation in synchronous lesions. Real Time-PCR, Western Blotting and ELISA confirmed that the metachronous lesions had the overexpression of EGFr, but the synchronous ones had the overexpression of Cyclo-oxygenase 2 (COX-2). These results suggest that synchronous or metachronous liver metastases from colorectal cancer could be differently treated on the basis of different molecular pathways.

Publication Title

Gene expression profiling of liver metastases from colorectal cancer as potential basis for treatment choice.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE70216
Differential gene expression to VEGF in aorta from wild-type and C17S PKARI knock-in mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Angiogenesis is essential for tissue development, wound healing and tissue perfusion, with its dysregulation linked-to tumorigenesis, rheumatoid arthritis and heart disease. Here we show pro-angiogenic stimuli couple to NADPH oxidase-dependent generation of oxidants that catalyse an activating intermolecular-disulphide between regulatory-RI subunits of protein kinase A (PKA), which stimulates PKA-dependent ERK signalling. This is crucial to blood vessel growth as 'redox-dead' Cys17Ser RI knock-in mice fully resistant to PKA disulphide-activation have deficient angiogenesis in models of hind limb ischaemia and tumour-implant growth. Disulphide-activation of PKA represents a new therapeutic target in diseases with aberrant angiogenesis.

Publication Title

Deficient angiogenesis in redox-dead Cys17Ser PKARIα knock-in mice.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE42765
MLLT10 gene recombinations in pediatric T-Acute Lymphoblastic Leukemia
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

MLLT10, a 24 exons gene at 10p12, is known in leukemogenesis as partner of MLL or PICALM and recently NAP1L1. We identified HNRNPH1 and DDX3X, genes involved in RNA processing, as new MLLT10 partners in 2 cases of pediatric NOTCH1 positive T-ALL. HNRNPH1/5q35 encodes for a member of the ubiquitously expressed heterogeneous nuclear ribonucleoprotein (hnRNP) subfamily of RNA binding protein. DDX3X/Xp11.3, belongs to the big family of RNA helicases with a DEAD box domain.

Publication Title

New MLLT10 gene recombinations in pediatric T-acute lymphoblastic leukemia.

Sample Metadata Fields

Disease

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