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accession-icon GSE89997
Expression data from 2 cohorts of human pancreatic ductal adenocarcinoma (PDAC) tumors
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

In this dataset, we included expression data obtained from 30 resected human PDAC tumors, to examine what genes are differentially expressed in different cohorts that might lead to various outcomes

Publication Title

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE50868
Induction of Ground-State Pluripotency by Minimal Factor Episomal-Expression in Single Cell Format
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human pluripotent stem cells in culture are often associated with the prime state which represents a more developed state relative to the nave state which is often associated with the inner cell mass and thought to have the potential to give rise to all cell types. We have developed a small molecule-driven cocktail FMM that maintains human pluripotent stem cells in a state similar to the naive state as defined by several properties including gene expression profile.

Publication Title

Platform for induction and maintenance of transgene-free hiPSCs resembling ground state pluripotent stem cells.

Sample Metadata Fields

Specimen part

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accession-icon SRP034732
Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion
  • organism-icon Homo sapiens
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples. We compared technical and biological replicates having undergone globin depletion or not and found that globin depletion removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Overall design: Peripheral whole blood transcriptome assessed by RNA-Seq on Illumina HiSeq 2000 in 6 healthy individuals and 6 pooled samples, either globin depleted or not.

Publication Title

Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33970
Predicting Acute Cardiac Allograft Rejection Using Donor and Recipient Gene Expression
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Acute rejection in cardiac transplant patients is still a contributing factor to limited survival of the implanted heart. Currently there are no biomarkers in clinical use that can predict, at the time of transplantation, the likelihood of post-transplantation acute rejection, which would be of great importance for personalizing immunosuppressive treatment. Within the Biomarkers in Transplantation initiative, the predictive biomarker discovery focused on data and samples collected before or during transplantation such as: clinical variables, genes and proteins from the recipient, and genes from the donor. Based on this study, the best predictive biomarker panel contains genes from the recipient whole blood and from donor endomyocardial tissue and has an estimated area under the curve of 0.90. This biomarker panel provides clinically relevant prediction power and may help personalize immunosuppressive treatment and frequency of rejection monitoring.

Publication Title

Predicting acute cardiac rejection from donor heart and pre-transplant recipient blood gene expression.

Sample Metadata Fields

Sex, Age, Specimen part, Race

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accession-icon GSE17739
Circadian gene profiling in the distal nephron and collecting ducts
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Renal excretion of water and major electrolytes exhibits a significant circadian rhythm. This functional periodicity is believed to result, at least in part, from circadian changes in secretion/reabsorption capacities of the distal nephron and collecting ducts. Here, we studied the molecular mechanisms underlying circadian rhythms in the distal nephron segments, i.e. distal convoluted tubule (DCT) and connecting tubule (CNT) and, the cortical collecting duct (CCD). Temporal expression analysis performed on microdissected mouse DCT/CNT or CCD revealed a marked circadian rhythmicity in the expression of a large number of genes crucially involved in various homeostatic functions of the kidney. This analysis also revealed that both DCT/CNT and CCD possess an intrinsic circadian timing system characterized by robust oscillations in the expression of circadian core clock genes (clock, bma11, npas2, per, cry, nr1d1) and clock-controlled Par bZip transcriptional factors dbp, hlf and tef. The clock knockout mice or mice devoid of dbp/hlf/tef (triple knockout) exhibit significant changes in renal expression of several key regulators of water or sodium balance (vasopressin V2 receptor, aquaporin-2, aquaporin-4, alphaENaC). Functionally, the loss of clock leads to a complex phenotype characterized by partial diabetes insipidus, dysregulation of sodium excretion rhythms and a significant decrease in blood pressure. Collectively, this study uncovers a major role of molecular clock in renal function.

Publication Title

Molecular clock is involved in predictive circadian adjustment of renal function.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP068418
Targeted deletion of circadian clock gene Arntl in the nephron results in dysregulation of diverse metabolic pathways
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina HiSeq 2000

Description

The circadian clock controls a wide variety of metabolic and homeostatic processes in a number of tissues, including the kidney. However, the role of the renal circadian clocks remains largely unknown. To address this question we performed transcriptomic analysis in mice with inducible and conditional ablation of the circadian clock system in the renal tubular cells (Bmal1lox/lox/Pax8-rtTA/LC1 mice). Deep sequencing of the renal transcriptome revealed significant changes in the expression of genes related to metabolic pathways and organic anion transport. In parallel, kidneys from Bmal1lox/lox/Pax8-rtTA/LC1 mice exhibited a significant decrease in the NAD+/NADH ratio suggesting an increased anaerobic glycolysis and/or decreased mitochondrial function. In-depth analysis of two selected pathways revealed (i) a significant increase in plasma urea levels correlating with increased renal arginase 2 (Arg2) activity, hyperargininemia and increase of the kidney arginine content; (ii) a significantly increased plasma creatinine concentration and reduced capacity of the kidney to secrete anionic drugs (furosemide), paralleled by a ~80% decrease in the expression levels of organic anion transporter OAT3 (SLC22a8). Collectively, these results indicate that the renal circadian clocks control a variety of metabolic/homeostatic processes at both the intra-renal and systemic levels and are involved in drug disposition. Overall design: Mice with a specific ablation of the Arntl gene encoding BMAL1 in the renal tubular cells were compared to wild-type littermate at ZT4 and ZT16 (ZT – Zeitgeber time units; ZT0 is the time of light on and ZT12 is the time of light off).

Publication Title

Nephron-Specific Deletion of Circadian Clock Gene Bmal1 Alters the Plasma and Renal Metabolome and Impairs Drug Disposition.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon GSE114469
Expression data from NPY Y1R-deficient osteoblastic cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

NPY signalling via osteoblastic Y1 receptors has been shown to control bone mass but also contributes significantly to the control of whole-body insulin secretion and glucose homeostasis in mice through the release of novel factor(s) which are different from the previously implicated osteocalcin.

Publication Title

Osteoglycin, a novel coordinator of bone and glucose homeostasis.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP049142
Mus musculus strain:CL57BL6x129 Transcriptome or Gene expression
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Identification of downstream genes of onecut transcriptions factors in the developing retina

Publication Title

Onecut1 and Onecut2 redundantly regulate early retinal cell fates during development.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE47353
Global Analyses of Human Immune Variation Reveal Baseline Predictors of Postvaccination Responses
  • organism-icon Homo sapiens
  • sample-icon 288 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A major goal of systems biology is the development of models that accurately predict responses to perturbation. Constructing such models requires the collection of dense measurements of system states, yet transformation of data into predictive constructs remains a challenge. To begin to model human immunity, we analyzed immune parameters in depth both at baseline and in response to influenza vaccination.

Publication Title

Global analyses of human immune variation reveal baseline predictors of postvaccination responses.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon SRP055444
Immunoglobulin transcript sequence and somatic hypermutation computation from unselected RNA-seq reads in Chronic Lymphocytic Leukemia
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

IGHV mutation status is a well-established prognostic factor in chronic lymphocytic leukemia, and also provides crucial insights into tumor cell biology and function. Currently, determination of IGHV transcript sequence, from which mutation status is calculated, requires a specialized laboratory procedure. RNA sequencing is a method that provides high resolution, high dynamic range transcriptome data that can be used for differential expression, isoform discovery, and variant determination. In this paper, we demonstrate that unselected next-generation RNA sequencing can accurately determine the IGH@ sequence, including the complete sequence of the complementarity-determining region 3 (CDR3), and mutation status of CLL cells, potentially replacing the current method which is a specialized, single-purpose Sanger-sequencing based test. Overall design: CLL cells were sequenced by mRNA-seq on the Illumina platform then subjected to the costom bioinformatic pipeline Ig-ID which yields IGH data

Publication Title

Immunoglobulin transcript sequence and somatic hypermutation computation from unselected RNA-seq reads in chronic lymphocytic leukemia.

Sample Metadata Fields

No sample metadata fields

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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)

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Developed by the Childhood Cancer Data Lab

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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.

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