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accession-icon SRP002184
Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzer

Description

Epidermal growth factor (EGF) is a key regulatory growth factor activating a myriad of processes affecting cell proliferation and survival that are relevant to normal development and disease. Here we have used a combined approach to study the EGF dependent transcriptome of HeLa cells. We obtained mRNA expression profiles using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, Febit, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer I (GA-I). By applying a procedure for cross-platform data meta-analysis based on rank product and global ancova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We used this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we found a whole new set of genes previously unrelated to the currently accepted EGF associated cellular functions, among which are metallothionein genes. We propose the use of global genomic cross-validation to generate more reliable datasets derived from high content technologies (microarrays or deep sequencing). This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data. Keywords: treated vs. untreated comparison, time course Overall design: Time course experiment comparing HeLa gene expression in response to EGF analyzed on different microarray platforms (Agilent, IMPPC, Illumina, and Operon) and by digital gene expression using short read high throughput tag sequencing. Three independent experiments were performed where HeLa cells were serum deprived for 24 hours and were either left untreated or treated with EGF for 6, and 24 h and harvested for RNA extraction. Technical dye swap duplicates were performed for each of the three biological replicates in both time points. Comparative genomic hybridization of HeLa cell genomic DNA versus poooled genomic DNA from blood obtained from human females conducted on commercial oligonucleotide microarrays (Human Genome CGH Microarray Kit 244A, Agilent Technologies) in order to assess DNA dosage dependence of gene expression levels and response to EGF. Digital gene expression using short read high throughput tag sequencing data submitted to NCBI''s SRA

Publication Title

Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP077708
Transcriptome of Celiac Disease
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina HiScanSQ

Description

The aim of this study is to analyze the transcriptome of epithelial (CD326+ enriched) and immune (CD45+ enriched) fraction in Celiac Disease and controls to find differentially expressed genes.

Publication Title

The methylome of the celiac intestinal epithelium harbours genotype-independent alterations in the HLA region.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon E-MEXP-2702
Transcription profiling of Zea mays embryos under camptothecin (CPT) treatment
  • organism-icon Zea mays
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Maize Genome Array (maize)

Description

Camptothecin (CPT) is a plant alkaloid that specifically binds topoisomerase I (Topo I) inhibiting its activity and inducing double stranded breaks in the DNA, activating the genotoxic cell responses, and ultimately, it might trigger programmed cell death (PCD). We used microarrays to detail the changes in gene expression during as a consequence of CPT treatment in maize immature embryos. In four independent experiments immature embryos were plated on MS medium supplemented with 50 uM CPT and incubated during three days. Untreated embryos incubated on MS medium were used as controls.

Publication Title

Transcriptomic and proteomic profiling of maize embryos exposed to camptothecin.

Sample Metadata Fields

Specimen part, Compound

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accession-icon SRP059938
RNA-sequencing analysis of liver from mice overexpressing miR-30c
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

This study aims to investigate the role of microRNA-30c on hepatic and metabolic gene expression and physiology Overall design: For this experiment, we used male C57BL/6 mice. At an age of 8 weeks, we started them on Western diet for one month and then injected them with either PBS or increasing dose of Scr or miR-30c mimic (2.5, 5.0, and 7.5 mg/kg) for 6 weeks. Liver from these mice were harvested and flash frozen. RNA from the livers of these mice were extracted and RNA-seq was performed.

Publication Title

MicroRNA-30c Mimic Mitigates Hypercholesterolemia and Atherosclerosis in Mice.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE21819
Caenorhabditis elegans infected with Staphylococcus aureus
  • organism-icon Caenorhabditis elegans
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Young adult fer-15;fem-1 Caenorhabditis elegans were infected with Staphylococcus aureus for 8 h to determine the transcriptional host response to Staphylococcus aureus. Analysis of differential gene expression in C. elegans young adults exposed to two different bacteria: E. coli strain OP50 (control), wild-type Staphylococcus aureus RN6390. Samples were analyzed at 8 hours after exposure to the different bacteria. These studies identified C. elegans genes induced by pathogen infection.

Publication Title

Distinct pathogenesis and host responses during infection of C. elegans by P. aeruginosa and S. aureus.

Sample Metadata Fields

Disease, Disease stage

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accession-icon SRP042044
Innate host defense requires TFEB-mediated transcription of cytoprotective and antimicrobial genes
  • organism-icon Caenorhabditis elegans
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We report the profiling of induced mRNA transcripts in two C. elegan replicate populations -- WT (N2) and mutant strain with deficient HLH30. Both strains were fed either OP50 strain of e-coli (normal feed) or S. aureus Overall design: Examination of infected versus uninfected wildtype and mutant lawns of animals

Publication Title

Innate host defense requires TFEB-mediated transcription of cytoprotective and antimicrobial genes.

Sample Metadata Fields

Subject

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accession-icon GSE44541
Expression data from antimycin A-treated BE(2)-C cells
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of transcription response of undifferentiated human BE(2)-C neuronal cells to stimulation with purified antimycin A1a or unfractionated commercially available antimycin A (Sigma A8674).

Publication Title

Discovery of potent broad spectrum antivirals derived from marine actinobacteria.

Sample Metadata Fields

Specimen part

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accession-icon GSE51909
Expression data from 205432- or 206381-treated BE(2)-C cells
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Analysis of transcription response of undifferentiated human BE(2)-C neuronal cells to stimulation with novel indole-2-carboxamide antivirals 205432 or 206381.

Publication Title

Novel indole-2-carboxamide compounds are potent broad-spectrum antivirals active against western equine encephalitis virus in vivo.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP142312
Cell composition analysis of bulk genomics using single cell data
  • organism-icon Mus musculus
  • sample-icon 74 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Single-cell expression profiling is a rich resource of cellular heterogeneity. While profiling every sample under study is advantageous, such workflow is time consuming and costly. We devised CPM - a deconvolution algorithm in which cellular heterogeneity is inferred from bulk expression data based on pre-existing collection of single-cell RNA-seq profiles. We applied CPM to investigate individual variation in heterogeneity of murine lung cells during in vivo influenza virus infection, revealing that the relations between cell quantities and clinical outcomes varies in a gradual manner along the cellular activation process. Validation experiments confirmed these gradual changes along the cellular activation trajectory. Additional analysis suggests that clinical outcomes relate to the rate of cell activation at the early stages of this process. These findings demonstrate the utility of CPM as a mapping deconvolution tool at single-cell resolution, and highlight the importance of such fine cell landscape for understanding diversity of clinical outcomes. Overall design: Lungs gene expression of Collaborative Cross mice taken 48h after the infection with either the influenza virus or PBS.

Publication Title

Cell composition analysis of bulk genomics using single-cell data.

Sample Metadata Fields

Specimen part, Subject, Time

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accession-icon SRP069801
Dissecting the Effect of Genetic Variation on the Hepatic Expression of Drug Disposition Genes across the Collaborative Cross Mouse Strains
  • organism-icon Mus musculus
  • sample-icon 53 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

A central challenge in pharmaceutical research is to investigate genetic variation in response to drugs. The Collaborative Cross (CC) mouse reference population is a promising model for pharmacogenomic studies because of its large amount of genetic variation, genetic reproducibility, and dense recombination sites. While the CC lines are phenotypically diverse, their genetic diversity in drug disposition processes, such as detoxification reactions, is still largely uncharacterized. Here we systematically measured RNA-sequencing expression profiles from livers of 29 CC lines under baseline conditions. We then leveraged a reference collection of metabolic biotransformation pathways to map potential relations between drugs and their underlying expression quantitative trait loci (eQTLs). By applying this approach on proximal eQTLs, including eQTLs acting on the overall expression of genes and on the expression of particular transcript isoforms, we were able to construct the organization of hepatic eQTL-drug connectivity across the CC population. The analysis revealed a substantial impact of genetic variation acting on drug biotransformation, allowed mapping of potential joint genetic effects in the context of individual drugs, and demonstrated crosstalk between drug metabolism and lipid metabolism. Our findings provide a resource for investigating drug disposition in the CC strains, and offer a new paradigm for integrating biotransformation reactions to corresponding variations in DNA sequences. Overall design: This dataset includes RNA-Seq data of mRNA that were extracted from the liver of 55 male mice. The 55 mice belong to 29 different collaborative cross strains. The number of individual mice per strains is 3 for 3 strains, 2 for 16 strains, and 1 for 8 strains. All the mice are naïve without any special treatment.

Publication Title

Dissecting the Effect of Genetic Variation on the Hepatic Expression of Drug Disposition Genes across the Collaborative Cross Mouse Strains.

Sample Metadata Fields

Specimen part, Cell line, Subject

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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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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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