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accession-icon GSE42690
Exon-level expression profiling of normal colonic mucosa samples.
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

These samples have been analyzed for global alternative splicing variation on exon-level expression data using the FIRMA algorithm. We have identified and described transcriptome instability as a genome-wide, pre-mRNA splicing related characteristic of solid cancers.

Publication Title

Transcriptome instability as a molecular pan-cancer characteristic of carcinomas.

Sample Metadata Fields

Specimen part

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accession-icon GSE24551
Exon level expression profiling of colorectal cancer tissue samples
  • organism-icon Homo sapiens
  • sample-icon 331 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

Sample Metadata Fields

Specimen part

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accession-icon GSE24550
Exon level expression profiling of colorectal cancer tissue samples (validation sample series).
  • organism-icon Homo sapiens
  • sample-icon 165 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Colorectal cancer is a heterogeneous disease molecularly characterized by inherent genomic instabilities, chromosome instability and microsatellite instability. In the present study we propose transcriptome instability as an analogue to genomic instability on the transcriptome level. Exon microarray data from two independent series of altoghether 160 colorectal cancer tissue samples was used for global alternative splicing detection using the FIRMA algorithm (aroma.affymetrix). The sample-wise amounts of these alternative splicing scores exceeding a defined threshold (deviating exon usage amounts) were summarized to provide the basis for description of transcriptome instability. This characteristic was shown to be associated with splicing factor expression levels and patient survival in both independent sample series.

Publication Title

Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

Sample Metadata Fields

Specimen part

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accession-icon GSE24549
Exon level expression profiling of colorectal cancer tissue samples (test sample series).
  • organism-icon Homo sapiens
  • sample-icon 166 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Colorectal cancer is a heterogeneous disease molecularly characterized by inherent genomic instabilities, chromosome instability and microsatellite instability. In the present study we propose transcriptome instability as an analogue to genomic instability on the transcriptome level. Exon microarray data from two independent series of altoghether 160 colorectal cancer tissue samples was used for global alternative splicing detection using the FIRMA algorithm (aroma.affymetrix). The sample-wise amounts of these alternative splicing scores exceeding a defined threshold (deviating exon usage amounts) were summarized to provide the basis for description of transcriptome instability. This characteristic was shown to be associated with splicing factor expression levels and patient survival in both independent sample series.

Publication Title

Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival.

Sample Metadata Fields

Specimen part

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accession-icon GSE30378
Gene level expression profiling of colorectal cancer tissue samples (test sample series)
  • organism-icon Homo sapiens
  • sample-icon 95 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This series is part of a larger series (GSE24549) of colorectal cancer tissue samples analyzed for global gene expression. The expression measures were used to develope a gene signature for prediction of prognosis in stage II and III colorectal cancer.

Publication Title

ColoGuideEx: a robust gene classifier specific for stage II colorectal cancer prognosis.

Sample Metadata Fields

Specimen part

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accession-icon GSE29638
Gene level expression profiling of colorectal cancer tissue samples
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

By the use of whole genome transcription analysis, we aimed to develop a gene expression classifier to increase the likelihood of identifying stage II colorectal cancer (CRC) samples with a poor prognostic outcome. Gene expression measurement were measured by the GeneChip Human Exon 1.0 ST Arrays from Affymetrix.

Publication Title

ColoGuideEx: a robust gene classifier specific for stage II colorectal cancer prognosis.

Sample Metadata Fields

Specimen part

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accession-icon GSE69182
Exon level expression profiling of colorectal cancer tissue samples (77 samples)
  • organism-icon Homo sapiens
  • sample-icon 77 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

These colorectal cancer (CRC) samples have been analyzed by exon expression profiling to identify genes with overexpression of 3 parts. By characterizing underlying transcript structures of such genes with a combination of rapid amplification of cDNA ends and deep-sequencing (RACE-seq), we identify and describe novel RNA-variants in CRC.

Publication Title

Novel RNA variants in colorectal cancers.

Sample Metadata Fields

Specimen part

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accession-icon GSE140258
Gene expression profiling of colorectal cancer cell lines after treatment with talazoparib
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

We have performed post-treatment gene expression profiling of cell lines to analyze response mechanisms to PARP inhibition.

Publication Title

Molecular correlates of sensitivity to PARP inhibition beyond homologous recombination deficiency in pre-clinical models of colorectal cancer point to wild-type TP53 activity.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE80750
Gene expression profiling of the prostate cancer cell line PC3.
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

To study the effect of miR-130a in prostate cancer, PC3 cells overexpressing miR-130a were analyzed for global gene expression.

Publication Title

Epigenetic disruption of miR-130a promotes prostate cancer by targeting SEC23B and DEPDC1.

Sample Metadata Fields

Cell line

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accession-icon GSE42954
Expression profiling of prostate cancer biopsies.
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This work was conducted to identify shared and specific target genes of different ETS transcription factor rearrangements in prostate cancer. Potential target genes were identified by differential gene expression analysis of primary tumor samples with ETS rearrangements, and validated by ETS silencing in prostate cancer cell lines.

Publication Title

Molecular subtyping of primary prostate cancer reveals specific and shared target genes of different ETS rearrangements.

Sample Metadata Fields

Specimen part

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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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