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accession-icon GSE24514
Expression data from human MSI colorectal cancer and normal colonic mucosa
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Microsatellite instability (MSI), caused by defective mismatch repair, is observed in a subset of colorectal cancers (CRCs). We evaluated somatic mutations in microsatellite repeats of genes chosen based on reduced expression in MSI CRC and existence of a coding mononucleotide repeat.

Publication Title

Candidate driver genes in microsatellite-unstable colorectal cancer.

Sample Metadata Fields

Specimen part

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accession-icon SRP021911
Small RNA sequencing of human preovulatory cumulus and mural granulosa cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The granulosa cells in the mammalian ovarian follicle respond to gonadotropin signalling and are involved in the processes of folliculogenesis and oocyte maturation. Studies on gene expression and regulation in human granulosa cells are of interest due to their potential for estimating the oocyte viability and IVF success. However, the post-transcriptional gene expression studies on miRNA level in the human ovary have been scarce. The current study determined the miRNA profile by deep sequencing of the two intrafollicular somatic cell types: mural and cumulus granulosa cells isolated from women undergoing controlled ovarian stimulation and in vitro fertilization. Overall design: Paired cumulus and mural granulosa samples were analysed from 3 women participating in IVF procedure. Libraries of all 6 samples were sequenced twice, generating 2 technical replicates for each sample. Differential gene expression study was performed on the pooled results of technical replicates.

Publication Title

Research resource: small RNA-seq of human granulosa cells reveals miRNAs in FSHR and aromatase genes.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP021912
High-throughput RNA sequencing of human preovulatory cumulus and mural granulosa cells (mRNA)
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The granulosa cells in the mammalian ovarian follicle respond to gonadotropin signalling and are involved in the processes of folliculogenesis and oocyte maturation. Studies on gene expression and regulation in human granulosa cells are of interest due to their potential for estimating the oocyte viability and IVF success. The current study determined the mRNA profile by deep sequencing of the two intrafollicular somatic cell types: mural and cumulus granulosa cells isolated from women undergoing controlled ovarian stimulation and in vitro fertilization. Overall design: Paired cumulus and mural granulosa samples were analysed from 3 women participating in IVF procedure. Differential gene expression study was performed. The identified gene expression profile was also used for predicting targets for miRNAs that were also identified from the same samples (GSE46489).

Publication Title

Research resource: small RNA-seq of human granulosa cells reveals miRNAs in FSHR and aromatase genes.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE53203
Notch signaling regulates neural crest differentiation from human pluripotent stem cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The aim of the dataset was to study on genome-wide level the effect of Notch inhibition in gene expression on neural crest differentiation of human embryonic stem cells under chemically defined conditions.

Publication Title

Notch signaling regulates the differentiation of neural crest from human pluripotent stem cells.

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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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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