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accession-icon GSE66649
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20), Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE66628
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_Gene1.0) (exon analysis)
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge IconAgilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Disease

View Samples
accession-icon GSE66648
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (Affymetrix_HTA2.0)
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconAgilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version), Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

Disease

View Samples
accession-icon SRP055917
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_ClonTech)
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations. Overall design: The study assessed differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP055916
Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology (RNA-seq_RiboZero)
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

We present a more extensive and yet precise assessment to elucidate differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes. Our results showed a fair degree of overall correlation between all 6 platforms evaluated; but, to varying degrees, two RNA-seq protocols outperformed three of the microarray platforms in most categories. Notably, a fourth microarray platform, Agilent, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments. Furthermore, 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% concordance with the gold standard TaqMan assay in terms of fold-change accuracy. Our study suggests that the use of transcript patterns can enhance a number of the observed cross-platform correlations, indicating a potential usefulness for similar evaluations. Overall design: The study assessed differences and similarities in performance at numerous aspects including signal range, sensitivity to fold-change, and fidelity with TaqMan qRT-PCR. There were three levels of data examined: entire data sets, data derived from gene name annotation oriented subset of 15442 RefSeq genes, and data derived from transcript pattern defined subset of 7034 RefSeq genes.

Publication Title

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE32719
Expression data from human bone marrow hematopoietic stem cells
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In the human hematopoietic system, aging is associated with decreased bone marrow cellularity, decreased adaptive immune system function, and increased incidence of anemia and other hematological disorders and malignancies. Recent studies in mice suggest that changes within the hematopoietic stem cell (HSC) population during aging contribute significantly to the manifestation of these age-associated hematopoietic pathologies. While the mouse HSC population has been shown to change both quantitatively and functionally with age, changes in the human HSC and progenitor cell populations during aging have not yet been characterized.

Publication Title

Human bone marrow hematopoietic stem cells are increased in frequency and myeloid-biased with age.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE23751
In Vitro Transcriptome Analysis of Porcine Plexus Epithelial Cells in Response to Streptococcus suis: Functions of the Choroid Plexus in Antimicrobial Defense
  • organism-icon Sus scrofa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Porcine Genome Array (porcine)

Description

We used microarrays to detail the global gene expression changes following apical infection of porcine choroid plexus epithelial cells (PCPEC) with Streptococcus suis (S. suis)

Publication Title

In vitro transcriptome analysis of porcine choroid plexus epithelial cells in response to Streptococcus suis: release of pro-inflammatory cytokines and chemokines.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE27159
Expression profiling of the murine neural crest precursor cell line, JoMa1
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

JoMa1 cells are pluripotent precursor cells, derived from the neural crest of mice transgenic for tamoxifen-inducible c-Myc. Following transfection with a cDNA encoding for MYCN, cells become immortlized even in the absence of tamoxifen.

Publication Title

MYCN and ALKF1174L are sufficient to drive neuroblastoma development from neural crest progenitor cells.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE16615
gene expression in human subcutaneous adipose tissue after CLA intervention
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Iisomer-specific effects of conjugated linoleic (CLA) supplementation on gene expression with particular consideration of the PPAR 2 Pro12Ala SNP in human adipose tissue.

Publication Title

Isomer-specific effects of CLA on gene expression in human adipose tissue depending on PPARgamma2 P12A polymorphism: a double blind, randomized, controlled cross-over study.

Sample Metadata Fields

Subject

View Samples
accession-icon GSE74297
MALT1 protease activity controls the expression of inflammatory genes in keratinocytes upon Zymosan stimulation
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

The protease activity of the paracaspase MALT1 plays an important role in antigen receptor-mediated lymphocyte activation by controlling the activity of the transcription factor NF-kB and is thus essential for the expression of inflammatory target genes.

Publication Title

MALT1 Protease Activity Controls the Expression of Inflammatory Genes in Keratinocytes upon Zymosan Stimulation.

Sample Metadata Fields

Treatment

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.

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