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accession-icon GSE4182
Genetic background of the polygenic neural tube defect
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In polygenic disorders we do not know exactly, how many genes are involved in the pathomechanism, but the analysis of fetal gene expression can get us closer to the solution. In our study we were searching for the genetic background of the polygenic neural tube defect, which is the second most common birth defect in the world (1 in 1000 live births). Our data revealed novel candidate genes, like SLAP, LST1 and BENE, which can play an important role in the pathogenesis of neural tube defects. We created a data warehouse from the results, suitable for further analysis. This study also demonstrates that a routinely collected amount of amniotic fluid (as small as 6 mL) is enough to successfully hybridize isolated RNA to expression arrays, making the ability to use the technique from normally collected amniotic fluid samples.

Publication Title

Use of routinely collected amniotic fluid for whole-genome expression analysis of polygenic disorders.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE5081
Expression data from Helicobacter positive and negative human gastritis samples
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The whole-genome oligonucleotide microarray analysis gives an opportunity for studying the unidentified gene expression background of the idiopathic and H.pylori related gastric erosive alterations. Using microarrays we compared the whole genome gene expression profile of HP+ and HP- gastric erosions and normal adjacent mucosa to explain the possible role and response to HP infection and to get morphology related mRNA expression patterns.

Publication Title

Helicobacter pylori and antrum erosion-specific gene expression patterns: the discriminative role of CXCL13 and VCAM1 transcripts.

Sample Metadata Fields

Sex, Age, 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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