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- Confirming that autism and epilepsy genes are expressed in specific brain areas
- Gene expression enrichment tests are sensitive enough to detect where your background data came from #TopAnat
- When fold-enrichment is more informative than p-values: #TopAnat analysis of autism genes from GWAS
- #TopAnat where are genes significant in a breast cancer GWAS expressed?
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Monthly Archives: February 2016
When fold-enrichment is more informative than p-values: #TopAnat analysis of autism genes from GWAS
In a recent post on this blog we saw how to analyze results from a breast cancer GWAS. In that case, we did not have very strong expectations of tissue-specificity for the genes; it was more of an exploratory analysis. … Continue reading
#TopAnat where are genes significant in a breast cancer GWAS expressed?
Genome Wide Association Studies (GWAS) report many significant SNPs, which may be associated to many genes. How can we make sense of them? One way is to compute enrichment of the resulting gene list for properties of interest. For example … Continue reading
The contribution of #RNAseq, #microarrays, in situ hybridization and ESTs to #TopAnat gene enrichment signal
In Bgee, we integrate gene expression data from RNA-seq, Affymetrix microarrays, ESTs and in situ hybridization data. It is natural to think that with RNA-seq being so powerful, we should not bother with other sources of information. Yet we still have … Continue reading
Posted in RNA-Seq, topanat
Tagged ESTs, in situ hybridization, Microarray, RNA-Seq, statistics
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What makes #TopAnat special relative to classical #GeneOntology enrichment?
In bioinformatics and genomics, we are all familiar with GO (Gene Ontology) enrichment test. You take a gene list, paste it into a tool such as Gorilla, PANTHER, or others, and obtain a list of terms which are enriched in … Continue reading
Posted in topanat
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