Author Archives: bgeedb

About bgeedb

This is the blog of the database of gene expression evolution Bgee, at University of Lausanne and Swiss Institute of Bioinformatics. http://www.bgee.org/

New gene page, new Bgee interface

Yesterday we have released a major update of our web interface: The download functionality remains the same, as does the data (processing for the next release is just starting with the new Ensembl release – we love Ensembl). It’s just easier … Continue reading

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Confirming that autism and epilepsy genes are expressed in specific brain areas

Recently we presented on this blog a quick-and-dirty analysis of genes with the keyword “autism” from the GWAS Catalog at EBI. But recently, Jabbari and Nürnberg have published a more thorough study of autism and epilepsy candidate genes: Jabbari and … Continue reading

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Gene expression enrichment tests are sensitive enough to detect where your background data came from #TopAnat

When you invent such a cool toy as TopAnat, you play with it. And then sometimes, you’re afraid that you might have broken it. But then, maybe it’s more robust than you expected. This is such a story. One lab … Continue reading

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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

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#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

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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

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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

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