Differential Gene Expression Analysis Suggestions
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4.9 years ago

Hello,

I am currently undergoing a project that involves deriving differentially expressed genes from RNA-seq data and performing an intersection analysis with the list of differentially expressed genes and a list of recent GWAS SNP's. I have performed this and have decided to conduct a pathway analysis on my genes that have intersected the GWAS SNP's. So far I have performed an analysis to identify enriched biological and pathological themes and functional clustering analysis using the DAVID database. I have also used STITCH to analyse known protein and chemical interactions. Does anybody have any suggestions of other resources I can use to conduct further analysis of biological pathways/disease-related genes? Just in case I'm missing something that would be useful!

Thanks in advance!

RNA-Seq • 978 views
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The clusterProfiler, DOSE, ReactomePA family of packages are pretty useful.

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4.9 years ago

You need to be super careful with this sort of analysis:

Long genes are more likely to have GWAS hits in them than short genes. Long genes (and highly expressed genes) are more likely to be differentially expressed than short genes.

Thus the overlap is much more likely to be significant than you'd expect, and the usual Fisher's/hypergeometric statistics for enrichment don't apply.

Several genesets/pathways are also enriched for long/highly expressed genes. For example, genes important to neurons are longer than other genes on average, thus if your set of DE/GWAS genes is longer than average, and neural genes are longer than average, then there is more likely to be a "chance" overlap between them than would be suggested by normal pathway enrichment statistics.

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4.9 years ago
kgosche ▴ 30

You could try Partek Pathway (http://www.partek.com/partek-pathway/). You can start with a list of genes and perform an enrichment test against the KEGG database. You can visualize pathway diagrams and annotate them with additional information.

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We have asked you before to include a disclaimer about the commercial nature of your product, A: single cell RNA-seq pipeline, please respect that.

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