Hi Ramón,
We generally direct users to the (text based) user guide: https://software.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html
But also this video (that was produced by a 3rd party) is generally pretty good: https://www.youtube.com/watch?v=KY6SS4vRchY
-Anthony
Anthony S. Castanza, PhD
Curator, Molecular Signatures Database
Mesirov Lab, Department of Medicine
University of California, San Diego
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Hi Ramon
You can run this data in GSEA Preranked mode, if you just take the full list of genes and their Log2(FC) and format them as a .rnk file: Data formats - GeneSetEnrichmentAnalysisWiki (broadinstitute.org)
-Anthony
Anthony S. Castanza, PhD
Curator, Molecular Signatures Database
Mesirov Lab, Department of Medicine
University of California, San Diego
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-Anthony
Anthony S. Castanza, PhD
Curator, Molecular Signatures Database
Mesirov Lab, Department of Medicine
University of California, San Diego
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Hi Ramón
From this error message it’s looking like the CHIP file you’ve selected isn’t actually the right one for your gene identifiers.
The one you picked only works with unversioned Human Ensembl Gene IDs. Those IDs look like ENSG00000012345 or such. If the ID ends with a .version number in your data (like ENSG00000012345.6) that suffix would have to be removed. If your genes were converted to their gene symbol already then you’d want to use the Human_Gene_Symbol_with_Remapping_ chip. There are corresponding chips for Mouse or Rat data as well.
If you’re not sure exactly what chip you need, if you send a screenshot of your RNK file’s contents I can probably tell you which one it is.
-Anthony
Anthony S. Castanza, PhD
Curator, Molecular Signatures Database
Mesirov Lab, Department of Medicine
University of California, San Diego
From: Ramon Garcia Areas
Sent: Wednesday, October 13, 2021 8:02 PM
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Hi Ramón,
Based on the error message, that doesn't appear to be the right chip file for your dataset. Could you send me a sample, or a screenshot, of what the gene identifiers in your ranked list look like?
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Hi Ramón,
GSEA works its way down the entire ranked gene list computing if the genes in the gene set are, on balance, upregulated or downregulated. The gene sets that are upregulated on balance are presented in the positive enrichment phenotype (for preranked na_pos) and the gene sets that are on balance downregulated are presented in the negative enrichment phenotype (for preranked na_neg). It is possible for gene sets that are enriched in one direction to contain some genes that responded in the opposite direction, this just means that the signal of those genes was not enough to overbalance the signal of the other genes in the set. GSEA doesn't consider the up and down halves of the ranked list separately, it looks at the dataset as a whole and tries to evaluate each set in its global context.
Does that make sense?
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-Anthony
Anthony S. Castanza, PhD
Curator, Molecular Signatures Database
Mesirov Lab, Department of Medicine
University of California, San Diego
To view this discussion on the web visit https://groups.google.com/d/msgid/gsea-help/b82c48b5-8d70-486d-8a50-d0a390cdac76n%40googlegroups.com.
If you're not using the collapse functions then there will be no " Symbol_to_probe_set_mapping_details.tsv" and GSEA will use all the symbols as-is, it will still use these symbols to filter the gene sets and produce the filtered "gene_sets.gmt" and gene_set_sizes.tsv" which should tell you if there were genes that are in gene sets what were not detected in your dataset.
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