Using gene expression data (log2 fold change) to analyze enrichment test with GSEA
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3.8 years ago
sslimb95 • 0

Hello.

Thanks in advance.

I'm just beginning in bioinformatics, so any help would be really appreciated.

I want to do GSEA to get an enrichment score.

I knew that input data which is gene expression data that are comparable to one another across features within a sample and comparable to one another across samples like Counts/Expected Counts, Transcripts per Million (TPM) and FPKM/RPKM. (https://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Using_RNA-seq_Datasets_with_GSEA)

But i want to do GSEA to input data which have an expression information which are log2(fold change).

Is there any solution that using log2 fold change expression data for input data to do GSEA using gseapy or GSEA program in www.gsea-msigdb.org ?

Again, thank you so much.

rna-seq GSEA log2foldchange • 2.2k views
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Hi, I have the same issue here.

I have found section 2.3. here (http://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/FAQ#Should_I_use_natural_or_log_scale_data_for_GSEA.3F)

and also the below explanation in https://www.gsea-msigdb.org/gsea/doc/GSEAUserGuideFrame.html?Preparing_Data_Files "GSEA works with expression data from any source. Although different processing methods produce different types of expression values (for example, natural scale versus logged expression levels for Affymetrix data, or Affymetrix data versus two-color ratio data), any type of expression values can be used to create your expression dataset file. The GSEA algorithm examines the differences in expression values, rather than the values themselves. (As in most data analysis methodologies, the same expression data represented in different formats may, of course, generate different analysis results.)"

To my understanding, there should not be a strong difference although they used natural scale expression levels.

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