[BioC] positively correlated genes

[Sindre Lee]

Can I please ask how to interpret this results? Im used to Spearman/Pearson correlations and don't quite know how to present or explain the results obtained this way.

I wanted to find genes correlating with gene X. Then I got about 6000 significant genes at p < 0.05. Some with negative some with positive log2FC.

Now, what do I do? What does this tell me?


Thank you!


________________________________________
From: bioconductor-bounces at r-project.org <bioconductor-bounces at r-project.org> on behalf of Gordon K Smyth <smyth at wehi.edu.au>
Sent: 10 September 2014 03:08
To: deepaksrna at gmail.com
Cc: Bioconductor mailing list
Subject: [BioC] positively correlated genes

If you are using edgeR's glmFit function or limma's voom and lmFit
functions, you can simply add the log-expression values of the gene of
interest as a column of the design matrix.  Then a standard DE analysis
will detect any other genes that are significantly correlated with the
gene of interest.

Gordon

> Date: Tue,  9 Sep 2014 01:41:14 -0700 (PDT)
> From: "karthik [guest]" <guest at bioconductor.org>
> To: bioconductor at r-project.org, deepaksrna at gmail.com
> Subject: [BioC] positively correlated genes
>
> hi
>   I am interested to find out the genes that are positively and
> negatively correlated genes with my genes of interest. (using rnaseq
> normalized expression data). Can some one suggest me a better option.
>
> Thank you
>
> -- output of sessionInfo():
>
> sessionInfo()
> R version 3.0.2 (2013-09-25)
> Platform: x86_64-w64-mingw32/x64 (64-bit)

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