question re mRNA expression (RNA Seq V2 RSEM)

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Ruppert, Mike

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Feb 19, 2016, 7:30:02 PM2/19/16
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I am new to RNA seq, is the mRNA expression data I downloaded representing normalized RPKM/FPKM?

 

I did not select the z score data, I selected the other option.

 

I understand the z score concept except I am not always sure what the reference is for the mean -- the exact same subgroup under analysis or all tumors in that study?

 

And when I select z score 1.5 as a cutoff, are tumors with mRNA downregulation therefore less than 1.5 SDs below the mean (i.e., z less than -1.5)?

 

Thanks much.

 

J. Michael Ruppert

Professor of Biochemistry

Jo and Ben Statler Chair in Breast Cancer Research

Room 212 Biomedical Research Bldg

1 Medical Center Dr

Morgantown, WV 26506

(304) 293-5246

 

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JianJiong Gao

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Feb 25, 2016, 6:01:11 PM2/25/16
to cbiop...@googlegroups.com, mrup...@hsc.wvu.edu
Thanks for contacting us.

The RNAseq V2 values are normalized TPM values by RSEM.

The reference population is all samples that are diploid for the gene in question.

If you select z-score 1.5, all samples with z-score below -1.5 or above 1.5 for the query gene will be considered as altered. You can also use Onco Query Language to do one-side query, e.g. "EGFR: EXP>1.5"

I hope this is helpful. Please let us know if you have any other questions.

Best,
-JJ

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weiz...@gmail.com

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Aug 23, 2016, 4:14:00 PM8/23/16
to cBioPortal for Cancer Genomics Discussion Group, mrup...@hsc.wvu.edu
Jianjiong;

 I got the gene expression values of the samples from firehose, including raw count, tau value (TPM / 10e6) and normalized count etc.  But, I cannot match RNAseq V2 values from cBioPortal with the TCGA firehose data, including the formula "normalized TPM values" by RSEM.  Could you describe how the values of "RNAseq V2" are calculated at cBioPortal?

In particular, I am looking for the gene expression comparison across multiple cancer types.  I need to figure whether it is proper to used the downloaded cBioPortal data directly or to apply certain normalization approach further to make them more comparable. 

Thanks,

Wei Zhu
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