p values don't match up

Question: p values don't match up

4.1 years ago by

United States

A college of mine run an RNA-seq analysis using Galaxy a couple of years ago.

I used the same datasets to run a new analysis - and even though the list of genes generated was identical, I found discrepancies in the number of genes detected as significant (his dataset had more than a thousand significant hits, while mine had a handful).

When I looked closer to each dataset I discovered that the values were different in the two sets while p values and q values were recorded as ''0'' for the older dataset. I was wondering why this is the case.

For example:

OLD DATASET:	chrom location:	Sample1:	Sample2:	status	value1	value2	log2 fold change	test-stat	p_value	q_value	significance
Npy	chr6:49822728-49829505	WT NaV1.8 DRG	V600E NaV1.8 DRG	OK	0.367901	692.945	10.8792	-12.1069	0	0	yes
NEW DATASET:
Npy	chr6:49822728-49829505	WT	V600E	OK	0.497657	878.635	10.7859	15.1569	0.0268	0.642657	no

rna-seq • 955 views

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modified 4.1 years ago by Jennifer Hillman Jackson ♦ 25k • written 4.1 years ago by mariel.voutounou • 0

4.1 years ago by

Jennifer Hillman Jackson ♦ 25k

United States

Jennifer Hillman Jackson ♦ 25k wrote:

Hello,

This is most likely due to a change in the underlying tool versions or possibly a parameter change as well. Most tools in the pipeline have been upgraded in the last few years. Some have completely revamped algorithms, others mostly added new parameters. If you have the original prior workflow or job, when you try to execute it or "re-run", Galaxy will provide a warning for each tool that has a upgraded version available (some older versions may still be present, or you may be required to upgrade - if you wish to work on the Main public instance at http://usegalaxy.org).

We do not keep all versions indefinitely on Main. But, the Tool Shed is a great archive of prior tools/versions http://usegalaxy.org/toolshed. These would be for use in a production local/cloud Galaxy.

To exactly duplicate a run, based on nearly every factor, use the same exact tool versions, wrappers, and input data (including reference data). This can be done quite effectively on a CloudMan Galaxy with minimal set-up. With this option, a saved copy of the analysis could also be retained now going forward, for exact reproducibility later on, that you have full control over. Please note that Amazon has a grant program to help with costs.
http://usegalaxy.org/cloud

Hope this helps! Jen, Galaxy team

ADD COMMENT • link written 4.1 years ago by Jennifer Hillman Jackson ♦ 25k

Dear Jen,

Thank you for your reply. I have done (as you recommended) a re-run of the analysis - I found the same results as my newest run -but i am still unsure about the parameters that you are referring to.

Is it possible to know what these upgrades where? Is it the number of base pairs that are detected/ is it something else? How stringent are the detection parameters? What do you consider as a hit? etc

What are the newer algorithms used to detect significance and why is a gene for example that looks like its up-regulated 800 fold shown as non-significant?

I believe that its absolutely imperative to understand what these parameters are so that I can better interpret my data.

I am looking forward to your reply,

Kind Regards, Mariel

Mariel Voutounou, Ph.D. Burke Medical Research Institute, Department of Neurology & Neuroscience, Weill Medical College of Cornell University, 785 Mamaroneck Ave, White Plains, NY10605 Tel:(914) 426-3682

ADD REPLY • link written 4.0 years ago by mariel.voutounou • 0

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