is it possible to before and after batch effect removal from the data and see that batch effect removal actually worked
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amoltej ▴ 10
@amoltej-7192
Last seen 4.0 years ago
Australia

Hello everyone, 

I am using SVA for batch effect removal. I would like to know if it is possible to find out that batch effect removal procedure has actually worked and now there is no batch effect? or simply to visualize data before and after batch effect removal and see how data has transformed?

Thank you for your time

Amol

combat sva batch effect comba • 789 views
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@manimaran_1975-8939
Last seen 5.6 years ago
United States
Hi, That is exactly where the Shiny App R-Package tool BatchQC is useful. http://bioconductor.org/packages/BatchQC Best, Mani From: amoltej [bioc] [mailto:noreply@bioconductor.org] Sent: Tuesday, November 8, 2016 7:47 AM To: manimaran_1975@hotmail.com Subject: [bioc] is it possible to before and after batch effect removal from the data and see that batch effect removal actually worked Activity on a post you are following on support.bioconductor.org<https: support.bioconductor.org=""> User amoltej<https: support.bioconductor.org="" u="" 7192=""/> wrote Question: is it possible to before and after batch effect removal from the data and see that batch effect removal actually worked<https: support.bioconductor.org="" p="" 89192=""/>: Hello everyone, I am using SVA for batch effect removal. I would like to know if it is possible to find out that batch effect removal procedure has actually worked and now there is no batch effect? or simply to visualize data before and after batch effect removal and see how data has transformed? Thank you for your time Amol ________________________________ Post tags: combat sva, batch effect, comba You may reply via email or visit is it possible to before and after batch effect removal from the data and see that batch effect removal actually worked
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@vegard-nygaard-6284
Last seen 19 months ago
Norway

Hi Amol.
 
I would argue that in practice it is difficult to remove the batch effect and end up with a completely batch effect free data set. A batch effect removal tool must before removal somehow estimate the batch effect. This estimate has an estimation error, and when the estimate is removed from the data the estimation error will take its place and may likewise act as a batch effect. This can be hard to detect in a real setting, but in a simulation study this can be directly observed by comparing the adjusted data with the "true" data.

I find that plotting (PCA, clustering) the data after adjustment is useful in order to inspect if the samples cluster mainly by biology as long as this grouping by biology information was not used in the batch effect removal. When batch and biological group (assuming there is one) are severely confounded, the "after" plot may be misleading if the same information is used in both the batch removal and the inspection plot. I observed this problem using simulated data and comparing what the plots indicated (PCA, Hierarchical Clustering, PVCA) with what I could deduce looking at the difference between adjusted data and "true" data.

I found the simulations so useful that I made a shiny app for it which you can test here:
https://vegard.shinyapps.io/batch-adjustment-simulator  (read help)

vegard

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