Best protein imputation method when comparing knock-outs?
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7 weeks ago

Dear all, We performed a gene knock-out and we are analyzing proteomics mass-spectrometry label-free (LFQ) data. For the imputation usually I use MissForest. However, the knocked-out protein is not identified as differential (limma).

Indeed the imputation of the knock-out samples leads to the assignment of values similar to the wild-type ones. I believe that this happens when all the 4 replicates have NA values (because knock out).

Do you have any suggestion for a better imputation method that can handle this issue/case?

imputation proteomics mass-spectrometry MS LFQ • 311 views
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Entering edit mode
7 weeks ago
KABILAN ▴ 130

You can try the R package named lfproQC which will give you the suitable combination of normalization and imputation method for your dataset out of three methods in each. It's also available as a Shiny app at https://dabiniasri.shinyapps.io/lfproQC/.

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