Inquiry about suitable package for proteomics study design
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@15a92372
Last seen 14 months ago
Canada

Hello!

I have an inquiry about what package works best for my dataset since I find it a bit complex to understand.

I have a proteomics dataset; fish were exposed to 2 different drug treatments and a control, and each fish had its mucus sampled before exposure, 15 days after exposure, and 30 days after exposure (making it a repeated measures design). enter image description here

Effectively, there is control for the treatment (0mg, 5mg, 10mg), and for the time (Day 0, Day 15 and Day 30).

Additionally, the proteomics data I have is in the form of peak intensities- where the rows are protein names, columns are the samples and the cells contain peak intensity values

What package works best with such a proteomics dataset, since a lot of them are designed mainly for transcriptomics data?

Any suggestions and explanations are welcome, since I would like to learn and apply this further!

Thank you:)

Proteomics design • 1.3k views
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@james-w-macdonald-5106
Last seen 10 hours ago
United States

Contingent upon having no missing data, you can use limma. I usually exclude proteins with > 20% missing and then impute the rest, then use limma. An alternative if you don't want/can't impute is to use proDA.

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Thank you!

I was also reading on limma-voom, they suggest not using it on spectral count data, but is it okay to use on peak intensity data?

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I didn't say limma-voom. Just limma.

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You may need to use limma-trend if there is a relationship between the mean and variance of your intensity data, but that's up to you.

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evocanres • 0
@evocanres-17914
Last seen 11 months ago
United States

Use the excellent tutorial on Proteomic analysis

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