yafeng / DEqMS

DEqMS is a tool for quantitative proteomic analysis
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spectraCounteBayes Warning messages #14

Open yudada2020 opened 4 months ago

yudada2020 commented 4 months ago

Hello, I have tried to analyse my label-free data by referring to the tutorial "DEqMS analysis using MaxQuant outputs (label-free data)", but when I run the code fit4 = spectraCounteBayes(fit3), R pops up a warning message. How can I fix it?

屏幕截图 2024-03-19 213815

Thanks, Nai xiang Yu

yafeng commented 4 months ago

@yudada2020 Hi, please check the input expression matrix if there are proteins with missing values. DEqMS requires at least two values for each group.

Yafeng

yudada2020 commented 4 months ago

Hello, Dr yafeng, I have used the code "df.LFQ.filter = df.LFQ[df.LFQ$na_count_H<2 & df.LFQ$na_count_L<2,1:34]" as per your suggestion to perform missing value removal for the protein expression matrix but the same error is reported. Interesting to be able to output seemingly normal results. Attached is my input protein expression matrix.

Thanks, Naixiang

test_LFQ.intensity.txt

longchung90 commented 2 months ago

Hi Yafeng, it is such a wonderful script, thanks for sharing with us.

I did encounter a problem when I run fit4 = spectraCounteBayes(fit3)

The error came out as Error in model.frame.default(formula = logVAR ~ x) : variable lengths differ in DeqMS (found for 'x')

Do you have any ides?

Thank you very much in advance! L

yafeng commented 2 months ago

@yudada2020 Hi, i checked your input data frame, you should use df.LFQ.filter = df.LFQ[df.LFQ$na_count_H<2 & df.LFQ$na_count_L<2,c(1,4:37)] (don't keep column 2, 3 ) and don't forget to do log2 transformation. protein.matrix = log2(as.matrix(df.LFQ.filter))

if you still encounter error, check the peptide count table, it should contains peptide count per protein.

Yafeng

yafeng commented 2 months ago

@longchung90 Hi, i suspect there are missing values in fit3$count, which stores the peptide count per protein. Try min(fit3$count) to see if all proteins have valid peptide count. If it returns NA, then one of your proteins contains NA for peptide count.

Yafeng

yafeng commented 2 months ago

@longchung90 Hi, i suspect there are missing values in fit3$count, which stores the peptide count per protein. Try min(fit3$count) to see if all proteins have valid peptide count. If it returns NA, then one of your proteins contains NA for peptide count.

Yafeng