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Get LFQ Values for fractionated data at protein level #140

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bressin opened this issue Jan 26, 2024 · 6 comments
Open

Get LFQ Values for fractionated data at protein level #140

bressin opened this issue Jan 26, 2024 · 6 comments

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@bressin
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bressin commented Jan 26, 2024

Hi,
I want to extract the protein LFQ intensities for fractionated data. I tried the sum but it appears to be wrong.

This paper (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563855/) states "FlashLFQ can normalize fractionated datasets by using a bounded Nelder–Mead optimizer [33] to find a normalization coefficient for each fraction, similar to MaxLFQ."

So I need to apply the normalization coefficient first to each fraction, but where are they listed?
I'm using the standard GALAXY output.

Best regards,
Annkatrin

@Alexander-Sol
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Hi Annkatrin,

The normalization coefficients are calculated internally when the "Normalize Intensities" option is selected. The reported protein intensities are derived from the normalized peptide intensities. There is no post-processing normalization required

@bressin
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bressin commented Jan 26, 2024

Here are my settings:
PsmIdentificationPath = "msms.psmtsv"
SpectraFileRepository = "./spectrum_dir"
Silent = false
OutputPath = "out"
Normalize = true
PpmTolerance = 10.0
IsotopePpmTolerance = 5.0
Integrate = false
NumIsotopesRequired = 2
IdSpecificChargeState = false
MaxThreads = -1
MatchBetweenRuns = true
MbrRtWindow = 2.5
RequireMsmsIdInCondition = false
BayesianProteinQuant = true
ProteinQuantBaseCondition = "Day5"
McmcSteps = 500
McmcBurninSteps = 1000
UseSharedPeptidesForProteinQuant = false
RandomSeed = 0

Hey, here are my settings. So to get the intensity for a sample with fractions I simply sum all intensity values?

@Alexander-Sol
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Could you share your experimentalDesign.tsv file?

@bressin
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bressin commented Jan 26, 2024

FileName Condition Biorep Fraction Techrep
Day5-F-G_SCX_X Day5 3 4 1
Day5-F-G_SCX_5 Day5 3 3 1
Day5-F-G_SCX_4 Day5 3 2 1
Day5-F-G_SCX_3 Day5 3 1 1
Day5-F-G_1D Day5 3 5 1
Day5-D-E_SCX_X Day5 2 4 1
Day5-D-E_SCX_5 Day5 2 3 1
Day5-D-E_SCX_4 Day5 2 2 1
Day5-D-E_SCX_3 Day5 2 1 1
Day5-D-E_1D Day5 2 5 1
Day5-B-C_SCX_3 Day5 1 5 1
Day5-B-C_SCX_X Day5 1 4 1
Day5-B-C_SCX_5 Day5 1 3 1
Day5-B-C_SCX_4 Day5 1 2 1
Day5-B-C_1D Day5 1 1 1
Day4-D_SCX_X Day4 3 5 1
Day4-D_SCX_5 Day4 3 4 1
Day4-D_SCX_4 Day4 3 3 1
Day4-D_SCX_3 Day4 3 2 1
Day4-D_1D Day4 3 1 1
Day4-C_SCX_X Day4 2 5 1
Day4-C_SCX_5 Day4 2 4 1
Day4-C_SCX_4 Day4 2 3 1
Day4-C_SCX_3 Day4 2 2 1
Day4-C_1D Day4 2 1 1
Day4-B_SCX_X Day4 1 5 1
Day4-B_SCX_5 Day4 1 4 1
Day4-B_SCX_4 Day4 1 3 1
Day4-B_SCX_3 Day4 1 2 1
Day4-B_1D Day4 1 1 1
Day3-D_SCX_X Day3 3 5 1
Day3-D_SCX_5 Day3 3 4 1
Day3-D_SCX_4 Day3 3 3 1
Day3-D_SCX_3 Day3 3 2 1
Day3-D_1D Day3 3 1 1
Day3-C_SCX_X Day3 2 5 1
Day3-C_SCX_5 Day3 2 4 1
Day3-C_SCX_4 Day3 2 3 1
Day3-C_SCX_3 Day3 2 2 1
Day3-C_1D Day3 2 1 1
Day3-B_SCX_X Day3 1 5 1
Day3-B_SCX_5 Day3 1 4 1
Day3-B_SCX_4 Day3 1 3 1
Day3-B_SCX_3 Day3 1 2 1
Day3-B_1D Day3 1 1 1
Day2-D_SCX_X Day2 3 5 1
Day2-D_SCX_5 Day2 3 4 1
Day2-D_SCX_4 Day2 3 3 1
Day2-D_SCX_3 Day2 3 2 1
Day2-D_1D Day2 3 1 1
Day2-C_SCX_X Day2 2 5 1
Day2-C_SCX_5 Day2 2 4 1
Day2-C_SCX_4 Day2 2 3 1
Day2-C_SCX_3 Day2 2 2 1
Day2-C_1D Day2 2 1 1
Day2-B_SCX_X Day2 1 5 1
Day2-B_SCX_5 Day2 1 4 1
Day2-B_SCX_4 Day2 1 3 1
Day2-B_SCX_3 Day2 1 2 1
Day2-B_1D Day2 1 1 1
Day1-D_SCX_X Day1 3 5 1
Day1-D_SCX_5 Day1 3 4 1
Day1-D_SCX_4 Day1 3 3 1
Day1-D_SCX_3 Day1 3 2 1
Day1-D_1D Day1 3 1 1
Day1-C_SCX_X Day1 2 5 1
Day1-C_SCX_5 Day1 2 4 1
Day1-C_SCX_4 Day1 2 3 1
Day1-C_SCX_3 Day1 2 2 1
Day1-C_1D Day1 2 1 1
Day1-B_SCX_X Day1 1 5 1
Day1-B_SCX_5 Day1 1 4 1
Day1-B_SCX_4 Day1 1 3 1
Day1-B_SCX_3 Day1 1 2 1
Day1-B_1D Day1 1 1 1
Day0-D_SCX_X Day0 3 5 1
Day0-D_SCX_5 Day0 3 4 1
Day0-D_SCX_4 Day0 3 3 1
Day0-D_SCX_3 Day0 3 2 1
Day0-D_1D Day0 3 1 1
Day0-C_SCX_X Day0 2 5 1
Day0-C_SCX_5 Day0 2 4 1
Day0-C_SCX_4 Day0 2 3 1
Day0-C_SCX_3 Day0 2 2 1
Day0-C_1D Day0 2 1 1
Day0-B_SCX_X Day0 1 5 1
Day0-B_SCX_5 Day0 1 4 1
Day0-B_SCX_4 Day0 1 3 1
Day0-B_SCX_3 Day0 1 2 1
Day0-B_1D Day0 1 1 1

@Alexander-Sol
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Thanks for providing that. What make you say that the values appear to be wrong?

Would it be useful if we provided the normalization coefficients as an output?

@bressin
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bressin commented Feb 8, 2024

If the intensities are already weighted I don't need the coefficients, but I think it would be still nice to report them somewhere. However, sometimes the summed LFQ values don't match the log2FC provided. Maybe it is worth checking.

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