diff --git a/webinterface/pages/DDA_Quant.py b/webinterface/pages/DDA_Quant.py index 91398185..22d3ff7c 100644 --- a/webinterface/pages/DDA_Quant.py +++ b/webinterface/pages/DDA_Quant.py @@ -74,7 +74,52 @@ def generate_input_field(self, input_format: str, content: dict): def _main_page(self): """Format main page.""" - st.title("Proteobench") + st.title("Module 2: DDA quantification") + st.header("Description of the module") + st.markdown(""" + This module compares the MS1-level quantification tools for + data-dependent acquisition (DDA). The raw files provided for + this module are presented in the comprehensive LFQ benchmark + dataset from [Van Puyvelde et al., 2022](https://www.nature.com/articles/s41597-022-01216-6). + The samples contain tryptic peptides from Homo sapiens, + Saccharomyces cerevisiae, and Escherichia coli, mixed in different + ratios (condition A and condition B), with three replicates of each + condition. With these samples, we calculate three metrics: + - To estimate the sensitivity of the workflows, we report the + number of unique precursors (charged modified sequence) quantified + in all 6 runs. + - To estimate the accuracy of the workflows, we report the weighted + sum of precursor deviation from expected ratios. + - To estimate the precision of the workflows, we report the weighted + average of the interquartile range (IQR) of the precursors ratio. + + ProteoBench plots these three metrics to visualize workflow outputs + from different tools, with different versions, and/or different + sets of parameters for the search and quantification. + The full description of the pre-processing steps and metrics + calculation is available here: LINK. + """) + st.header("Downloading associated files") + st.markdown(""" + The raw files used for this module were acquired on an Orbitrap + Q-Exactive H-FX (ThermoScientific). They can be downloaded from the + proteomeXchange repository PXD028735. You can download them here: + [LFQ_Orbitrap_AIF_Condition_A_Sample_Alpha_01.raw](https://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD028735/LFQ_Orbitrap_AIF_Condition_A_Sample_Alpha_01.raw) + [LFQ_Orbitrap_AIF_Condition_A_Sample_Alpha_02.raw](https://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD028735/LFQ_Orbitrap_AIF_Condition_A_Sample_Alpha_02.raw) + [LFQ_Orbitrap_AIF_Condition_A_Sample_Alpha_03.raw](https://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD028735/LFQ_Orbitrap_AIF_Condition_A_Sample_Alpha_03.raw) + [LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_01.raw](https://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD028735/LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_01.raw) + [LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_02.raw](https://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD028735/LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_02.raw) + [LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_03.raw](https://ftp.pride.ebi.ac.uk/pride/data/archive/2022/02/PXD028735/LFQ_Orbitrap_AIF_Condition_B_Sample_Alpha_03.raw) + + **It is imperative not to rename the files once downloaded!** + """) + st.markdown(""" + Download the fasta file here: [TODO] + The fasta file provided for this module contains the three species + present in the samples and contaminant proteins + ([Frankenfield et al., JPR](https://pubs.acs.org/doi/10.1021/acs.jproteome.2c00145)) + """) + st.header("Input and configuration") with st.form(key="main_form"):