Curation and ISA representation of a SARS-Cov2/Covid-19 Proteomics Dataset deposited in PRIDE database with accession number: PXD107710 ISA-Tab annotation for the "SARS-CoV-2 infected host cell proteomics reveal potential therapy targets" publication. Github repository: https://github.com/ISA-tools/PXD017710 This is part of an effort to (re-)annotate: https://dx.doi.org/10.21203/rs.3.rs-17218/v1 Additional work done as part of: https://github.com/virtual-biohackathons/covid-19-bh20 https://github.com/virtual-biohackathons/covid-19-bh20/wiki/FairData Proteomics data Available from PRIDE at https://www.ebi.ac.uk/pride/archive/projects/PXD017710 and [MassIVE/CCMS Maestro+MSstats reanalysis of MSV000085096 / PXD017710] ISA-Tab representation: Rationale: Demonstrate suitability of the ISA format for representing MS based protein profiling experiment with more granularity and details, thus providing a better representation of the experiment design. The formatting and re-annotation are based on information extracted from: - the original publication - the supplementary tables available from the publishers site - the 'filtered-results.csv' helper file as supplied to @sneumann during the HUPO-PSI meeting March 2020 Viewing the ISA-tab formatted and re-annotated PXD017710 with ISATab-Viewer Viewing the ISA-tab formatted and re-annotated PXD017710 locally, do the following: ```bash python -m http.server 8000 ``` Then point your browser to `http://0.0.0.0:8000/isaviewer-demo.html` Curation tasks performed: * initial structure of the study design in ISA format: * linkage of Proteome and Translatome data (supplementary material) to ISA assay tables (via Derived Data File) * processing the Proteome and Translatome data (supplementary material) with python pandas library to generate the following csv files: - proteome_intensities_long_table_ggplot2.txt - proteome_diffanal_ratio_pvalue_long_table_ggplot2.txt - translatome_intensities_long_table_ggplot2.txt - translatome_diffanal_ratio_pvalue_long_table_ggplot2 The files are `long table` corresponding to a `melt` on the Excel file originally generated by the users and can be readily loaded in R ggplot2 library for graphical representation. The statistical relevant elements have been annotated with the STATO ontology and the tables comply with a Frictionless.io Data Package. The jupyter notebook for the transformation is available. * conversion of raw data to mzML format: detailed in https://github.com/ISA-tools/PXD017710 install docker: ```bash >brew update >brew install docker ``` sign in to docker ```bash >docker start >docker login ``` pull docker container for ProteoWizard: ```bash >docker pull chambm/pwiz-i-agree-to-the-vendor-licenses ``` :warning: be sure to sign-up and login to https://hub.docker.com/ in order to be able to reach https://hub.docker.com/r/chambm/pwiz-skyline-i-agree-to-the-vendor-licenses run the pwiz tool from the container over the raw data: ```bash docker run -it --rm -e WINEDEBUG=-all -v /Users/Downloads/PXD017710/raw/:/data chambm/pwiz-skyline-i-agree-to-the-vendor-licenses wine msconvert /data/*.raw --mzML ``` * ontology markup for: * declaration of independent variables as ISA Study Factors:{biological agent, dose, time point, replicate} ->OBI * Taxonomic information (host cells and virus) -> NCBITaxonomy * Cell line: CaCo-2 cells -> Cell Line Ontology * Disease: Colon Cancer -> Human Phenotype Ontology * MS specific aspect (TMT reagent, instrument ... ) -> PSI-MS * Statistical Tests -> STATO Unresolved curatorial issues: 1. ambiguities related to Tandem Mass Tag labelling protocol - the publication mentions TMT11 (see Figure 2 in https://www.researchsquare.com/article/rs-17218/v1) - the information available from PRIDE mentions TMT6 (https://www.ebi.ac.uk/pride/archive/projects/PXD017710) This may require another round of annotation on the TMT agents and fractions in the ISA a_assay representation 2. SARS-Cov2 isolate: no clear NCBI Taxonomic anchoring and unclear origin: -> the markup is made to the parent class (as of 06.04.2020) Release and packaging as a BDBAG: The tgz file associated with this upload has been producing using https://github.com/fair-research/bdbag. It contains several manifest files detailing metadata and data files, providing md5 and sha256 checksums. Github repository: https://github.com/ISA-tools/PXD017710