Iām re-starting the proteomics subgroup to develop a GeneLab consensus pipeline for processing proteomics data hosted on the OSDR. We will meet on the second Wednesday of each month starting on Wednesday, June 12th at the following times: 2-3pm PT | 5-6pm ET | 9-10pm GMT | Thursday 7-8am AEST (Melbourne).
If you are interested in joining this sub-group, please add your information to the table in the Proteomics_AWG_Subgroup_Members google doc.
Some people who may have experience and valuable input @Oracle009 @mmarto3 @mjr5770 @vinita.chauhan @ojaskulkarni5 (listed proteomics among their interest/expertise)
Look forward to attending with some of my team, we make LFQ analyst for data visualisation but as a facility we process and analyse every type of proteomics experiment (internally we work with prettt much every package, pipeline and data type) 
https://analyst-suites.org/
The top contenders for a universal type -processing pipeline- would be nf-core, msfragger based, or ms stats based, allowing interoperability.
I.e. universal inputs ideally, there are tools that can handle all types of inputs but choice of consensus types: LFQ, TMT, DIA, Silac, ITRAQ, Phos or PTM based integrations with or without matched total proteomes. Im not sure if anyone has done any interactomes
The question is whether one would also want the multi-layered data integration. I.e. proteomics, metabolomics, transcriptomics, methylomics, metap/g and functional integration. There are a couple of JS front ends than run python under the hood.
I know there are fecal samples from missions but i havent checked matching proteomics datasets on the repository, the integration of meta proteomics visualisations is a more complex thing, a few tools like iMetalab is a complete tool offering end to end processing and visualistion but some other more packaged pipelines exist now.
I will assemble a list as i have a few students who work in this space and our bioinformatics team have been considering flipping everything we do into a more a-synch environment. The issue here is that i know R and Nasa arent the best of friends for the OSDR website, but i guess it doesnt need to be r to vis. @asaravia @MultiOmicsAWG
Heard you all met! Exciting progress!
@asaravia @joel.steele Hossein Fazelinia @mjr5770 @vinita.chauhan @sudip.sharma.temple @terry.lim @barbara.novak @GabGoncalves @mohammadreza.dorvash also those not in here yet: Debbie Chong, Hailey Zhang, Hossein Valipourkahrod
Hello! I see this was posted in May. Is there any work left? Can I join? I am happy to put my information in the Google Doc.
Hello to you.
I think we can tag @asaravia for more info.
Hi everyone, @joel.steele,
To add to the metadata discussion, we were wondering about lipidomics data. Presumably, it has some assay-specific metadata not shared with either metabolomics or proteomics, but do those differences influence the processing pipeline? And if so, which metadata differences would be important to track?
thanks!
Barbara