You'll find a lot of posts in here regarding Galaxy, particularly the GalaxyP project that is kind of centralized around my friends in Minnesota. Galaxy is a HUGE package in genomics research with tons of great tools and an amazing support community. More and more of these tools and researchers are thinking (quite logically!) that they should integrate proteomics, and we all stand to gain from access to these resources.
In a brand new paper in press at MCP, Jun Fan et al., demonstrate the usage of Galaxy tools for transcriptomics and how we can get better peptide identifications and improved protein inference by leveraging these tools versus our MS/MS spectra. I think that was a run on sentence. Who has time for grammar when you're this excited? Not me!
How'd they do it? Here is an interesting schematic stolen from the paper. Does it look convoluted? Of course it does! If it was simple, why would we even need bioinformaticians? Making it look complicated is job security. But when you break it down, it really isn't that bad.
What are the points I don't have in my typical workflows? Well, I have RAW files, I can search them, I've got FASTAs, and I can BLAST unmatched spectra (even the de novo ones, thanks to the new versions of Peaks and the de novo GUI). The only thing I don't really have here is the ability to make my transcriptomics data easily searchable. But they outline open source tools in the paper that do. Time to convert some variant call files to FASTA!!!
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