Big shoutout to Brett Phinney @UCDProteomics for this one! Diverting social media platforms for science!
Want to make sure you're using that label free quan algorithm correctly? Want to test that awesome new algorithm you're developing? Some awesome, expertly prepared and acquired samples might be exactly what you need. (PD 2.2 launch is just around the corner!)
This one is fantastic and described here!
My go-to is the Claire Ramus et al., dataset -- and the Shalit et al., dataset is pretty solid.
How do the 2 stack up?
Ramus dataset -- Yeast digest with Sigma UPS1 peptides spiked in -- ran in High/low on Orbitrap Velos
Shalit dataset -- E.coli complete digest spiked into HeLa -- ran on a Q Exactive.
The Shalit dataset is more complex, but with high resolution fragment ions, depending on where you bottleneck (searching versus peak alignment/extraction) it might search faster.
If I was running an LTQ Orbitrap and using high/low, I'd probably still stick to the previous dataset. If you're using high/high, the other might be a better test for you.
Best of all? Both datasets are publicly available! The link to the Ramus dataset is here (ProteomeXchange PXD001819)
You can get the Shalit dataset directly here (it is ProteomeXchange PXD001385)
These are very helpful, thank you!
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