Build pathways out of your Phosphoproteomics data with PhosphoPath!

I just downloaded this and I'm digging for something cool to feed it. This is free, easy to use, software for analysis of your phosphoproteomics data!  And it runs through Java, so it should be accessible to just about everybody!

Did you just jump up out of your chair and yell a happy profanity? Or was that me?

It seems too good to be true to me, but I sure have a JAR file, and an instruction manual, and a practice dataset that I downloaded here.

It is described in this new paper (sorry, paywalled, I can't read the whole original paper yet either...) in JPR from Linsey M. Raaijmakers et al.,

If you get to check it out first, I'd love to know your impressions. I had a weird Java permissions issue (probably me and my PC settings) and I had to "unblock" the .JAR file, but I almost always have to.

Proteome "phasing" revealed by transcriptomics!

Okay....want a reason for a whole lot of those unmatched spectra in your human LC-MS/MS runs?

Check out this paper in Nature Biotechnology from Hagen Tilgner et al.,!  In this study they used transcriptomics (in this case, long-read RNA-Seq) and looked at different tissues. Turns out there is splicing everywhere!

Splicing? Well, that's when DNA that should be over here making this protein -->
ends up hanging out
with DNA
that's way over here -->
(who says blogging can't be hi-tech!)

and you end up with a transcript (and therefore a protein!) that, from a purely DNA perspective, TOTALLY SHOULDN'T EXIST AT ALL! (Definitely isn't in Uniprot/Swissprot...!)

Sorry for shouting.  I'm excited. This paper focused on mouse brains and found a whole ton of these things. In regards to some of the recent discoveries in brain proteins, maybe this isn't that big of a deal, but tissue-wise, holy cow....should we be using a different FASTA file if we are profiling liver tissue than if we are doing tissue that came from brain samples?  Sure looks like it!  Heck, if nothing else, its another great argument for PROTEOGENOMICS!  (Yeah, I'm shouting again!)

Worth a read. Sorry it isn't open access. And sorry if this is jumbled. Its kind of late and I've been excited about one thing or another for the last couple of days.

Assessment of longitudinal interlab variability

This one is pretty cool .

What happens when 64 different labs submit BSA samples that they run every month for 9 months and people sit down and assess the data?  Sounds like an ABRF study to me!

As we've come to expect, intralab variability (same lab over the 9 months) was smaller than interlab variability (from one place to another...I get them mixed up). That makes sense.  My LC my mass spec, I'm going to keep it pretty consistent for 9 months, compared to the way I run it versus those wackos over at Whats-It-Called University.

Variability among all the samples really doesn't look all that bad. It his, however, a single protein digest -- so we'd kind of expect that. Sampling of 100,000 peptides from a normal mammalian line might be a more sensitive indicator, but I still think this is a promising measurement.  As a field, we're getting better all the time!

Interestingly, the real outliers seem to show up right after LC-MS preventative maintenance (PM). And this makes sense, too. If you've had your LC open and changed some thingies in it recently then peakwidths and retention times might have shifted a bit pre- and post- opening it.  Sure does emphasize the frequent use and recording of quality control standards, particularly after maintenance and things.

Oh yeah, and this paper is currently open access in early release format at MCP here.

70- Surprise Eggs ! Kinder Surprise EggS Cars 2 Barbie Mickey Mouse Sur...

Can you use the SMART digest kits for proteomics?

Okay, y'all know I've been trying to find a good, easy, and reproducible protein digestion method to get behind. And I've mentioned the SMART (previously Perfinity FLASH) digests kits before. The big question that is floating around is: it works for single proteins just fine, but how well does it work for proteomics?

According to this paper it works pretty darned well. Now, this is just one paper and all, but I really can't come up with a reason that a method that digests one protein wouldn't digest a whole bunch of 'em and do it well (so long as the protein to enzyme ratios aren't all wonky).

Sure, its N=1, but it sure looks like it works!

First impressions of the free LFQ node from OpenMS

Over the weekend I got to finally toy around with one of the cool free nodes from the Kohlbacher lab that we can install into Proteome Discoverer 2.0.  The LFQ is short for "Label Free Quan" and the nodes are freely available to download for anybody here.   Now, before I go forward I should probably reiterate something that is on that page. These are 2nd party nodes and these won't be supported by Thermo's Proteome Discoverer team. Questions should be directed to the node developers. Fortunately, they seem quite straight forward!

Here are some early impressions of the nodes.

1) They are easy to install. Download the file from SourceForge, make sure all Proteome Discoverer versions on the PC are closed and run the file.  When you reopen, the nodes are there!

2) The node developer's even have workflows ready for us! There is a Processing Workflow and Consensus Workflow. Which is great! Cause, honestly, I wouldn't have thought to set them up as above....

3) Interesting note.  SequestHT and Percolator are mandatory. Gotta have 'em or you won't go anywhere, it seems.

4) LFQProfiler appears to multithread.

Windows performance loggers are always kind of hard to interpret, but all 8 cores on this desktop appeared to be doing something when the LFQ Profiler kicked in.  In the consensus you can actually tell that LFQ node how many cores it is allowed to use!  On other runs, it looked like I was maybe only using 4 cores, but this really isn't a good measurement.

5) Disclaimer here: I've got like 10 versions of Proteome and Compound Discoverer on my desktop because I have been alpha/beta testing them for years. I've got some versions that are locked down for different projects so my working environment is probably sub-ideal. But... I'm gonna be honest here, and I'm likely doing something wrong, but I'm finding the node a little difficult to integrate into my workflows, in an odd way. I keep getting "Execution failed" in my Administration tabs, but the failed workflow can be opened and looks just fine. I do have to unhide my Intensity but the numbers are here and it looks like it ran real fast!

So...first impressions. The LFQ node installs easy, has convenient pre-made workflows (additional downloads required) and seems to run fast. More analysis required to see how it works, but its Sunday and this is all the PD I think I'll do today!

UPDATE: 12/2/15.  Downloaded the LFQ nodes and they are AWESOME!!!

66- Surprise Eggs ! Kinder Surprise EggS Cars 2 Barbie Mickey Mouse Sur...