ProteoSuite. Friendly free tools for quan!

There is a lot of proteomics software out there.  And...some of it is great!  This leaves a window open for people to write more stuff...hopefully great stuff!

ProteoSuite is a new package.  Why would you want to use this one when there are so many accepted free programs out there?  Actually, I don't know...

Wait!  I have a reason.  The TPP is imposing.  Sorry, it is.  Is it powerful?  Absolutely.  Is it easy for someone who has never done this stuff to start running on it?  No.  It is not (again, sorry, I seriously love you guys but if you are a biologist who just wants to re-assess an existing dataset this is not the tool you want to use.

MaxQuant isn't that much better, honestly.  Yes, I know there are tons of resources to get going.  Videos and publications and we all know how good that software is.  But you aren't going to download MaxQuant this morning and have quantitative data processing while you are at lunch.

ProteoSuite aims to bridge that gap with a friendly interface.  Check out how big the arrows are that they use!

ProteoSuite is still in development, but tutorial videos are on the site.  Example data sets are on the site.  ProteoSuite is putting accessibility and ease of use at the forefront.  And there is room in the open source quantitative proteomics world for that.

You can check out ProteoSuite here.  They are encouraging beta testing and looking for feedback.  If you decide to help them out, please post some of your feedback here somewhere.

Biotechniques article on the human proteome drafts

Yesterday's issue of BioTechniques had an interesting article on the human proteome drafts.  The best part of the article is a quote from Neil Kelleher that really puts this accomplishment in perspective.

You can check out the article here.

Tornadoes don't like metabolomics?!?

Today's iORBI in Indianapolis was interrupted by a tornado that touched down nearby.

Fortunately, I understand it only interrupted a talk on metabolomics.  :)

Protein isotope envelope fingerprinting

A concept I was introduced to at ASMS is isotope envelope fingerprinting.  Some research on this topic revealed that the idea isn't exactly new (just another new one to me!).  The idea is that under certain conditions the number of charges that a protein accepts as well as the masses within the "convoluted" isotope envelope would be enough for a protein ID.

It makes sense on some level, right?  I've ran the Waters IGg standard dozens (hundreds?) of times in my life, and it pretty much always looks the same.  The fans of isotope envelope fingerprinting want to exploit this and leave MS/MS for other assays (or for confirmation).  My guess is that it would be fine unless we are looking at complex things.  I can easily pull the 5 proteins in my normal intact/top down mix apart by just their envelope, but I would love to see data on complex runs.

Protein Goggle is a program that can be used to compared IEFs (not to be confused with IEF...sigh....).  If you're an academic researcher, you can get Protein Goggle for free to check it out.  If you're me, you probably wouldn't have time to try it out anyway!

The interface looks pretty straight-forward.

You can read more about this concept and the software you'd need for doing this type of analysis here.

GOAT -- Take the guesswork out of gradient optimization

This is pretty cool.

You can go back through this blog and find page after page of ramblings I have had on optimizing LC gradients to match your dynamic exclusion or your cycle time or your column length.

What if a sweet open source program could knock out some of those variables for you?!?!

Enter GOAT!  Automated gradient optimization!  Give GOAT some details about your sample and it'll build you an optimal gradient for your experiment.  Does it work?  Comparing a GOAT optimized gradient vs a non-optimized gradient for a HeLa digest on an Orbitrap Elite showed a 10% boost in peptide IDs!

You can read more about GOAT here.

PEFF -- A new proposed database format

I happened across a cool poster on PEFF, a new proposed database format.  Why would we want something like that?  Well, maybe we'd like to be able to look into our FASTA entry and see where it originally came from or when it was curated.   This would be particularly useful when studying an organism with an on-going sequencing project.

To find out more about PEFF, follow this link to the Proteomics Standards Initiative page.

Free Preview for everybody!

This is exciting!  I've previously went on and on about how much I like the Preview program from Protein Metrics.  Heck, I like all the programs I've tried from Protein Metrics (even the ones I haven't told you guys about yet).  

What could make Preview better?  What if it was free?!?  Now it is!  That's right.  The stand-alone Preview node is now being given away for nothing.

Even better than that?!?!?!?  If you have Proteome Discoverer you can also get the Preview node for free!  For more information, check out this press release!

Physikron: Algorithms to boost shotgun coverage?

I have several sheets of paper on my desk listing things to tell you guys about from ASMS.  This one is first because I got coffee on the sheet its on and I was afraid I wouldn't be able to read my notes later...

Physikron is a pre-processing program.  Your RAW data goes to Physikron, it does proprietary magic and then you give the files to your search engine.  Why on earth would you do this?

82% boost in proteins ID'ed?!?!?!?!

This is pretty unbelievable.  In fact, I'd almost go right by this one.  But it has papers backing it up.  Now, I don't love giving my data to black box programs that are doing things I can't know about.  At the end, however, if I get more high confidence protein IDs, I can get over it.

You can check out Physikron at the website here.

ASMS final day!

Wow, Ben.  The blog has been pretty underwhelming during ASMS.  Yes, I've had my hands full.  But I have so many cool things to tell you guys about.  There is no possible way that I will be able to test every piece of cool new open source software that I saw just yesterday before the next ASMS.  I'm working on prioritizing...cause there is just a ton to share!
 
Bear with me.  It all wraps up today.  My plan is to then sleep for 20 hours and return to what I consider normal.

At club quan

Mass spectrometry and techno?  Almost as cool as proteomics and death metal!!!

Top down quantitation?!?!?!

Top down proteomics is pretty cool, and the way that we all eventually want to go but a major drawback is that we can't quantify proteomic changes at that level, right?  Wrong!

In this new paper from Ioanna Ntai et al., out of the Kelleher lab, we get the description of global identification and quantitation of proteins from top down.  And it's automated.  How'd they do it?  I'm obviously tempted to say magic software (too bad they aren't a lab that makes their software commercially available sometimes, right?!), but the experimental design is really cool as well.

They started with a normal yeast background and spiked in some known standards as proof-of-principle.  They followed up with a cool yeast vs. yeast knockout strain and pulled out known proteins to shift when this gene is deleted.  Xtract was used for deconvolution, which essentially limited the upper level of the proteins to be quantified to around 30kDa and everything was backed up with cool statistics.

If you are interested in top down, I highly recommend this paper.  There is a poster at ASMS as well.  The App says tomorrow from 10:30 to 2:30; poster 157.

My ASMS badge

I've been wanting to see what all the vendors are doing, so I disguised myself yesterday!

Thousands of mass spectrometrists!

There are so many of us!!!!

Live from ASMS 2014

Over 1000 people got up for a 7 am meeting?  You mass spec people are hard core....

Extract injection time info from Fusion and QE files!

HaHa!  I have a solution to a question lots of you guys have asked!  RAW Meat, one of my favorite programs ever does not currently have injection time extraction ability from the Q Exactive and Orbitrap Fusion.  This has been a hang up for me for almost 2 years.

This month, my team hired a stellar new Scientist, Dr. Shan Randall, and he has a solution:  Xcalibur Query language!

It is described in this poster (you can find the direct link to the PDF here):

XQL can pull out all sorts of info from RAW files, and we've tested it on Fusion.  You can pull out the TICs and plot them vs scan number as we did to generate the image at the top of this post.  The language is command line driven for now, but it will get you this info!

Book is up on Kindle!

Last horn-tooting that I do on this project, I promise.  But I'm pretty psyched by how well this turned out.  It doesn't look perfect on my e-Reader, but it looks pretty good.  Found a typo...yay for copy editors!

Anyway, its up here.  It won't be appearing on Nook but Barnes and Noble will carry the paperback beginning in July sometime.  w00t!

PepFinder!!!

This is a piece of software I've been dying to talk about for the last 6 months or so.  Legally, however, I've just had to enjoy it myself and keep my mouth shut.

I know, there is a ton of software out there.  Why would I want to learn another package?  If you are interested in characterizing 1 protein, I've never seen anything that even comes close to PepFinder.

Highlights?
-You don't need an MS/MS spectra to make an ID.  MS1 for IDs, MS2 for sequence confirmation
-It can find your PTMs
-PepFinder can do error tolerant searches (find PTMs you didn't know about)
-It can find amino acid substitutions (ranks them in order of likelihood in your organism of interest, internally, and uses that data to score the sequence output.

You'll hear all about it at ASMS and you can read about it at the Thermo Omics Portal.

Proteome Discoverer Workflow: Level? God Mode!

Something I love about Proteome Discoverer?   Flexibility.  You can get awesome data with a simple workflow with just 4 nodes.  You can throw on an additional search engine if you want and get more data out of 5.  If you want something extra special?  Hell, you can build that, too!

Wanna see what PD is truly capable of?  Stop by Aimee Rinas's (from Lisa Jones's lab at IUPUI) poster at ASMS next week.  Aimee is building PD custom super workflows like this one above!

Almost ASMS time! Tips from a local!

Its almost ASMS time!

Since I've been around Baltimore (with some short interruptions) the last 11 years, I've been getting a lot of questions about the city.

Safety?  Yes, Baltimore is the #2 city for homicides/year in the U.S.  My suggestion:  During a drug transaction, particularly one involving heroin or crack cocaine, do not try to get ahead.  Know the fair market value for this purchase and stick to it.  Virtually all crimes in Baltimore are linked to drugs. Not involved in the drug trade?  You're going to be fine.
In all seriousness, most crimes in the Baltimore/DC area are "snatch and go" crimes where cellphones and tablets are grabbed from people's hands.  The inner harbor where ASMS will be is heavily policed for these crimes. In 11 years, I've never been mugged (in Baltimore), my car has never been broken into and I've never felt like I've been in danger.

Worth noting, particularly if you are from the West Coast or Europe.  In Baltimore, pedestrians typically DO NOT have priority in Baltimore.  The Harbor has many cross-walks and is pedestrian friendly.  However, 700 pedestrians in Baltimore were struck by cars in 2013.  Be cautious.

Quirks?
Baltimore is a quirky town.  It has its own dialect that is a little southern and a little made up.  Lifetime locals often skip a lot of consonants and drawl vowels together
Example:  "Baltimore"  proper pronunciation:  "Bawlmer"
"Oil" will be pronounced "awl"
Sentences often end in the word "Hon".  Its a term of endearment.  The first day of ASMS actually coincides with Hon-Fest, a celebration of Baltimore culture.  If you want to immerse yourself in Baltimore culture, sneak out on Sunday and go (its in my neighborhood)

Food?
Baltimore is a GREAT food town.  The inner harbor is mostly corporate restaurants with amazing views of the water.  Want amazing Italian?  Little Italy is a 15 minute walk (or 5 minute Uber) from the convention center.  You can find virtually any food from any culture in Baltimore.  One of my favorites in the Harbor?  La Tasca Spanish restaurant.  Beautiful views of the water.
If you get a chance, have some Baltimore blue crabs!  There's nothing like them!  And a 'Natty Boh' (National Bohemian beer, great, and $1.50 at a lot of bars, though I have paid as much as $3 for one in the Harbor...)

Transport?
The Charm City Circulator is a free bus service, particularly set up for tourists!  See the sights of Baltimore for free!
Uber is BIG and cheap in Baltimore.  Lyft is also picking up steam.  I always use Uber, and rarely if ever use other cab services.  My personal preference.

Cool stuff near ASMS?
The National Aquarium
Edgar Allen Poe's house and grave
The Visionary Art Museum
The World Trade Center (get a great view of all of Baltimore for (I think) $4 "Top of the World"
Other ideas?  Check out this "50 free things to do in Baltimore" article.

This town is FUN!!!  See you there!

MSAmanda -- the algorithm is now out and published!

If you've been reading the blog for very long, you know that I'm a big fan of MSAmanda.  I'm psyched to announce that the paper describing the algorithm is now available here via JPR.  The Venn diagram above shows the power of MSAmanda vs Sequest and the top secret Mascot algorithm.

I'm not knocking Mascot, but I sure do prefer publishing on algorithms that we can refer to!  Particularly when they are free and they get me better results.

New stuff from the paper?  There is a stand-alone MSAmanda!  And they did some searching vs. low res MS/MS spectra and MSAmanda did very well.  So, not only for high res MS/MS now!

Sneak peak -- new accessory for Orbitrap Fusion!!!

Breaking news with ASMS coming up -- a new add on for your Orbitrap Fusion!!!

The Marketing release!

Orbitrap Fusion Tribrid  even helps Spiders with their everyday lab work

9 out of 10 Spiders want an Tribrid Fusion

Forget ABIRD use the New Spider Source for background ion reduction

Keep that source clean with our new large mass particulate filter provided by Mother Nature

Tribrid Fusion with Spidey sense ion detection

So stable even Spider feel at home with it…

Thanks to an anonymous reader who sent this to me and put this together.  I've been in this lab.  It is pretty tidy.  That spider had some serious skills to get in there.

Weighing the World: Why Mass Spectrometry is Changing How We Do Everything

WOOOOHHHOOOOOO!!!!!

This has been a big month for me.  Another project is successfully off my desk and I don't have to think about it anymore!

My new book:  Weighing the World:  Why Mass Spec is Changing How We Do Everything was just launched on Amazon.  Currently, only the paperback is available, but the Kindle versions will be up soon (only for color Kindle readers, unfortunately, I think...I have to read more of these emails...) and it will also be distributed by Barnes and Noble (possibly also available via Nook, though I'm not 100% on that one....)

The book isn't really for you guys (my audience of expert mass spectrometrists!).  It is intended for people outside of the field.  Its a pop-sci look at where mass specs are right now, an overview of how they work, and a short summary of loads of different types of research that we do on them.  As such, I kept it pretty simple (heck, I don't even talk about isotopes until one of the last chapters)

I picked a lot of my favorite papers from the last 5 years or so and talked about:
The mass spec on Curiosity
Forensic applications
Atomic mass spec
Phosphoproteomics of the brain
Drug discovery
Proteoisoforms
How the railroads are using mass specs

I started this project almost 3 years ago and was pretty tired of looking at it, lol!

I'm not super-psyched about the Amazon front page for it, but you can check it out here if you want.

Normalized collision energy calculation for Q Exactive

I get this question all the time.  And I got the answer when I was in Bremen 2 summers ago, and always mean to put it up here:

Q:  What is the formula the Q Exactive uses for normalizing the collision energy?  Or how do we go from a NCE setting to the actual electron volts used for each fragmentation?

I'm going to give you the equation and explain it as I understand it (I'm a biologist, so chill out):

The formula:

Absolute energy (eV) = (settling NCE) x (Isolation center) / (500 m/z) x (charge factor)

Charge factors are as so:
Charge/charge factor
2/0.9
3/0.85
4/0.8
5/0.75
>5/0.75

So.... if you set the QE to do a NCE of 40 and you hit a 1,000 m/z ion with a charge state of 1
(40) x (1,000)/500 x 1 = 80 eV

Now, this was the equation for the original QE and good for the software version that was out 2 summers ago (August,2012).  I can't speak to how this equation has been adjusted or changed for new software versions or for the QE Plus, but it at least gives you a good idea, right?

Human proteome maps part 2: Digging deeper into ProteomicsDB

Wow.  The readers have spoken.  In 6 short days, my comparison of the 2 human proteome maps is already my 3rd most popular post of all time.  You can read part 1 here.

Yeah, cause I totally needed more reasons to explore these huge releases in my field!  What better thing to do on a long train ride this early morning?  For now, I think I've shown you all that the Human Proteome Map.org can do, but we've really only scratched the surface of what resources are available from ProteomicsDB.

To start off, I'm going to Browse Proteins.  And I'm not letting the Kuster lab off easy this time.  Let's see how they do with Integrin Alpha 5 (one of my favorite proteins and a nasty one to work with via mass spec. Membrane....ewww...)

First off.  It found it!  As well as isoforms.  Man, I love this thing....  I'm going to stick to full length isoform 1.  This is the summary page.

The chromosome it's on!  All the IDs!  Graphical maps of the peptide coverage, GO and links.  I'm a little confused by the illustration...probably a place the Kuster lab was slacking.  Guess I'll click on it just in case...

...oh...its DOMAIN MATCH maps!?!?  With confidence statistics.  This is via a page called SMART:  the Simple Modular Architecture Research Tool.  Something to investigate later. Next tab:

Okay!  Finally something that us normal human beings can do.  Assemble a sequence coverage map.  Did I mention that this protein sucks to work with?  From this map, you might not believe me though...

Next tab!  Whats a protease map?

Definitely click on this one to expand it.  It theoretically digests your peptide.  Big deal, the Protein Prospector has been able to do that for 20 years.  The metrics are pretty cool, though.  You pick the enzyme you want from the ones available (user customizable enzyme might be nice; minor suggestion) and it does the digest.  Hover over the map and the sequence appears in a little bubble.  The mouse obscures it a little, but it's there.  The cool thing is the % theoretical in the lower right hand.  I was pretty psyched the other day about manually calculated % theoretical coverage, and this thing does it automatically (so does X!Tandem, I'm told).  Nice to have all these features in one place!

Next tab.  Proteotypicity?

I choose iTRAQ and hit the calculate button:

...and I get spectral libraries for iTRAQ labeled peptides from the protein.  Terminology is weird/confusing, but the data is incredibly thorough (see the cool black line at the front where the reporter ions are?)

In part 1, I showed you the expression maps. Let's skip to the Projects tab:

Nice cropping job...did I mention I'm on a train?  Anyway, this is another cool tab.  For example, Mendoza_JPR_2013 found 17 unique peptides from ITGA5.  If I want 15 peptides, I can click the PubMed link, go to the Mendoza paper, and use the method they used (its a membrane paper, btw).  I can follow the Project link and actually download all the RAW data files for that project.

I'm going to cut this short now.  The WiFi speed on this train has dropped dramatically and uploading these images has become a pain.  I hope that this give you some sense of the insane amount of work they have put into this resource for us.

PepExplorer -- multi-engine solution for de novo

What is the biggest problem with de novo peptide sequencing?  I think the consensus is definitely false discoveries.  There are some clever solutions out there.  PEAKS, in specific, has worked very hard over the last several years to develop and improve their FDR calculations, and to make those mechanisms public.

This new paper (currently in press at MCP, so open access) from Leprevost et. al., has taken a good hard swing at this problem and I really like their approach.

This paper introduces us to PepExplorer, a new algorithm that can compile the results of different de novo engines and compare them to help us get a feel for the confidence of our findings.  For example, if PepNovo+ and PEAKS (which are completely different algorithms) both give you high scores for a sequence identity (and, even better, it makes it through PEAKS FDR!) then we can be a lot more confident about that result.

I like the approach, but I can't speak to the software yet.  I'm pretty busy leading up to this ASMS thing.  If you happen to check it out, please post your opinions in the comments section.  Hopefully I'll get around to putting up my impressions later in the summer.

You can download PepExplorer here.

Scientific Data -- an awesome new journal!

Maybe y'all already know about this one, but it was new to me!

Nature has started a new journal that is solely for the description of cool data sets.  You know that experiment that didn't work?  The one where you ran the Orbi Velos for 3 months and didn't come up with a biomarker in those cell lines?

We need to do something with that data set!  Maybe that biomarker is a PTM nobody knew about!  If not, maybe just having it out there would stop me from trying that same experiment!  Better yet, maybe your n just wasn't big enough to successfully pull out the interesting stuff.  Maybe combining your "bad" data set with my "bad" data set would give us a big enough sample to get something really cool.

This journal is a BIG step in the right direction.  Lets get all this data out there!  And it's open source!

Another great one?

Hell yes!  I don't want to waste all my time doing experiments that you know don't work!  The impact factor is 1.1?  Who cares!  You publishing your stuff that doesn't work keeps other people from wasting their time.  And if somebody had published that experiment first then neither of you would have wasted your time!  We move forward.  Science moves forward.