topdownr is free and open-source software. If you use it, please support the project by citing it in publications:
P.V. Shliaha, S. Gibb, V. Gorshkov, M.S. Jespersen, G.R. Andersen, D. Bailey, J. Schwartz, S. Eliuk, V. Schwämmle, and O.N. Jensen. 2018. Maximizing Sequence Coverage in Top-Down Proteomics By Automated Multi-modal Gas-phase Protein Fragmentation. Analytical Chemistry. DOI: 10.1021/acs.analchem.8b02344
For bugs, typos, suggestions or other questions, please file an issue
in our tracking system (https://github.com/sgibb/topdownr/issues)
providing as much information as possible, a reproducible example and
the output of
If you don’t have a GitHub account or wish to reach a broader audience for general questions about proteomics analysis using R, you may want to use the Bioconductor support site: https://support.bioconductor.org/.
topdownrData Generation Workflow
To create methods the user will have to install and modify Orbitrap Fusion LUMOS workstation first:
TribridSeriesWorkstationSetup-v3.2.exefrom Thermo Scientific.
XMLMethodChanger is needed to convert the xml methods into
.meth files. It
could be found at https://github.com/thermofisherlsms/meth-modifications
The user has to download and compile it himself (or request it from Thermo
Scientific as well). You would need at least the 3.2 beta version.
In order to use XMLMethodChanger the operating system has to use the
as decimal mark and the
, (comma) as digit group separator (one thousand dot
two should be formated as
In Windows 7 the settings are located at
Windows Control Panel > Region and Language > Formats.
Choose English (USA) here or use the Additional settings button to change it
After data aquisition
topdownr would need the header information from the
Therefore the ScanHeadsman software is used. It could be
downloaded from https://bitbucket.org/caetera/scanheadsman
It requires Microsoft .NET 4.5 or later (it is often preinstalled on a typical modern Windows or could be found in Microsoft’s Download Center, e.g. https://www.microsoft.com/en-us/download/details.aspx?id=30653). Additionally you would need Thermo’s MS File Reader which could be downloaded free of charge (but you have to register) from the Thermo FlexNet website: https://thermo.flexnetoperations.com/
ScanHeadsman was created by Vladimir Gorshkov firstname.lastname@example.org.
Importantly, XMLmethodChanger does not create methods de novo, but modifies pre-existing methods (supplied with XMLMethodChanger) using modifications described in XML files. Thus the whole process of creating user specified methods consists of 2 parts:
.methfile to XMLmethodChanger.
We choose to use targeted MS2 scans (TMS2) as a way to store the fragmentation parameters. Each TMS2 is stored in a separate experiment. Experiments do not overlap.
Shown below is the process of creating XML files and using them to modify the TMS2IndependentTemplateForTD.meth template file.
library("topdownr") ## Create MS1 settings ms1 <- expandMs1Conditions( FirstMass=400, LastMass=1200, Microscans=as.integer(10) ) ## Set TargetMass targetMz <- cbind(mz=c(560.6, 700.5, 933.7), z=rep(1, 3)) ## Set common settings common <- list( OrbitrapResolution="R120K", IsolationWindow=1, MaxITTimeInMS=200, Microscans=as.integer(40), AgcTarget=c(1e5, 5e5, 1e6) ) ## Create settings for different fragmentation conditions cid <- expandTms2Conditions( MassList=targetMz, common, ActivationType="CID", CIDCollisionEnergy=seq(7, 35, 7) ) hcd <- expandTms2Conditions( MassList=targetMz, common, ActivationType="HCD", HCDCollisionEnergy=seq(7, 35, 7) ) etd <- expandTms2Conditions( MassList=targetMz, common, ActivationType="ETD", ETDReactionTime=as.double(1:2) ) etcid <- expandTms2Conditions( MassList=targetMz, common, ActivationType="ETD", ETDReactionTime=as.double(1:2), ETDSupplementalActivation="ETciD", ETDSupplementalActivationEnergy=as.double(1:2) ) uvpd <- expandTms2Conditions( MassList=targetMz, common, ActivationType="UVPD" ) ## Create experiments with all combinations of the above settings ## for fragment optimisation exps <- createExperimentsFragmentOptimisation( ms1=ms1, cid, hcd, etd, etcid, uvpd, groupBy=c("AgcTarget", "replication"), nMs2perMs1=10, scanDuration=0.5, replications=2, randomise=TRUE ) ## Write experiments to xml files writeMethodXmls(exps=exps) ## Run XMLMethodChanger runXmlMethodChanger( modificationXml=list.files(pattern="^method.*\\.xml$"), templateMeth="TMS2IndependentTemplateForTD.meth", executable="path\\to\\XmlMethodChanger.exe" )
After setting up direct infusion make sure that MS1 spectrum produces expected protein mass after deconvolution by Xtract. Shown below is a deconvoluted MS1 spectrum for myoglobin. The dominant mass corresponds to myoglobin with Met removed.
R analysis of protein fragmentation data we have to convert the
Some of the information (SpectrumId, Ion Injection Time (ms), Orbitrap Resolution, targeted Mz, ETD reaction time, CID activation and HCD activation) is stored in scan headers, while other (ETD reagent target and AGC target) is only available in method table.
You can run ScanHeadsman from the commandline
ScanHeadsman.exe --noMS --methods:CSV) or use the function provided by
runScanHeadsman( path="path\\to\\raw-files", executable="path\\to\\ScanHeadsman.exe" )
ScanHeadsman will generate a
.txt (scan header table) and a
table) file for each
The spectra have to be charge state deconvoluted with Xtract node in Proteome Discoverer 2.1. The software returns deconvoluted spectra in mzML format.