Scaffold 5 introduced the ability to search raw directly by connecting Scaffold to MSFragger. Since the program is build on Java like Scaffold, MSFragger can be used on Windows, macOS or Linux. The following document provides additional information on running MSFragger in Scaffold.
At this stage our direct support for MSFragger is still very new. Thus, there are some known issues to be aware of. We are working to get these corrected in a future version of Scaffold. While we recommend using the most current supported version, here is the MSFragger change log for reference.
- Some digestion enzymes in the dropdown menu in the MSFragger search parameters are not currently supported. These include: pepsin 1.3, pepsin 2, Glu-C (bicarb), Gluc-C (phosphate), Asp N, Asp N (ambic), V8, Proteinase K, Trypsin/CnBr, Thermolysin, Lys N, Lys C, pepsina, endopeptidase, Trypsin K, Trypsin p DP and Lys C P DP. If interested in using an alternative digestion enzyme, consider running FragPipe and loading the data into Scaffold. Tryptic searches are working correctly
- There was a bug in previous MSFragger versions that caused the MGF file to not be written in some cases. This was fixed in version 3.3. If you are running a version of MSFragger prior to 3.3, please update.
- The SemiTrypic digestion enzyme option reverts to Trypsin. Again, consider using FragPipe.
- If using MSFragger version 3.1 or 3.1.1 do not use LFDR as the scoring model. In most cases it is generally recommended to use Percolator.
When run by itself or within Scaffold, MSFragger does not support precursor intensity quantitation. To get precursor values when using MSFragger, run it through FragPipe and then load the resulting files into Scaffold. Please see our Support Data Formats for more information on supported quantitation methods.
Connecting to MSFragger
Once MSFragger has been downloaded, point Scaffold to the MSFragger
JAR file using the Edit > Preferences > Paths menu. Make sure to keep the MSFragger
JAR file in the folder it came in as other files in it are required for data processing.
Note, MSFragger requires a separate license from Scaffold. Please see https://github.com/Nesvilab/MSFragger/wiki/Preparing-MSFragger for information on obtaining a license.
Larger data sets require more RAM to be allocated to Scaffold and MSFragger. While RAM can be allocated to Scaffold using the Edit > Preferences > Memory tab, MSFragger RAM needs to be allocated separately.
Navigate to the
msfragger.params.template file found in your Scaffold 5 installation directory on your C drive, and open it with a text editor. In this file you see
-Xmx:8g. This is the default and it means that there is currently 8gb of RAM allocated to MSFragger. To change the allocation simply replace this number with how much RAM you would like to allocate. For example change this to
-Xmx:24g to allocate 24gb of RAM to MSFragger. Save the file and restart Scaffold if it is running. You should now be using the new setting.
MSFragger has specific requirements for how decoys are annotated in the FASTA file. Please see their article on FASTA title lines: https://github.com/Nesvilab/philosopher/wiki/How-to-prepare-a-protein-database#header-formatting. FASTA parsing can easily be changed in Scaffold to accommodate the correct MSFragger annotations.
Additional MSFragger Search Parameters
All of the search parameters required to complete an MSFragger search are available through the Scaffold Load Data Wizard. However, some additional parameters can be modified as needed.
Parameters can be added to the
msfragger.params.template file that was edited in the previous section. Please use the
closed_fragger.params file found in your MSFragger installation as a reference but do not edit this file. Copy parameters from it into the template file.
For more information on each parameter, please consult the MSFragger documentation.
The following is a list of parameters that should not be changed.
Modifications should either be set in the Scaffold Load Data Wizard or in the template file but not in both. Additionally, Scaffold does not allow for more that one variable modification on a single amino acid.
The following parameters can be changed by adding the parameter to the