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Articles tagged: Mascot Distiller
Improving precursor quantitation results with ion mobility filtering
One of the major new features in Mascot Distiller 2.8 is support for raw data files from the Bruker timsTOF instrument. timsTOF combines an ion mobility dimension with QTOF, allowing an additional separation dimension. The instrument can use this to help separate MS/MS spectra from otherwise isobaric peptides. Mascot Distiller 2.8 can use the precursor ion mobility values for identified [...]
Global thinking: Label Free Quantitation in Mascot Distiller 2.8
Mascot Distiller supports a wide range of precursor based quantitation methods, including two label-free methods, which we call Replicate and Average. Version 2.8 makes significant improvements to the Replicate method. This is the method for label-free quantitation based on the relative intensities of extracted ion chromatograms (XICs) for precursors in multiple data sets aligned using mass and elution time. Replicate [...]
Solving a puzzle with Mascot Distiller de novo
Have you tried either of the MS/MS interpretation challenges organised by EUPA and LBMSDG? Maybe you are expert enough to read off the peptide sequence, directly. If so, you can stop reading right here! If your interpretation skills and mental arithmetic are a bit rusty, we thought it might be useful to walk through how Mascot Distiller plus a bit [...]
Using the Quantitation Summary to create reports and charts
An earlier article described how to create a Quantitation Summary in Mascot Daemon. This is a spreadsheet-like text file, where the rows correspond to proteins and the columns contain expression data for various samples in the form of abundances or ratios of abundances. A Quantitation Summary can be opened and manipulated in a spreadsheet program such as Excel, and it [...]
Tabulate expression data from multiple analyses with Mascot Daemon
Studies that use mass spectrometry-based quantitation often contain large numbers of individual analyses: samples from different sources or treatments or time points, possibly fractionated, with replicates and so forth. Using statistical methods to combine the analyses, extract meaningful information, and report it as charts and tables is a complex task that usually requires custom scripting in a language such as [...]
How to set up remote working
There are times when you unexpectedly find yourself having to work from home. Fear not: data analysis doesn’t need to stop when you’re away from the lab. Mascot Server has a client-server architecture, and the client PC can be located anywhere. Distiller and Daemon can also be used remotely, or they can be run on a remote client PC and [...]
Disulfide bond characterisation
Support for matching crosslinked peptides is a new feature in Mascot Server 2.7. The following linkage types can be detected: intralinks – the linked peptides are from the same protein interlinks – the linked peptides are from two different proteins looplinks – connecting two amino acids within a single peptide monolinks – a linker with one end attached and the [...]
Disaster recovery
There are a number of potential issues that can cause your Mascot Server or other computer infrastructure to stop working. In the worst case, you may need to do a full recovery from backups. This can be an involved procedure, but it is straightforward as long as you have backed up key configuration and data files. For disk or storage [...]
The three Ds: Diethylation, Dimethylation and the Deuterium effect
Dimethylation Mascot Server and Mascot Distiller support a number of precursor intensity based quantitation techniques using a number of different techniques and chemistries. The software also allows you to flexibly define your own methods, allowing you to implement quantitation protocols which we have not supplied ‘out of the box’. One isotope labelling method which Distiller supports ‘out of the box’ [...]
Mascot Distiller 2.7: Farewell to re-gridding
We recently released Mascot Distiller 2.7. The main new feature of this release is a change to how peak detection works on raw profile datasets that have been saved as sparse, or compressed data, with runs of zero values dropped. Common examples of this are Thermo Orbitrap and Sciex Analyst datasets saved as profile data. For these types of data, [...]