Blog
Strange software failures? Check your disk space
From time to time, a piece of software that has been working reliably suddenly doesn’t. The most common reason for Mascot Server to fail is running out of disk space, which can cause all kinds of weird faults. Proteomics software is more prone to it than others due to the large size of input data and temporary files created during [...]
Peak list arcana: Area vs. signal to noise
A recent paper from Hijazi et al. [1] raised some interesting points about how a peaklists file can differ from the appearance of the underlying raw file, and specifically raised some differences with the peaklists generated by Mascot Distiller if you output the signal to noise (S/N) as fragment ion intensity instead of the default, which is the peak area. [...]
Replacements for NCBI nr
NCBI nr is the comprehensive database of non-identical protein sequences compiled by the National Center for Biotechnology Information. The database configuration has long been shipped with Mascot Server as the NCBIprot predefined definition. However, it seems the FASTA file has quietly been retired; the last version appears to be the February 2024 file. The last-modified time of nr.gz on the [...]
Top-3 Quantitation Summary in Mascot Daemon 3 using DDA-PASEF
Mascot Daemon includes a protein level quantitation summary report for both precursor based methods (LFQ, SILAC etc) and MS/MS quantitation (iTRAQ, TMT). The exported format is suitable for importing into statistic packages such as R or Perseus. In Mascot Daemon 3, we added an option to export protein intensity values calculated using the “Top-3″ method. Instead of using all matched [...]
Probabilistic spectrum-centric scoring for DIA
In DIA analysis, it feels like far too much attention is devoted to maximising the number of identified proteins and too little on the quality of results. We’re working on a universal spectrum-centric solution for the analysis of DIA data, called Mascot DIA. The key focus is on using all the peak information in the MS/MS scan, without prior assumptions [...]
You’ve got to pick a precursor or two: Precursor detection in Mascot DIA
We’re working on a universal spectrum-centric solution for the analysis of DIA data, called Mascot DIA. A preview was presented at our ASMS 2025 Breakfast Meeting, the slides from which are free to download. Last month’s blog article outlines the spectrum-centric search approach for DIA data and compares it to the more common peptide-centric approach. One thing that is essential [...]
The promise of spectrum-centric DIA
We’re working on a universal spectrum-centric solution for the analysis of DIA data, called Mascot DIA. A preview was presented at our ASMS 2025 Breakfast Meeting, whose slides are free to download. But what is spectrum-centric searching and what is it meant to solve? Complementary approaches “Peptide-centric” and “spectrum-centric” analysis are broad technical terms that are mainly of interest to [...]
Identify more proteins using Mascot and Proteome Discoverer with this one small trick
Mascot Server is often used with software packages like Thermo Proteome Discoverer™ (PD). We recently made it possible to enable machine learning on the server side by specifying it in the Mascot instrument definition, which is also the topic of one of our ASMS 2025 posters. An important detail was overlooked in the initial instructions, which is: you should disable [...]
Adding a custom AI/ML adapter to Mascot
Mascot Server 3.0 and later ship with MS2Rescore for predicting retention time and spectral similarity. What if you wanted to use a different AI/ML system for predictions? Mascot Server has an application programming interface (API) exactly for this purpose. The tutorial below includes a fully working Python script that you can use as a starting point for your own adapter. [...]
Big databases and large peak lists
When it comes to sequence database searches, how large is too large to handle? This is actually two questions in one: a search can be large because the database has millions of protein sequences; or it can be large because of the number of peak lists. Mascot Server has no limits because of its design, which makes it ideal for [...]
Mascot Distiller quantitates more proteins with machine learning
Mascot Distiller can now use machine learning with LFQ, TMT and other quantitation methods, thanks to API changes made in the recent Mascot Server 3.1 release. Machine learning typically increases the number of identified peptides at a fixed false discovery rate, which often leads to a substantial boost in the number of proteins quantified. We demonstrate this with an LFQ [...]
Using machine learning with Mascot and Proteome Discoverer
Update: There is a newer version of this article, Identify more proteins using Mascot and Proteome Discoverer with this one small trick. The PD setup instructions have been updated accordingly. Mascot Server 3.1 is a patch release that enhances integration with Thermo Proteome Discoverer™ and fixes a few important bugs introduced in Mascot Server 3.0. The full list of improvements [...]
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