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Articles tagged: label-free
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 [...]
Spectrum-centric searching of narrow window DIA data with Mascot Server
Data-independent acquisition (DIA) can be broadly separated into narrow window and wide window strategies depending on the size of the isolation window. There are also two data analysis strategies – peptide-centric and spectrum-centric. Wide window DIA typically requires a peptide-centric approach, but narrow window DIA data can be analysed either way. Mascot Server is spectrum-centric, and it’s possible to run [...]
Divide and conquer: Fractionated Label Free Quantitation in Mascot Distiller 2.8.2
We have recently released Mascot Distiller 2.8.2. The headline new feature is support for Label-Free Quantitation of fractionated samples. With Mascot Distiller 2.8, individual raw files in a project are aligned against a consensus generated by roughly aligning and combining the total ion chromatograms (TICs) of each raw file. If a peptide match is found in one sample file and [...]
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 [...]