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Articles tagged: error tolerant

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Posted by Patrick Emery (November 13, 2023)

Finding unsuspected modifications in narrow-window DIA data using the Mascot Error Tolerant Search

Mascot’s spectrum-centric approach doesn’t have the constraints on variable modifications, missed cleavages and protein sequences that are required by peptide-centric DIA tools. In fact, it’s nearly trivial to identify unsuspected variable modifications in narrow-window DIA data using the Mascot Error Tolerant Search. There can be many reasons for failing to get a significant sequence match to an MS/MS spectrum. Three [...]

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Posted by Ville Koskinen (November 16, 2022)

Paleoproteomics

Paleoproteomics is a growing application area for mass spectrometry. Its cross-disciplinary remit includes analysis of ancient proteins (bone, skin, silk), ancient proteomes (enamel, egg shells, plant seeds) and most ambitiously ancient metaproteomes (dental calculus, food remains). The recent review by Warinner et al. in Chemical Reviews has excellent coverage not just of the varied applications but also the sample processing [...]

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Posted by John Cottrell (July 14, 2021)

Error tolerant searches now show statistical significance

The latest release of Mascot Server introduces some important changes to error tolerant searches. Matches from the second pass search now have expect values attached, indicating confidence levels. These are either estimates based on counting trials or empirical values derived from searching a decoy database. If you are not familiar with the error tolerant search, now is the time to [...]

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Posted by Patrick Emery (July 15, 2020)

Variable Modifications in Mascot 2.7

Most protein samples will exhibit some degree of modification which needs to be considered when carrying out a database search In this article we’ll take a look at some important changes we introduced in Mascot 2.7 in how Mascot handles variable modifications. Variable modification permutation in Mascot 2.6 and earlier In Mascot 2.6 or earlier, variable modification permutation is handled [...]

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Posted by John Cottrell (November 15, 2018)

The plus one dilemma

There are several common modifications that can add approximately 1 Da to a peptide mass. Even if you have high accuracy data, it can sometimes be difficult to figure out which one is correct.   Delta Lys->Glu substitution 0.947630 Leu->Asn or Ile->Asn substitution 0.958863 Deamidation at N or Asn->Asp substitution 0.984016 Deamidation at Q or Gln->Glu substitution 0.984016 Citrullination at [...]

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Posted by Richard Jacob (July 16, 2018)

Back to Basics: Optimize your search parameters

Every now and then you need to determine good search parameters for a data set. They may be different from the normal ones you use due to a change in instrumentation, you may be analyzing data from a public resource like PRIDE/Proteome exchange or it could be data from a collaborator. Whatever the reason, here’s a quick overview on how [...]

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Posted by John Cottrell (January 12, 2018)

Results round-up for the ‘dark matter’ challenge

In June, we tried to harness the power of crowd-sourcing to explain some of the unidentified modifications found in open database searches. We selected 20 abundant and unassigned mass deltas from Supplementary Table 3 of the recent MSFragger paper from Alexey Nesvizhskii’s group at U. Michigan and offered prizes for the first credible explanations. There were 35 unannotated deltas in [...]

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Posted by John Cottrell (October 16, 2017)

Step away from the iodoacetamide

In our July newsletter, we featured a paper from Torsten Müller and Dominic Winter, University of Bonn, concerning alkylation artefacts. Some of their findings were quite shocking. For example, differences of more than 9 fold in numbers of identified methionine-containing peptides for in-gel digested samples between iodine- and non-iodine-containing alkylation reagents. This is important because a glance at the literature [...]

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Posted by John Cottrell (September 12, 2017)

How to create a spectral library for contaminants

An earlier article highlighted how modified and non-specific peptides from contaminants can be matched using a spectral library without increasing the search space for the target proteins. This is particularly useful for sequencing grade trypsin, which is modified by methylation or acetylation of the lysines, creating a large number of modified non-specific peptides that are missed by typical search strategies. [...]

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Posted by John Cottrell (July 12, 2017)

The most analysed protein is …

Trypsin, of course. The Journal of Proteome Research has a paper from the Medical University of Graz concerning the importance of correctly identifying spectra from contaminant proteins. In particular, trypsin autolysis peptides. The authors point out that sequencing grade trypsin is modified by methylation or acetylation of the lysines, to inhibit autolysis. Unless these variable modifications are selected in a [...]

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