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Posted by John Cottrell (June 17, 2020)

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 [...]

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Posted by John Cottrell (May 19, 2020)

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 [...]

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Posted by John Cottrell (December 17, 2019)

Protein FDR in Mascot Server 2.7

One of the new features in Mascot Server 2.7, now running on this web site, is an estimate of protein FDR. This is displayed in the Protein Family Summary for Fasta searches whenever automatic decoy is selected. The basis is the number of proteins inferred in the target database compared with the number in the decoy database. Conceptually, this is [...]

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Posted by John Cottrell (June 14, 2019)

What are you inferring?

Benchmarking protein inference is notoriously difficult. Artificial samples of known content tend to be too simple while real samples lack ground truth. An interesting approach was adopted for the ABRF iPRG 2016 study, and has been the subject of a publication from The et al. A collection of human Protein Epitope Signature Tags (PrESTs) were expressed in E. coli and [...]

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Posted by Ville Koskinen (May 17, 2019)

Back to basics 5: Peptide-spectrum match statistics

Mascot can identify peptides in uninterpreted MS/MS data. Observed spectra are submitted to Mascot as search queries. A query specifies the precursor ion m/z and charge state as well as the MS/MS peak list. Mascot digests protein sequences from the chosen database and selects peptide sequences whose mass is within the specified tolerance of the query’s precursor mass. The software [...]

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Posted by John Cottrell (April 15, 2019)

Mascot workflows in Proteome Discoverer

For many users of Thermo instruments, Proteome Discoverer (PD) is their primary user interface for database searching, and Mascot is represented by a node in the workflow. This article collects together a few tips and observations concerning Proteome Discoverer 2.3 and Mascot Server 2.6. Proteome Discoverer Configuration Under Administration; Mascot Server, the setting Max. MGF File Size [MB] has a [...]

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Posted by Patrick Emery (October 15, 2018)

Back to basics 3: Quantitation statistics

Mascot Server and Distiller support a number of different quantitation methods. These methods are carried out at the peptide level, the peptides are then grouped into protein families, and the peptide quantitation results used to calculate protein ratio values. Mascot and Distiller perform a number of statistical procedures and tests to give you an indication of the quality and reliability [...]

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Posted by John Cottrell (March 14, 2016)

Some peaks are more equal than others

When you look at the details of a peptide match in the Mascot Peptide View report, only a small number of the peaks may be labelled in the spectrum graphic and highlighted in the table of fragment masses. We often got challenged about this: "Why haven’t you labelled these other peaks that clearly match?". So, in Mascot 2.3, we added [...]

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Posted by John Cottrell (July 15, 2015)

Search only for peptides we care about?

The July issue of Nature Methods contains a commentary from William Noble with the slightly provocative title "Mass spectrometrists should search only for peptides they care about". At first sight, this seems to contradict our general advice to include contaminant sequences when searching a single organism database or when using a taxonomy filter. One of Noble’s examples is a study [...]

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Posted by John Cottrell (November 22, 2013)

Does protein FDR have any meaning?

Its easy to grasp the concept of using a target/decoy search to estimate peptide false discovery rate. You search against a decoy database where there are no true matches available, so the number of observed matches provides a good estimate of the number of false matches in the results from the target. People debate implementation details, such as whether the [...]

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