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Articles tagged: FDR

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Posted by Ville Koskinen (April 14, 2020)

Human Proteome Project data interpretation guidelines

The Human Proteome Project (HPP) data interpretation guidelines were recently updated. Many of the guidelines are good practice and common sense in any proteomics study where reliable protein identification is critical, not just when studying the human proteome. The guidelines are easy to meet using Mascot Server 2.7. Core guidelines The full list consists of 9 guidelines. The first one [...]

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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 Ville Koskinen (September 16, 2019)

Common myths about protein scores

Mascot Server is used in many different application areas by both mass spectrometry experts and non-experts. Over the years, we’ve spotted a few recurring misconceptions about how protein scores are interpreted and used. All the examples come from recent peer-reviewed papers. Protein scores in PMF searches The very first thing to check is, what type of experiment is being reported. [...]

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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 (June 18, 2016)

High FDRs for methylated peptides III

The MCP paper "Large Scale Mass Spectrometry-based Identifications of Enzyme-mediated Protein Methylation Are Subject to High False Discovery Rates" raises some important questions concerning the accuracy and interpretation of database search results. In this third article, we look at the difference between using counts of matches (PSMs) and counts of distinct sequences to calculate the false discovery rate (FDR). filestarget [...]

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Posted by John Cottrell (May 18, 2016)

High FDRs for methylated peptides II

In a previous article, we discussed how the false discovery rate (FDR) for modified peptides would be higher than the global FDR for all PSMs if the proportion of modified peptides in the search space for false matches was higher than for true matches. This is only one factor in the very high FDRs for methylated peptides reported in the [...]

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Posted by John Cottrell (April 21, 2016)

High FDRs for methylated peptides

"Large Scale Mass Spectrometry-based Identifications of Enzyme-mediated Protein Methylation Are Subject to High False Discovery Rates" in the March edition of Molecular & Cellular Proteomics represents a very substantial and systematic piece of work from the University of New South Wales. Three types of sample preparation (coomassie gel, unstained gel, HILIC) were combined with three different ionisation methods (CID, ETD, [...]

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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 (January 19, 2015)

Creating a list of confidently identified proteins

This can be done very easily using Report Builder: Select the Decoy checkbox when submitting the search Open the result report as a Protein Family Summary Switch to the Report Builder tab Expand the decoy search section and set the peptide FDR to 1% Expand the filters section and set ‘Num of significant unique sequences’ > 1 Optionally, expand the [...]

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