Dataset Information

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

ABSTRACT: For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types.

SUBMITTER: Piehowski PD

PROVIDER: S-EPMC3676282 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

Piehowski Paul D PD Petyuk Vladislav A VA Sandoval John D JD Burnum Kristin E KE Kiebel Gary R GR Monroe Matthew E ME Anderson Gordon A GA Camp David G DG Smith Richard D RD

Proteomics 20130204 5

For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Paramet ...[more]

PMID: 23303698

Similar Datasets

Project description:Data on the distribution of plant species at spatial (grid) scales are required as input for integrative analysis along with related climate, environment, topography and soil data. Although the world's scientific community is increasingly generating data on plant species at various spatial grids and statistically interpolating and extrapolating the available information, data on plant diversity from the Asian continent are scant. Such data are unavailable for India, the mainland of which has part of three of the world's 36 biodiversity hotspots. Although sufficient field sampling is always impossible and impractical, it is essential to utilize fully any available database by adjudging the sampling sufficiency at a given scale. In this work, we used an exhaustive database of the plant species of the Indian mainland that was sufficient in terms of sampling vegetation types. We transformed the data, obtained the distribution at the 1° and 2° spatial grid levels and evaluated the sampling sufficiency at acceptable threshold limits (60% to 80%). The greatest species richness values recorded in the 0.04 ha quadrant, 1° grid and 2° grid were 59, 623 and 1244, respectively. Clench model was significantly (p value < 0.001) fitted using the plant species data at both the grid levels with a very high coefficient of determination (>0.95). At an acceptable threshold limit of 70%, almost all the grids at the 2° level and more than 80% of the grids at the 1° level were found to be sufficiently sampled. Sampling sufficiency was observed to be highly scale-dependent as a greater number of 2° grids attained asymptotic behaviour following the species-area curve. Grid-level sampling insufficiency was attributed to lower numbers of sampling quadrats in forests with poor approachability, which coincided with the world biodiversity hotspots', suggesting that additional sampling was required. We prescribe the use of the 1° and 2° spatial grids with sufficient sampling for any ecological analysis in conjunction with other data and thereby offer grid-level plant species richness data for the Indian mainland for the first time.

Dataset Information

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

Publications

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets