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1.  jmzTab: A Java interface to the mzTab data standard 
Proteomics  2014;14(11):1328-1332.
mzTab is the most recent standard format developed by the Proteomics Standards Initiative. mzTab is a flexible tab-delimited file that can capture identification and quantification results coming from MS-based proteomics and metabolomics approaches. We here present an open-source Java application programming interface for mzTab called jmzTab. The software allows the efficient processing of mzTab files, providing read and write capabilities, and is designed to be embedded in other software packages. The second key feature of the jmzTab model is that it provides a flexible framework to maintain the logical integrity between the metadata and the table-based sections in the mzTab files. In this article, as two example implementations, we also describe two stand-alone tools that can be used to validate mzTab files and to convert PRIDE XML files to mzTab. The library is freely available at http://mztab.googlecode.com.
doi:10.1002/pmic.201300560
PMCID: PMC4230411  PMID: 24659499
Bioinformatics; Data standard; Java application programming interface; Proteomics Standards Initiative
3.  Allele Frequencies Database 
Summary
This review describes a database for the collection, archiving, sorting, searching and display of gene and allele frequencies for immunogenetic genes.
doi:10.1159/000368056
PMCID: PMC4264510  PMID: 25538537
Data management system; HLA; Immunogenetics; KIR
5.  The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience* 
Molecular & Cellular Proteomics : MCP  2014;13(10):2765-2775.
The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R.
We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online.
doi:10.1074/mcp.O113.036681
PMCID: PMC4189001  PMID: 24980485
6.  The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics* 
The range of heterogeneous approaches available for quantifying protein abundance via mass spectrometry (MS)1 leads to considerable challenges in modeling, archiving, exchanging, or submitting experimental data sets as supplemental material to journals. To date, there has been no widely accepted format for capturing the evidence trail of how quantitative analysis has been performed by software, for transferring data between software packages, or for submitting to public databases. In the context of the Proteomics Standards Initiative, we have developed the mzQuantML data standard. The standard can represent quantitative data about regions in two-dimensional retention time versus mass/charge space (called features), peptides, and proteins and protein groups (where there is ambiguity regarding peptide-to-protein inference), and it offers limited support for small molecule (metabolomic) data. The format has structures for representing replicate MS runs, grouping of replicates (for example, as study variables), and capturing the parameters used by software packages to arrive at these values. The format has the capability to reference other standards such as mzML and mzIdentML, and thus the evidence trail for the MS workflow as a whole can now be described. Several software implementations are available, and we encourage other bioinformatics groups to use mzQuantML as an input, internal, or output format for quantitative software and for structuring local repositories. All project resources are available in the public domain from the HUPO Proteomics Standards Initiative http://www.psidev.info/mzquantml.
doi:10.1074/mcp.O113.028506
PMCID: PMC3734589  PMID: 23599424
8.  Ten Years of Standardizing Proteomic Data: a report on the HUPO-PSI Spring Workshop 12–14th April 2012, San Diego, USA 
Proteomics  2012;12(18):2767-2772.
The Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI) was established in 2002 with the aim of defining community standards for data representation in proteomics and facilitating data comparison, exchange and verification. Over the last 10 years significant advances have been made, with common data standards now published and implemented in the field of both mass spectrometry and molecular interactions. The 2012 meeting further advanced this work, with the mass spectrometry groups finalising approaches to capturing the output from recent developments in the field, such as quantitative proteomics and SRM. The molecular interaction group focused on improving the integration of data from multiple resources. Both groups united with a guest work track, organized by the HUPO Technology/Standards Committee, to formulate proposals for data submissions from the HUPO Human Proteome Project and to start an initiative to collect standard experimental protocols.
doi:10.1002/pmic.201270126
PMCID: PMC3895333  PMID: 22969026
9.  Controlled vocabularies and ontologies in proteomics: Overview, principles and practice☆ 
Biochimica et Biophysica Acta  2014;1844(1):98-107.
This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the “mapping files” used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.
Highlights
► The semantic annotation using ontologies is a prerequisite for the semantic web. ► The HUPO-PSI defined a set of XML-based standard formats for proteomics. ► These standard formats allow the referencing of CV terms defined in obo files. ► The CV terms can be used to enforce MIAPE compliance of the data files. ► The mass spectrometry CV is constantly maintained in a community process.
doi:10.1016/j.bbapap.2013.02.017
PMCID: PMC3898906  PMID: 23429179
ANDI-MS, Analytical Data Interchange format for Mass Spectrometry; AniML, Analytical Information Markup Language; API, Application Programming Interface; ASCII, American Standard Code for Information Interchange; ASTM, American Society for Testing and Materials; BTO, BRENDA (BRaunschweig ENzyme DAtabase) Tissue Ontology; ChEBI, Chemical Entities of Biological Interest; CV, Controlled Vocabulary; DL, Description Logic; EBI, European Bioinformatics Institute; HDF5, Hierarchical Data Format, version 5; HUPO-PSI, Human Proteome Organisation-Proteomics Standards Initiative; ICD, International Classification of Diseases; IUPAC, International Union for Pure and Applied Chemistry; JCAMP-DX, Joint Committee on Atomic and Molecular Physical data-Data eXchange format; MALDI, Matrix Assisted Laser Desorption Ionization; MeSH, Medical Subject Headings; MI, Molecular Interaction; MIBBI, Minimal Information for Biological and Biomedical Investigations; MITAB, Molecular Interactions TABular format; MIAPE, Minimum Information About a Proteomics Experiment; MS, Mass Spectrometry; NCBI, National Center for Biotechnology Information; NCBO, National Center for Biomedical Ontology; netCDF, Network Common Data Format; OBI, Ontology for Biomedical Investigations; OBO, Open Biological and Biomedical Ontologies; OLS, Ontology Lookup Service; OWL, Web Ontology Language; PAR, Protein Affinity Reagents; PATO, Phenotype Attribute Trait Ontology; PRIDE, PRoteomics IDEntifications database; RDF(S), Resource Description Framework (Schema); SRM, Selected Reaction Monitoring; TPP, Trans-Proteomic Pipeline; URI, Uniform Resource Identifier; XSLT, eXtensible Stylesheet Language Transformation; YAFMS, Yet Another Format for Mass Spectrometry; Proteomics data standards; Controlled vocabularies; Ontologies in proteomics; Ontology formats; Ontology editors and software; Ontology maintenance
10.  A tutorial for software development in quantitative proteomics using PSI standard formats☆ 
Biochimica et Biophysica Acta  2014;1844(1):88-97.
The Human Proteome Organisation — Proteomics Standards Initiative (HUPO-PSI) has been working for ten years on the development of standardised formats that facilitate data sharing and public database deposition. In this article, we review three HUPO-PSI data standards — mzML, mzIdentML and mzQuantML, which can be used to design a complete quantitative analysis pipeline in mass spectrometry (MS)-based proteomics. In this tutorial, we briefly describe the content of each data model, sufficient for bioinformaticians to devise proteomics software. We also provide guidance on the use of recently released application programming interfaces (APIs) developed in Java for each of these standards, which makes it straightforward to read and write files of any size. We have produced a set of example Java classes and a basic graphical user interface to demonstrate how to use the most important parts of the PSI standards, available from http://code.google.com/p/psi-standard-formats-tutorial. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.
Highlights
•A tutorial to help software developers use PSI standard formats.•A description of programming interfaces and tools available.•Code snippets and a basic graphical interface to assist understanding.
doi:10.1016/j.bbapap.2013.04.004
PMCID: PMC4008935  PMID: 23584085
Quantitative proteomics; Software; Standard formats; APIs
11.  FDRAnalysis: A tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines 
Journal of proteome research  2011;10(4):2088-2094.
Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the post-processing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server, and a downloadable application, which makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download.
doi:10.1021/pr101157s
PMCID: PMC3707089  PMID: 21222473
bioinformatics; false discovery rate; multiple search engines; web server; data standards
12.  Tools (Viewer, Library and Validator) that Facilitate Use of the Peptide and Protein Identification Standard Format, Termed mzIdentML* 
Molecular & Cellular Proteomics : MCP  2013;12(11):3026-3035.
The Proteomics Standards Initiative has recently released the mzIdentML data standard for representing peptide and protein identification results, for example, created by a search engine. When a new standard format is produced, it is important that software tools are available that make it straightforward for laboratory scientists to use it routinely and for bioinformaticians to embed support in their own tools. Here we report the release of several open-source Java-based software packages based on mzIdentML: ProteoIDViewer, mzidLibrary, and mzidValidator. The ProteoIDViewer is a desktop application allowing users to visualize mzIdentML-formatted results originating from any appropriate identification software; it supports visualization of all the features of the mzIdentML format. The mzidLibrary is a software library containing routines for importing data from external search engines, post-processing identification data (such as false discovery rate calculations), combining results from multiple search engines, performing protein inference, setting identification thresholds, and exporting results from mzIdentML to plain text files. The mzidValidator is able to process files and report warnings or errors if files are not correctly formatted or contain some semantic error. We anticipate that these developments will simplify adoption of the new standard in proteomics laboratories and the integration of mzIdentML into other software tools. All three tools are freely available in the public domain.
doi:10.1074/mcp.O113.029777
PMCID: PMC3820921  PMID: 23813117
13.  A database for curating the associations between killer cell immunoglobulin-like receptors and diseases in worldwide populations 
The killer cell immunoglobulin-like receptors (KIR) play a fundamental role in the innate immune system, through their interactions with human leucocyte antigen (HLA) molecules, leading to the modulation of activity in natural killer (NK) cells, mainly related to killing pathogen-infected cells. KIR genes are hugely polymorphic both in the number of genes an individual carries and in the number of alleles identified. We have previously developed the Allele Frequency Net Database (AFND, http://www.allelefrequencies.net), which captures worldwide frequencies of alleles, genes and haplotypes for several immune genes, including KIR genes, in healthy populations, covering >4 million individuals. Here, we report the creation of a new database within AFND, named KIR and Diseases Database (KDDB), capturing a large quantity of data derived from publications in which KIR genes, alleles, genotypes and/or haplotypes have been associated with infectious diseases (e.g. hepatitis C, HIV, malaria), autoimmune disorders (e.g. type I diabetes, rheumatoid arthritis), cancer and pregnancy-related complications. KDDB has been created through an extensive manual curation effort, extracting data on more than a thousand KIR-disease records, comprising >50 000 individuals. KDDB thus provides a new community resource for understanding not only how KIR genes are associated with disease, but also, by working in tandem with the large data sets already present in AFND, where particular genes, genotypes or haplotypes are present in worldwide populations or different ethnic groups. We anticipate that KDDB will be an important resource for researchers working in immunogenetics.
Database URL: http://www.allelefrequencies.net/diseases/
doi:10.1093/database/bat021
PMCID: PMC3625957  PMID: 23584834
14.  The HUPO proteomics standards initiative- mass spectrometry controlled vocabulary 
Controlled vocabularies (CVs), i.e. a collection of predefined terms describing a modeling domain, used for the semantic annotation of data, and ontologies are used in structured data formats and databases to avoid inconsistencies in annotation, to have a unique (and preferably short) accession number and to give researchers and computer algorithms the possibility for more expressive semantic annotation of data. The Human Proteome Organization (HUPO)–Proteomics Standards Initiative (PSI) makes extensive use of ontologies/CVs in their data formats. The PSI-Mass Spectrometry (MS) CV contains all the terms used in the PSI MS–related data standards. The CV contains a logical hierarchical structure to ensure ease of maintenance and the development of software that makes use of complex semantics. The CV contains terms required for a complete description of an MS analysis pipeline used in proteomics, including sample labeling, digestion enzymes, instrumentation parts and parameters, software used for identification and quantification of peptides/proteins and the parameters and scores used to determine their significance. Owing to the range of topics covered by the CV, collaborative development across several PSI working groups, including proteomics research groups, instrument manufacturers and software vendors, was necessary. In this article, we describe the overall structure of the CV, the process by which it has been developed and is maintained and the dependencies on other ontologies.
Database URL: http://psidev.cvs.sourceforge.net/viewvc/psidev/psi/psi-ms/mzML/controlledVocabulary/psi-ms.obo
doi:10.1093/database/bat009
PMCID: PMC3594986  PMID: 23482073
15.  Library of Apicomplexan Metabolic Pathways: a manually curated database for metabolic pathways of apicomplexan parasites 
Nucleic Acids Research  2012;41(Database issue):D706-D713.
The Library of Apicomplexan Metabolic Pathways (LAMP, http://www.llamp.net) is a web database that provides near complete mapping from genes to the central metabolic functions for some of the prominent intracellular parasites of the phylum Apicomplexa. This phylum includes the causative agents of malaria, toxoplasmosis and theileriosis—diseases with a huge economic and social impact. A number of apicomplexan genomes have been sequenced, but the accurate annotation of gene function remains challenging. We have adopted an approach called metabolic reconstruction, in which genes are systematically assigned to functions within pathways/networks for Toxoplasma gondii, Neospora caninum, Cryptosporidium and Theileria species, and Babesia bovis. Several functions missing from pathways have been identified, where the corresponding gene for an essential process appears to be absent from the current genome annotation. For each species, LAMP contains interactive diagrams of each pathway, hyperlinked to external resources and annotated with detailed information, including the sources of evidence used. We have also developed a section to highlight the overall metabolic capabilities of each species, such as the ability to synthesize or the dependence on the host for a particular metabolite. We expect this new database will become a valuable resource for fundamental and applied research on the Apicomplexa.
doi:10.1093/nar/gks1139
PMCID: PMC3531055  PMID: 23193253
16.  A Critical Appraisal of Techniques, Software Packages, and Standards for Quantitative Proteomic Analysis 
Abstract
New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool (http://www.proteosuite.org/?q=other_resources) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology.
doi:10.1089/omi.2012.0022
PMCID: PMC3437040  PMID: 22804616
17.  A Software Toolkit and Interface for Performing Stable Isotope Labeling and Top3 Quantification Using Progenesis LC-MS 
Abstract
Numerous software packages exist to provide support for quantifying peptides and proteins from mass spectrometry (MS) data. However, many support only a subset of experimental methods or instrument types, meaning that laboratories often have to use multiple software packages. The Progenesis LC-MS software package from Nonlinear Dynamics is a software solution for label-free quantitation. However, many laboratories using Progenesis also wish to employ stable isotope-based methods that are not natively supported in Progenesis. We have developed a Java programming interface that can use the output files produced by Progenesis, allowing the basic MS features quantified across replicates to be used in a range of different experimental methods. We have developed post-processing software (the Progenesis Post-Processor) to embed Progenesis in the analysis of stable isotope labeling data and top3 pseudo-absolute quantitation. We have also created export ability to the new data standard, mzQuantML, produced by the Proteomics Standards Initiative to facilitate the development and standardization process. The software is provided to users with a simple graphical user interface for accessing the different features. The underlying programming interface may also be used by Java developers to develop other routines for analyzing data produced by Progenesis.
doi:10.1089/omi.2012.0042
PMCID: PMC3437041  PMID: 22888986
18.  In silico analysis of HLA associations with drug-induced liver injury: use of a HLA-genotyped DNA archive from healthy volunteers 
Genome Medicine  2012;4(6):51.
Background
Drug-induced liver injury (DILI) is one of the most common adverse reactions leading to product withdrawal post-marketing. Recently, genome-wide association studies have identified a number of human leukocyte antigen (HLA) alleles associated with DILI; however, the cellular and chemical mechanisms are not fully understood.
Methods
To study these mechanisms, we established an HLA-typed cell archive from 400 healthy volunteers. In addition, we utilized HLA genotype data from more than four million individuals from publicly accessible repositories such as the Allele Frequency Net Database, Major Histocompatibility Complex Database and Immune Epitope Database to study the HLA alleles associated with DILI. We utilized novel in silico strategies to examine HLA haplotype relationships among the alleles associated with DILI by using bioinformatics tools such as NetMHCpan, PyPop, GraphViz, PHYLIP and TreeView.
Results
We demonstrated that many of the alleles that have been associated with liver injury induced by structurally diverse drugs (flucloxacillin, co-amoxiclav, ximelagatran, lapatinib, lumiracoxib) reside on common HLA haplotypes, which were present in populations of diverse ethnicity.
Conclusions
Our bioinformatic analysis indicates that there may be a connection between the different HLA alleles associated with DILI caused by therapeutically and structurally different drugs, possibly through peptide binding of one of the HLA alleles that defines the causal haplotype. Further functional work, together with next-generation sequencing techniques, will be needed to define the causal alleles associated with DILI.
doi:10.1186/gm350
PMCID: PMC3698530  PMID: 22732016
19.  The mzIdentML Data Standard for Mass Spectrometry-Based Proteomics Results 
Molecular & Cellular Proteomics : MCP  2012;11(7):M111.014381.
We report the release of mzIdentML, an exchange standard for peptide and protein identification data, designed by the Proteomics Standards Initiative. The format was developed by the Proteomics Standards Initiative in collaboration with instrument and software vendors, and the developers of the major open-source projects in proteomics. Software implementations have been developed to enable conversion from most popular proprietary and open-source formats, and mzIdentML will soon be supported by the major public repositories. These developments enable proteomics scientists to start working with the standard for exchanging and publishing data sets in support of publications and they provide a stable platform for bioinformatics groups and commercial software vendors to work with a single file format for identification data.
doi:10.1074/mcp.M111.014381
PMCID: PMC3394945  PMID: 22375074
20.  The Gel Electrophoresis Markup Language (GelML) from the Proteomics Standards Initiative 
Proteomics  2010;10(17):3073-3081.
The Human Proteome Organisation’s Proteomics Standards Initiative (HUPO-PSI) has developed the GelML data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for mass spectrometry data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications.
doi:10.1002/pmic.201000120
PMCID: PMC3193076  PMID: 20677327
data standard; gel electrophoresis; database; ontology
21.  jmzIdentML API: A Java interface to the mzIdentML standard for peptide and protein identification data 
Proteomics  2012;12(6):790-794.
We present a Java application programming interface (API), jmzIdentML, for the Human Proteome Organisation (HUPO) Proteomics Standards Initiative (PSI) mzIdentML standard for peptide and protein identification data. The API combines the power of Java Architecture of XML Binding (JAXB) and an XPath-based random-access indexer to allow a fast and efficient mapping of extensible markup language (XML) elements to Java objects. The internal references in the mzIdentML files are resolved in an on-demand manner, where the whole file is accessed as a random-access swap file, and only the relevant piece of XMLis selected for mapping to its corresponding Java object. The APIis highly efficient in its memory usage and can handle files of arbitrary sizes. The APIfollows the official release of the mzIdentML (version 1.1) specifications and is available in the public domain under a permissive licence at http://www.code.google.com/p/jmzidentml/.
doi:10.1002/pmic.201100577
PMCID: PMC3933944  PMID: 22539429
Bioinformatics; Java API; mzIdentML; Proteomics standards initiative (PSI); XML
22.  A DIGE study on the effects of salbutamol on the rat muscle proteome - an exemplar of best practice for data sharing in proteomics 
BMC Research Notes  2011;4:86.
Background
Proteomic techniques allow researchers to perform detailed analyses of cellular states and many studies are published each year, which highlight large numbers of proteins quantified in different samples. However, currently few data sets make it into public databases with sufficient metadata to allow other groups to verify findings, perform data mining or integrate different data sets. The Proteomics Standards Initiative has released a series of "Minimum Information About a Proteomics Experiment" guideline documents (MIAPE modules) and accompanying data exchange formats. This article focuses on proteomic studies based on gel electrophoresis and demonstrates how the corresponding MIAPE modules can be fulfilled and data deposited in public databases, using a new experimental data set as an example.
Findings
We have performed a study of the effects of an anabolic agent (salbutamol) at two different time points on the protein complement of rat skeletal muscle cells, quantified by difference gel electrophoresis. In the DIGE study, a total of 31 non-redundant proteins were identified as being potentially modulated at 24 h post treatment and 110 non redundant proteins at 96 h post-treatment. Several categories of function have been highlighted as strongly enriched, providing candidate proteins for further study. We also use the study as an example of best practice for data deposition.
Conclusions
We have deposited all data sets from this study in public databases for further analysis by the community. We also describe more generally how gel-based protein identification data sets can now be deposited in the PRoteomics IDEntifications database (PRIDE), using a new software tool, the PRIDESpotMapper, which we developed to work in conjunction with the PRIDE Converter application. We also demonstrate how the ProteoRed MIAPE generator tool can be used to create and share a complete and compliant set of MIAPE reports for this experiment and others.
doi:10.1186/1756-0500-4-86
PMCID: PMC3080311  PMID: 21443781
23.  Allele frequency net: a database and online repository for immune gene frequencies in worldwide populations 
Nucleic Acids Research  2010;39(Database issue):D913-D919.
The allele frequency net database (http://www.allelefrequencies.net) is an online repository that contains information on the frequencies of immune genes and their corresponding alleles in different populations. The extensive variability observed in genes and alleles related to the immune system response and its significance in transplantation, disease association studies and diversity in populations led to the development of this electronic resource. At present, the system contains data from 1133 populations in 608 813 individuals on the frequency of genes from different polymorphic regions such as human leukocyte antigens, killer-cell immunoglobulin-like receptors, major histocompatibility complex Class I chain-related genes and a number of cytokine gene polymorphisms. The project was designed to create a central source for the storage of frequency data and provide individuals with a set of bioinformatics tools to analyze the occurrence of these variants in worldwide populations. The resource has been used in a wide variety of contexts, including clinical applications (histocompatibility, immunology, epidemiology and pharmacogenetics) and population genetics. Demographic information, frequency data and searching tools can be freely accessed through the website.
doi:10.1093/nar/gkq1128
PMCID: PMC3013710  PMID: 21062830
24.  Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines 
Proteomics  2009;9(5):1220-1229.
Tandem mass spectrometry, run in combination with liquid chromatography (LC-MS/MS), can generate large numbers of peptide and protein identifications, for which a variety of database search engines are available. Distinguishing correct identifications from false positives is far from trivial because all data sets are noisy, and tend to be too large for manual inspection, therefore probabilistic methods must be employed to balance the trade-off between sensitivity and specificity. Decoy databases are becoming widely used to place statistical confidence in results sets, allowing the false discovery rate (FDR) to be estimated. It has previously been demonstrated that different MS search engines produce different peptide identification sets, and as such, employing more than one search engine could result in an increased number of peptides being identified. However, such efforts are hindered by the lack of a single scoring framework employed by all search engines.
We have developed a search engine independent scoring framework based on FDR which allows peptide identifications from different search engines to be combined, called the FDRScore. We observe that peptide identifications made by three search engines are infrequently false positives, and identifications made by only a single search engine, even with a strong score from the source search engine, are significantly more likely to be false positives. We have developed a second score based on the FDR within peptide identifications grouped according to the set of search engines that have made the identification, called the combined FDRScore. We demonstrate by searching large publicly available data sets that the combined FDRScore can differentiate between between correct and incorrect peptide identifications with high accuracy, allowing on average 35% more peptide identifications to be made at a fixed FDR than using a single search engine.
doi:10.1002/pmic.200800473
PMCID: PMC2899855  PMID: 19253293
proteomics; mass spectrometry; decoy database; search engine; scoring; false discovery rate
25.  XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments 
Genome Biology  2010;11(3):R27.
XGAP, a software platform for the integration and analysis of genotype and phenotype data.
We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.
doi:10.1186/gb-2010-11-3-r27
PMCID: PMC2864567  PMID: 20214801

Results 1-25 (31)