%1 services

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

This project will be led by the ELIXIR Proteomics Community in collaboration with members of the Metabolomics Community and three ELIXIR platforms. High-throughput proteomics has become a popular choice in biological, biomedical and clinical studies and led to the development of hundreds of bioinformatics tools and data analysis pipelines. Given their large diversity, there is a urgent need to compare and benchmark different software pipelines over a large data spectrum.

This study aims to create the framework to benchmark proteomics data analysis workflows, to be built upon and improve resources from ELIXIR Tool, Data and Compute platforms by creating an interface between them linked with public proteomics data and open source stand-alone software and pipelines.

The involved data will be annotated with at least EOSC minimum information according to ELIXIR metadata standards. Our benchmarking will identify robust workflows and therefore nurture the proteomics community with high quality standards required for reproducible research and clinical applications.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

To dramatically improve the reusability of public proteomics datasets by substantially increasing the amount and quality of technical and biological annotations for datasets stored in the PRIDE database.

First, we will develop a posteriori annotation system for PRIDE, for both technical as well as biological metadata, which will leverage the unique synergies of already existing tools and pipelines developed by different ELIXIR nodes. Second, we will create data structures that can capture the most-frequently used experimental designs in proteomics studies. Third, an appropriate API will be built to allow annotation tools to be developed easily. Fourth, we will reach out to actively involve the whole proteomics community in the annotation process.

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

An ELIXIR implementation study started in February 2017, as a collaboration between EMBL-EBI and ELIXIR-DE. Its main objective is to develop open, robust, scalable and reproducible proteomics data analysis workflows based on OpenMS, directly connected to the PRIDE database (an ELIXIR core data resource) and to deploy these pipelines in the EMBL-EBI "Embassy Cloud" as a proof of concept.

Building on this work, we here propose a follow-up project that has three objectives: 

1. The inclusion of additional open tools developed by other ELIXIR nodes
2. The improvement of the overall infrastructure supporting the implementation of proteomics data analysis pipelines
3. The inclusion of quality control pipelines.

The overarching goal is that these tools can be deployed in other cloud infrastructures, and can be easily reused by anyone in the community, thus bringing the users closer to the tools, and the tools closer to the data.

Impact of the study

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

An ELIXIR implementation study started in February 2017, as a collaboration between EMBL-EBI and ELIXIR-DE. Its main objective is to develop open, robust, scalable and reproducible proteomics data analysis workflows based on OpenMS, directly connected to the PRIDE database (an ELIXIR core data resource) and to deploy these pipelines in the EMBL-EBI "Embassy Cloud" as a proof of concept.

Building on this work, we here propose a follow-up project that has three objectives: 

1. The inclusion of additional open tools developed by other ELIXIR nodes
2. The improvement of the overall infrastructure supporting the implementation of proteomics data analysis pipelines
3. The inclusion of quality control pipelines.

The overarching goal is that these tools can be deployed in other cloud infrastructures, and can be easily reused by anyone in the community, thus bringing the users closer to the tools, and the tools closer to the data.

Impact of the study

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

An ELIXIR implementation study started in February 2017, as a collaboration between EMBL-EBI and ELIXIR-DE. Its main objective is to develop open, robust, scalable and reproducible proteomics data analysis workflows based on OpenMS, directly connected to the PRIDE database (an ELIXIR core data resource) and to deploy these pipelines in the EMBL-EBI "Embassy Cloud" as a proof of concept.

Building on this work, we here propose a follow-up project that has three objectives: 

1. The inclusion of additional open tools developed by other ELIXIR nodes
2. The improvement of the overall infrastructure supporting the implementation of proteomics data analysis pipelines
3. The inclusion of quality control pipelines.

The overarching goal is that these tools can be deployed in other cloud infrastructures, and can be easily reused by anyone in the community, thus bringing the users closer to the tools, and the tools closer to the data.

Impact of the study

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

An ELIXIR implementation study started in February 2017, as a collaboration between EMBL-EBI and ELIXIR-DE. Its main objective is to develop open, robust, scalable and reproducible proteomics data analysis workflows based on OpenMS, directly connected to the PRIDE database (an ELIXIR core data resource) and to deploy these pipelines in the EMBL-EBI "Embassy Cloud" as a proof of concept.

Building on this work, we here propose a follow-up project that has three objectives: 

1. The inclusion of additional open tools developed by other ELIXIR nodes
2. The improvement of the overall infrastructure supporting the implementation of proteomics data analysis pipelines
3. The inclusion of quality control pipelines.

The overarching goal is that these tools can be deployed in other cloud infrastructures, and can be easily reused by anyone in the community, thus bringing the users closer to the tools, and the tools closer to the data.

Impact of the study

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

An ELIXIR implementation study started in February 2017, as a collaboration between EMBL-EBI and ELIXIR-DE. Its main objective is to develop open, robust, scalable and reproducible proteomics data analysis workflows based on OpenMS, directly connected to the PRIDE database (an ELIXIR core data resource) and to deploy these pipelines in the EMBL-EBI "Embassy Cloud" as a proof of concept.

Building on this work, we here propose a follow-up project that has three objectives: 

1. The inclusion of additional open tools developed by other ELIXIR nodes
2. The improvement of the overall infrastructure supporting the implementation of proteomics data analysis pipelines
3. The inclusion of quality control pipelines.

The overarching goal is that these tools can be deployed in other cloud infrastructures, and can be easily reused by anyone in the community, thus bringing the users closer to the tools, and the tools closer to the data.

Impact of the study

The outcome will be that an increased range of open proteomics tools will be included in an extended range of cloud infrastructures, including new quality control features based on OpenMS. Impact – increased facility for proteomics analysis across multiple cloud platforms – all with increased degree of quality control.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.

Resulting from the work performed in previous and/or ongoing ELIXIR implementation studies (IS) led by the ELIXIR Proteomics Community, PRIDE public proteomics datasets including metadata annotations using the Sample and Data Relationship Format (SDRF) as well as some open proteomics data analysis pipelines are starting to be available.

In this proposed follow-on IS previous results/outputs will be used as the base to develop a set of open and user-friendly analysis pipelines, which will be applied to assess the possibilities for performing more automated re-analyses using the metadata SDRF-encoded annotations of public datasets, not only at an identification but also on a quantitative and a statistical level for both data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets. Additionally, common ideas in this context and in others overlapping topics of interest will be explored e.g. in a joint gap analysis performed between the ELIXIR Proteomics with the IDP and 3D-BioInfo ELIXIR Communities, to further serve the overall ELIXIR goals.

This study provides a well-documented use case, which will motivate users to perform SDRF-annotations of public datasets. By developing and providing the community with data processing and analysis pipelines as well as by helping to standardize data management and annotation, two goals of the proteomics community will be addressed.