Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update from feeds: https://galaxyproject.org/news/2024-09-19-erga-ear/ #117

Conversation

galaxy-social-bot[bot]
Copy link
Contributor

This PR is created automatically by a feeds bot.
Update since 2024-09-06

Processed:
The ERGA Assembly Report - a community-developed Genome Assembly QC Document Using Galaxy

Copy link
Contributor

👋 Hello! I'm your friendly social media assistant. Below are the previews of this post:
posts/feed_bot/galaxy_europe/2024-09-19-erga-ear-group1.md

matrix-eu-announce

A graphical representation of ERGA Assembly Reporting tool in a Galaxy workflow and resultant output PDF report

📝 New blog post Released! https://galaxyproject.org/news/2024-09-19-erga-ear/

The ERGA Assembly Report - a community-developed Genome Assembly QC Document Using Galaxy

Ensuring consistent high-quality genome assemblies from a distributed project with multiple partners, technologies, organisms, and infrastructures requires addressing several key challenges. Often a question arises - How can we ensure that consistent high-quality genomes are generated across such diverse conditions? This can be achieved by adopting FAIR (Findable, Accessible, Interoperable, and Reproducible) principles, standardizing data formats, and utilizing shared bioinformatics pipelines. Automated quality control, benchmarking, and adaptable workflows are crucial for maintaining consistency. Additionally, how can we report our outputs in a robust and reproducible fashion? This involves adhering to rigorous metadata standards, thoroughly documenting methodologies, and sharing data and tools through open-access platforms with version control, ensuring transparency, reproducibility, and interoperability across all outputs.

The ERGA Assembly Report (EAR) is a community-developed Genome Assembly QC document that leverages the Galaxy platform, a highly accessible and user-friendly environment to provide a comprehensive quality control assessment of genome assemblies. This document covers several critical aspects of assembly evaluation. First, Read QC ensures the raw sequencing data meets quality standards before assembly begins. Assembly contiguity \& completeness metrics assess how well the genome has been reconstructed, focusing on factors like scaffold lengths and gaps. Gene completeness is evaluated using tools such as BUSCO to measure how many expected genes are present in the assembly. A contaminant screen helps identify and remove any non-target sequences that may have been introduced during the sequencing process. Finally, the ERGA Assembly Report includes detailed documentation of the software and pipeline versions used in the assembly process to ensure reproducibility and transparency, allowing others to verify or replicate the analysis. By using Galaxy's shared infrastructure, the report supports version control, history sharing, and workflow reuse, which enhances collaboration, transparency, and standardization across the genome assembly community, making it a powerful platform for the ERGA initiative.

Check ERGA Assembly Reporting Tool in Galaxy

mastodon-eu-freiburg

📝 New blog post Released!
https://galaxyproject.org/news/2024-09-19-erga-ear/

The ERGA Assembly Report - a community-developed Genome Assembly QC Document Using Galaxy

Ensuring consistent high-quality genome assemblies from a distributed project with multiple partners, technologies, organisms, and infrastructures requires addressing several key challenges. Often a question arises - How can we ensure that consistent high-quality genomes are generated across such diverse conditions? This can be achieved by adopting (1/6)

FAIR (Findable, Accessible, Interoperable, and Reproducible) principles, standardizing data formats, and utilizing shared bioinformatics pipelines. Automated quality control, benchmarking, and adaptable workflows are crucial for maintaining consistency. Additionally, how can we report our outputs in a robust and reproducible fashion? This involves adhering to rigorous metadata standards, thoroughly documenting methodologies, and sharing data and tools through open-access platforms with (2/6)

version control, ensuring transparency, reproducibility, and interoperability across all outputs.

The ERGA Assembly Report (EAR) is a community-developed Genome Assembly QC document that leverages the Galaxy platform, a highly accessible and user-friendly environment to provide a comprehensive quality control assessment of genome assemblies. This document covers several critical aspects of assembly evaluation. First, Read QC ensures the raw sequencing data meets quality standards before (3/6)

assembly begins. Assembly contiguity & completeness metrics assess how well the genome has been reconstructed, focusing on factors like scaffold lengths and gaps. Gene completeness is evaluated using tools such as BUSCO to measure how many expected genes are present in the assembly. A contaminant screen helps identify and remove any non-target sequences that may have been introduced during the sequencing process. Finally, the ERGA Assembly Report includes detailed documentation of the (4/6)

software and pipeline versions used in the assembly process to ensure reproducibility and transparency, allowing others to verify or replicate the analysis. By using Galaxy's shared infrastructure, the report supports version control, history sharing, and workflow reuse, which enhances collaboration, transparency, and standardization across the genome assembly community, making it a powerful platform for the ERGA initiative.

Check ERGA Assembly Reporting Tool in Galaxy: (5/6)

https://usegalaxy.eu/root?tool_id=make_ear

@[email protected]
#UseGalaxy #GalaxyProject #UniFreiburg #EOSC #EuroScienceGateway (6/6)

A graphical representation of ERGA Assembly Reporting tool in a Galaxy workflow and resultant output PDF report

linkedin-galaxyproject

📝 New blog post Released!
https://galaxyproject.org/news/2024-09-19-erga-ear/

The ERGA Assembly Report - a community-developed Genome Assembly QC Document Using Galaxy

Ensuring consistent high-quality genome assemblies from a distributed project with multiple partners, technologies, organisms, and infrastructures requires addressing several key challenges. Often a question arises - How can we ensure that consistent high-quality genomes are generated across such diverse conditions? This can be achieved by adopting FAIR (Findable, Accessible, Interoperable, and Reproducible) principles, standardizing data formats, and utilizing shared bioinformatics pipelines. Automated quality control, benchmarking, and adaptable workflows are crucial for maintaining consistency. Additionally, how can we report our outputs in a robust and reproducible fashion? This involves adhering to rigorous metadata standards, thoroughly documenting methodologies, and sharing data and tools through open-access platforms with version control, ensuring transparency, reproducibility, and interoperability across all outputs.

The ERGA Assembly Report (EAR) is a community-developed Genome Assembly QC document that leverages the Galaxy platform, a highly accessible and user-friendly environment to provide a comprehensive quality control assessment of genome assemblies. This document covers several critical aspects of assembly evaluation. First, Read QC ensures the raw sequencing data meets quality standards before assembly begins. Assembly contiguity & completeness metrics assess how well the genome has been reconstructed, focusing on factors like scaffold lengths and gaps. Gene completeness is evaluated using tools such as BUSCO to measure how many expected genes are present in the assembly. A contaminant screen helps identify and remove any non-target sequences that may have been introduced during the sequencing process. Finally, the ERGA Assembly Report includes detailed documentation of the software and pipeline versions used in the assembly process to ensure reproducibility and transparency, allowing others to verify or replicate the analysis. By using Galaxy's shared infrastructure, the report supports version control, history sharing, and workflow reuse, which enhances collaboration, transparency, and standardization across the genome assembly community, making it a powerful platform for the ERGA initiative.

Check ERGA Assembly Reporting Tool in Galaxy: https://usegalaxy.eu/root?tool_id=make_ear

#UseGalaxy #GalaxyProject #UniFreiburg #EOSC #EuroScienceGateway

A graphical representation of ERGA Assembly Reporting tool in a Galaxy workflow and resultant output PDF report

Copy link
Contributor

👋 Hello! I'm your friendly social media assistant. Below are the previews of this post:
posts/feed_bot/galaxy_europe/2024-09-19-erga-ear-group2.md

bluesky-galaxyproject

📝 New blog post Released!
https://galaxyproject.org/news/2024-09-19-erga-ear/

The ERGA Assembly Report - a community-developed Genome Assembly QC Document Using Galaxy

Ensuring consistent high-quality genome assemblies from a distributed project with multiple partners, technologies, (1/10)

organisms, and infrastructures requires addressing several key challenges. Often a question arises - How can we ensure that consistent high-quality genomes are generated across such diverse conditions? This can be achieved by adopting FAIR (Findable, Accessible, Interoperable, and (2/10)

Reproducible) principles, standardizing data formats, and utilizing shared bioinformatics pipelines. Automated quality control, benchmarking, and adaptable workflows are crucial for maintaining consistency. Additionally, how can we report our outputs in a robust and reproducible fashion? (3/10)

This involves adhering to rigorous metadata standards, thoroughly documenting methodologies, and sharing data and tools through open-access platforms with version control, ensuring transparency, reproducibility, and interoperability across all outputs.

The ERGA Assembly Report (EAR) is a (4/10)

community-developed Genome Assembly QC document that leverages the Galaxy platform, a highly accessible and user-friendly environment to provide a comprehensive quality control assessment of genome assemblies. This document covers several critical aspects of assembly evaluation. First, Read (5/10)

QC ensures the raw sequencing data meets quality standards before assembly begins. Assembly contiguity & completeness metrics assess how well the genome has been reconstructed, focusing on factors like scaffold lengths and gaps. Gene completeness is evaluated using tools such as BUSCO to (6/10)

measure how many expected genes are present in the assembly. A contaminant screen helps identify and remove any non-target sequences that may have been introduced during the sequencing process. Finally, the ERGA Assembly Report includes detailed documentation of the software and pipeline (7/10)

versions used in the assembly process to ensure reproducibility and transparency, allowing others to verify or replicate the analysis. By using Galaxy's shared infrastructure, the report supports version control, history sharing, and workflow reuse, which enhances collaboration, (8/10)

transparency, and standardization across the genome assembly community, making it a powerful platform for the ERGA initiative.

Check ERGA Assembly Reporting Tool in Galaxy: https://usegalaxy.eu/root?tool_id=make_ear

@galaxyproject.bsky.social
#UseGalaxy #GalaxyProject #UniFreiburg #EOSC (9/10)

#EuroScienceGateway (10/10)

A graphical representation of ERGA Assembly Reporting tool in a Galaxy workflow and resultant output PDF report

@arash77 arash77 closed this Oct 30, 2024
@arash77 arash77 deleted the posts/feed_bot/galaxy_europe/2024-09-19-erga-ear-update-20240920003251 branch October 30, 2024 17:22
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

1 participant