From 00d26e07dd6ba008b58afe04c54bcf7e720c4f3a Mon Sep 17 00:00:00 2001 From: Sofia Drobysheva Date: Sun, 8 Sep 2024 16:39:57 +0200 Subject: [PATCH 01/28] .trim() removed to keep new lines between collected versions --- src/content/blog/2024/nextflow-24.04-highlights.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/content/blog/2024/nextflow-24.04-highlights.md b/src/content/blog/2024/nextflow-24.04-highlights.md index adfc444f..845ea8b7 100644 --- a/src/content/blog/2024/nextflow-24.04-highlights.md +++ b/src/content/blog/2024/nextflow-24.04-highlights.md @@ -156,10 +156,10 @@ workflow { Channel.topic('versions') // [!code ++] | unique() | map { process, name, version -> - """ + """\ ${process.tokenize(':').last()}: ${name}: ${version} - """.stripIndent().trim() + """.stripIndent() } | collectFile(name: 'collated_versions.yml') | CUSTOM_DUMPSOFTWAREVERSIONS From c10b894836ec7a1acc896cfd663886b66310c9e6 Mon Sep 17 00:00:00 2001 From: Ken Brewer Date: Wed, 11 Sep 2024 13:44:04 -0700 Subject: [PATCH 02/28] feat: add blog post on bioinformatics core challenges by @lescai (#307) * feat: add blog post on bioinformatics core challenges by @lescai * Update src/content/blog/2024/addressing-bioinformatics-core-challenges.md --------- Co-authored-by: Marcel Ribeiro-Dantas --- .devcontainer/devcontainer.json | 28 ++++++ public/img/blog-2024-09-11--share.png | Bin 0 -> 276440 bytes ...dressing-bioinformatics-core-challenges.md | 80 ++++++++++++++++++ 3 files changed, 108 insertions(+) create mode 100644 .devcontainer/devcontainer.json create mode 100644 public/img/blog-2024-09-11--share.png create mode 100644 src/content/blog/2024/addressing-bioinformatics-core-challenges.md diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json new file mode 100644 index 00000000..83817a80 --- /dev/null +++ b/.devcontainer/devcontainer.json @@ -0,0 +1,28 @@ +// For format details, see https://aka.ms/devcontainer.json. For config options, see the +// README at: https://github.com/devcontainers/templates/tree/main/src/typescript-node +{ + "name": "Node.js & TypeScript", + // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile + "image": "mcr.microsoft.com/devcontainers/typescript-node:1-22-bookworm", + "features": { + "ghcr.io/astronomer/devcontainer-features/astro-cli:1": {}, + "ghcr.io/devcontainers-community/npm-features/prettier:1": { + "version": "3.2.5" + } + } + + // Features to add to the dev container. More info: https://containers.dev/features. + // "features": {}, + + // Use 'forwardPorts' to make a list of ports inside the container available locally. + // "forwardPorts": [], + + // Use 'postCreateCommand' to run commands after the container is created. + // "postCreateCommand": "yarn install", + + // Configure tool-specific properties. + // "customizations": {}, + + // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root. + // "remoteUser": "root" +} diff --git a/public/img/blog-2024-09-11--share.png b/public/img/blog-2024-09-11--share.png new file mode 100644 index 0000000000000000000000000000000000000000..9db243191897c3e2d0730762c3aaf63f205507e2 GIT binary patch literal 276440 zcmYg%1yodP_qT*}=MVx8ib!{Ni-P1ZfOJZSbcw*wCEX<=F{G3JkQyCKf8bXgsZ74;^R=`Jb3T`|AmsA#)Ajwl@A`E7GPoAU#U552mZr$ zQqpyO@Bo+e{vXPN^h^+N5ye$QQRYGU2<;!>4|FSO73l{Ls$y}kO&&f#7qovNC#~g) zvVHS5(d@!&5nF=tilD1?Ejvk6XLx2BfbYz zn}}CAjDKhY(qwH$j>n;^eLD`3@0!?kKRwr{(+>ZrYno)kSXx~-Uq4NWe)=f&%!@NF zDhiz_tS_t&x@bfk)rYmrafdtKezW42(?)uCs-w?^hv3@Hn6$xwnSgp8Bep^k!cb$- z5L|c#f^cPgW-=2{QwSz-@9*zj(YO?=ejF?B)zB311SL~NR7*R0^1pYFgGfr%?w@n! zyuZ=;e>dzDY9k=6=)k5(%+zL{Qxa0>zdLecF;(3YV0<_*ZTrfY>YvL!xv5<|z-2EB zF{1xngm8shfO?2~){+i#xdJWzp$McOLQ-nou?sVy<=({4wMJd?CWbXgu;+~;^2LE8dKn<&Ev(~l&P8lr-8+gNC zX-?yoXn&1x&$9;gNCfg0Qbce?1%3G6UDg5edV^j-Hqzg%H;$-!Q2wVM+fVJLo@d;% 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[path-to-regexp](https://github.com/pillarjs/path-to-regexp) from 6.2.2 to 6.3.0. - [Release notes](https://github.com/pillarjs/path-to-regexp/releases) - [Changelog](https://github.com/pillarjs/path-to-regexp/blob/master/History.md) - [Commits](https://github.com/pillarjs/path-to-regexp/compare/v6.2.2...v6.3.0) --- updated-dependencies: - dependency-name: path-to-regexp dependency-type: indirect ... 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He is bridging between nf-core, GHGA, Galaxy, and the + single cell community. He holds a PhD in Bioinformatics from Freiburg University, Germany. + + Date: Mon, 16 Sep 2024 14:01:01 -0400 Subject: [PATCH 05/28] Stub for Ep 46 of the podcast Missing the youtube ID --- .../podcast/2024/ep46_nextflow_vs_wdl.md | 25 +++++++++++++++++++ 1 file changed, 25 insertions(+) create mode 100644 src/content/podcast/2024/ep46_nextflow_vs_wdl.md diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md new file mode 100644 index 00000000..15ff516b --- /dev/null +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -0,0 +1,25 @@ +--- +title: "Nextflow meets WDL: Comparing modern workflow languages" +episode: 46 +description: How Nextflow compares to WDL +date: 2024-09-17 +type: podcast +subtype: Technical discussion +youtubeid: TBD +image: /img/podcast_ep46.png +tags: Nextflow +author: Developer advocates +icon: logo_podcast_channels.jpg +--- + +Join us to hear Geraldine Van der Auwera chat with Ben Sherman about how Nextflow compares to [WDL](https://openwdl.org/), the Workflow Description Language originally developed at the Broad Institute. After a brief introduction to the history of WDL, Geraldine shares her experience moving to Nextflow, which kicks off a deep dive discussion with Ben about the differences and similarities between the two languages, and Ben shares how he's drawing inspiration from WDL in his quest to further improve Nextflow. We discuss the following technical features: + +- Tasks vs. processes: basically the same thing +- Channels: why they're awesome and how to make it easier to leverage their power +- WDL's scatter functions vs. Nextflow's implicit parallelization +- How many operators does Nextflow really need? +- The benefits of a DSL and the appeal of static types +- Don't make me care about what order to pass inputs in +- The evolution of WDL's runtime block vs Nextflow's config files +- Portability across infrastructure backends: who wore it better? +- Cloud-native vs. HPC-to-cloud \ No newline at end of file From 75a77d5779b0c330a71f3eebde0a8798b27b0d57 Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Mon, 16 Sep 2024 14:02:36 -0400 Subject: [PATCH 06/28] Add cover image For episode 46 --- public/img/podcast_ep46.png | Bin 0 -> 421342 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 public/img/podcast_ep46.png diff --git a/public/img/podcast_ep46.png 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-- Cloud-native vs. HPC-to-cloud \ No newline at end of file +- Cloud-native vs. HPC-to-cloud From 5bac4d8409823ec19bacec0dfd0940febe11d344 Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Mon, 16 Sep 2024 22:03:28 -0400 Subject: [PATCH 08/28] Add episode summary Also fix youtube placeholder --- .../podcast/2024/ep46_nextflow_vs_wdl.md | 41 +++++++++++++++++-- 1 file changed, 38 insertions(+), 3 deletions(-) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index 4b31f999..62a1d9cd 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -5,14 +5,14 @@ description: How Nextflow compares to WDL date: 2024-09-17 type: podcast subtype: Technical discussion -youtubeid: TBD +youtubeid: TBD12345678 image: /img/podcast_ep46.png tags: Nextflow author: Developer advocates icon: logo_podcast_channels.jpg --- -Join us to hear Geraldine Van der Auwera chat with Ben Sherman about how Nextflow compares to [WDL](https://openwdl.org/), the Workflow Description Language originally developed at the Broad Institute. After a brief introduction to the history of WDL, Geraldine shares her experience moving to Nextflow, which kicks off a deep dive discussion with Ben about the differences and similarities between the two languages, and Ben shares how he's drawing inspiration from WDL in his quest to further improve Nextflow. We discuss the following technical features: +In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. We discuss the following technical features: - Tasks vs. processes: basically the same thing - Channels: why they're awesome and how to make it easier to leverage their power @@ -21,5 +21,40 @@ Join us to hear Geraldine Van der Auwera chat with Ben Sherman about how Nextflo - The benefits of a DSL and the appeal of static types - Don't make me care about what order to pass inputs in - The evolution of WDL's runtime block vs Nextflow's config files -- Portability across infrastructure backends: who wore it better? +- Portability across infrastructure backends: who wore it best? - Cloud-native vs. HPC-to-cloud + +## Summary of the episode + +### Introduction +The comparison between Nextflow and WDL (Workflow Description Language) is a fascinating one for anyone involved in bioinformatics and data science workflows. Both languages have their unique strengths and offer different approaches to solving similar problems. This blog post delves into the intricacies of both languages, highlighting their differences, similarities, and areas of potential improvement. + +### Meet the Contributors +Ben Sherman, a software engineer at Seqera and one of the main developers of Nextflow, brings a wealth of experience to the discussion. Geraldine, Lead Developer Advocate at Seqera, offers insights from her extensive past use of WDL. Together, they provide a comparative overview of these two powerful workflow languages. + +### Introduction to WDL +WDL, or Workflow Description Language, was developed at the Broad Institute starting around 2014. This language emerged during a period when existing workflow solutions were struggling to scale with increasing data volumes and the need for greater reproducibility. The Broad Institute, a nonprofit research institution in Cambridge, MA, needed a more effective software stack for its genome analysis pipeline, which was moving to the cloud. +Several workflow management tools were considered, including Queue (integrated with the GATK), Firehose, and Zamboni. The CWL (Common Workflow Language) which was emerging at the time was also reviewed but deemed too machine-oriented. This led to the development of WDL as a user-friendly, cloud-native DSL (domain-specific language) designed for high reproducibility. Today, WDL is an open-source project supported by two main engines: [Cromwell](https://github.com/broadinstitute/cromwell) (focused on high-scale execution) and [MiniWDL](https://github.com/mlin/miniwdl) (geared towards prototyping). + +### WDL Development History +From its inception, WDL was intended to simplify the process of sharing genomic analysis pipelines. With WDL, researchers can share readable, user-friendly scripts, with some limitations. As it evolved, WDL introduced more flexibility while keeping complexity in check. This balance is crucial for maintaining an approachable yet powerful workflow language. + +### Key Differences Between WDL and Nextflow +One of the major differences between Nextflow and WDL lies in their approach to parallelization and data handling. WDL uses explicit task invocation and a scatter function for batch processing. This approach is straightforward but can be limiting in complex scenarios. +On the other hand, Nextflow relies on channels to handle data flow between processes. This abstraction simplifies the user’s code and allows for more compact, readable scripts. Channels can hold single values, lists, or result sets, enabling processes to consume and produce data efficiently. While this implicit handling of data flow can be challenging to learn, it offers significant rewards in process efficiency and code simplicity. + +### Advanced Features of Nextflow +Nextflow processes and channels set it apart from most workflow managers. Inspired by Unix’s pipeline philosophy, Nextflow allows for powerful data manipulation through operators like map, flatMap, and filter. These operators enable users to create flexible, scalable workflows with fewer lines of code. +However, Nextflow's power can also lead to over-engineering in inexperienced hands. The development team continually strives to simplify Nextflow while maintaining its flexibility. For example, integrating static typing and record types could ease the learning curve by clarifying data structures and inputs. + +### Challenges and Improvements in Nextflow +Many of Nextflow's operators might be rethought or merged with standard library functions to simplify the language. Adding features like named parameter passing, similar to WDL, could enhance user-friendliness. Balancing power and simplicity is key to preventing users from creating unnecessarily complex workflows. + +### The Future of Nextflow and WDL +Both Nextflow and WDL have come a long way and continue to evolve. Lessons from WDL's strong typing and static typing system offer valuable insights for Nextflow's development. Borrowing best practices from each other can drive future improvements. + +### Conclusion +The comparison between Nextflow and WDL highlights the strengths of both languages and areas for potential enhancement. While WDL excels in its simplicity and user-friendliness, Nextflow shines in its flexibility and powerful data manipulation capabilities. As both languages continue to develop, they promise to offer even more robust solutions for bioinformatics and data science workflows. Stay tuned for more updates and innovations in both Nextflow and WDL! + +## Resources for newcomers to Nextflow +If you're new to Nextflow and you'd like to give it a try, we recommend starting with the [Hello Nextflow tutorial series](https://training.nextflow.io/hello_nextflow/), which will guide you through the process of writing and running your first Nextflow pipelines. This web-based training uses Gitpod and does not require installing anything on your own computer. From 0609c9959a3e3c697d81c21e2ae4d7335b011511 Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Mon, 16 Sep 2024 22:06:34 -0400 Subject: [PATCH 09/28] Fix linting issue --- src/content/podcast/2024/ep46_nextflow_vs_wdl.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index 62a1d9cd..fdc1e473 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -27,34 +27,44 @@ In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera an ## Summary of the episode ### Introduction + The comparison between Nextflow and WDL (Workflow Description Language) is a fascinating one for anyone involved in bioinformatics and data science workflows. Both languages have their unique strengths and offer different approaches to solving similar problems. This blog post delves into the intricacies of both languages, highlighting their differences, similarities, and areas of potential improvement. ### Meet the Contributors + Ben Sherman, a software engineer at Seqera and one of the main developers of Nextflow, brings a wealth of experience to the discussion. Geraldine, Lead Developer Advocate at Seqera, offers insights from her extensive past use of WDL. Together, they provide a comparative overview of these two powerful workflow languages. ### Introduction to WDL + WDL, or Workflow Description Language, was developed at the Broad Institute starting around 2014. This language emerged during a period when existing workflow solutions were struggling to scale with increasing data volumes and the need for greater reproducibility. The Broad Institute, a nonprofit research institution in Cambridge, MA, needed a more effective software stack for its genome analysis pipeline, which was moving to the cloud. Several workflow management tools were considered, including Queue (integrated with the GATK), Firehose, and Zamboni. The CWL (Common Workflow Language) which was emerging at the time was also reviewed but deemed too machine-oriented. This led to the development of WDL as a user-friendly, cloud-native DSL (domain-specific language) designed for high reproducibility. Today, WDL is an open-source project supported by two main engines: [Cromwell](https://github.com/broadinstitute/cromwell) (focused on high-scale execution) and [MiniWDL](https://github.com/mlin/miniwdl) (geared towards prototyping). ### WDL Development History + From its inception, WDL was intended to simplify the process of sharing genomic analysis pipelines. With WDL, researchers can share readable, user-friendly scripts, with some limitations. As it evolved, WDL introduced more flexibility while keeping complexity in check. This balance is crucial for maintaining an approachable yet powerful workflow language. ### Key Differences Between WDL and Nextflow + One of the major differences between Nextflow and WDL lies in their approach to parallelization and data handling. WDL uses explicit task invocation and a scatter function for batch processing. This approach is straightforward but can be limiting in complex scenarios. On the other hand, Nextflow relies on channels to handle data flow between processes. This abstraction simplifies the user’s code and allows for more compact, readable scripts. Channels can hold single values, lists, or result sets, enabling processes to consume and produce data efficiently. While this implicit handling of data flow can be challenging to learn, it offers significant rewards in process efficiency and code simplicity. ### Advanced Features of Nextflow + Nextflow processes and channels set it apart from most workflow managers. Inspired by Unix’s pipeline philosophy, Nextflow allows for powerful data manipulation through operators like map, flatMap, and filter. These operators enable users to create flexible, scalable workflows with fewer lines of code. However, Nextflow's power can also lead to over-engineering in inexperienced hands. The development team continually strives to simplify Nextflow while maintaining its flexibility. For example, integrating static typing and record types could ease the learning curve by clarifying data structures and inputs. ### Challenges and Improvements in Nextflow + Many of Nextflow's operators might be rethought or merged with standard library functions to simplify the language. Adding features like named parameter passing, similar to WDL, could enhance user-friendliness. Balancing power and simplicity is key to preventing users from creating unnecessarily complex workflows. ### The Future of Nextflow and WDL + Both Nextflow and WDL have come a long way and continue to evolve. Lessons from WDL's strong typing and static typing system offer valuable insights for Nextflow's development. Borrowing best practices from each other can drive future improvements. ### Conclusion + The comparison between Nextflow and WDL highlights the strengths of both languages and areas for potential enhancement. While WDL excels in its simplicity and user-friendliness, Nextflow shines in its flexibility and powerful data manipulation capabilities. As both languages continue to develop, they promise to offer even more robust solutions for bioinformatics and data science workflows. Stay tuned for more updates and innovations in both Nextflow and WDL! ## Resources for newcomers to Nextflow + If you're new to Nextflow and you'd like to give it a try, we recommend starting with the [Hello Nextflow tutorial series](https://training.nextflow.io/hello_nextflow/), which will guide you through the process of writing and running your first Nextflow pipelines. This web-based training uses Gitpod and does not require installing anything on your own computer. From 902982f5837e9c5b6f11f6bc52970edd2efcab94 Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Mon, 16 Sep 2024 22:16:53 -0400 Subject: [PATCH 10/28] minor tweaks --- src/content/podcast/2024/ep46_nextflow_vs_wdl.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index fdc1e473..a6872fba 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -1,7 +1,7 @@ --- title: "Nextflow meets WDL: Comparing modern workflow languages" episode: 46 -description: How Nextflow compares to WDL +description: Exploring what Nextflow can learn from WDL date: 2024-09-17 type: podcast subtype: Technical discussion @@ -15,7 +15,7 @@ icon: logo_podcast_channels.jpg In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. We discuss the following technical features: - Tasks vs. processes: basically the same thing -- Channels: why they're awesome and how to make it easier to leverage their power +- Channels: why they're awesome once you 'get it' and how to make it easier to leverage their power - WDL's scatter functions vs. Nextflow's implicit parallelization - How many operators does Nextflow really need? - The benefits of a DSL and the appeal of static types From 5e2fbad7b119fc02c784ca0fafb8cf88772795ec Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Tue, 17 Sep 2024 00:12:26 -0400 Subject: [PATCH 11/28] Add Youtube ID --- src/content/podcast/2024/ep46_nextflow_vs_wdl.md | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index a6872fba..06931b94 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -5,14 +5,18 @@ description: Exploring what Nextflow can learn from WDL date: 2024-09-17 type: podcast subtype: Technical discussion -youtubeid: TBD12345678 +youtubeid: qeJqdV_d8vI image: /img/podcast_ep46.png tags: Nextflow author: Developer advocates icon: logo_podcast_channels.jpg --- -In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. We discuss the following technical features: +In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. + + + +**Some key points from the episode** - Tasks vs. processes: basically the same thing - Channels: why they're awesome once you 'get it' and how to make it easier to leverage their power @@ -24,7 +28,7 @@ In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera an - Portability across infrastructure backends: who wore it best? - Cloud-native vs. HPC-to-cloud -## Summary of the episode +## Podcast overview ### Introduction From b24231f55972823571302303a3488c1e85e183d2 Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Tue, 17 Sep 2024 00:21:57 -0400 Subject: [PATCH 12/28] whitespaaaaace --- src/content/podcast/2024/ep46_nextflow_vs_wdl.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index 06931b94..0c3b5305 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -12,9 +12,9 @@ author: Developer advocates icon: logo_podcast_channels.jpg --- -In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. +In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. - + **Some key points from the episode** From 0596baf4dd3d294246cb34508006ec846e2db2a2 Mon Sep 17 00:00:00 2001 From: Geraldine Van der Auwera Date: Tue, 17 Sep 2024 01:18:25 -0400 Subject: [PATCH 13/28] added last name --- src/content/podcast/2024/ep46_nextflow_vs_wdl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index 0c3b5305..fc78a6cf 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -12,7 +12,7 @@ author: Developer advocates icon: logo_podcast_channels.jpg --- -In this episode of Channels, the Nextflow podcast, host Geraldine from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. +In this episode of Channels, the Nextflow podcast, host Geraldine Van der Auwera from Seqera and her colleague Ben Sherman dive into the differences and similarities between Nextflow and the [Workflow Description Language](https://openwdl.org/) (WDL). They discuss the origins and development of WDL at the Broad Institute, the challenges of working with different workflow languages, and how Nextflow's channel-based data flow model compares to WDL's approach. The conversation covers key features, type systems, and runtime specifications, highlighting the strengths and limitations of both languages. Ben hints at upcoming improvements and enhancements for Nextflow, aimed at making the language more robust and user-friendly. The episode offers valuable insights for bioinformaticians and developers navigating the complexities of workflow management. From 088e267c477eabbdf15c163996e1093c7a640eb4 Mon Sep 17 00:00:00 2001 From: Phil Ewels Date: Tue, 17 Sep 2024 12:41:04 +0200 Subject: [PATCH 14/28] Simplify detail a bit. --- src/content/podcast/2024/ep46_nextflow_vs_wdl.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md index fc78a6cf..17eee6b6 100644 --- a/src/content/podcast/2024/ep46_nextflow_vs_wdl.md +++ b/src/content/podcast/2024/ep46_nextflow_vs_wdl.md @@ -41,7 +41,7 @@ Ben Sherman, a software engineer at Seqera and one of the main developers of Nex ### Introduction to WDL WDL, or Workflow Description Language, was developed at the Broad Institute starting around 2014. This language emerged during a period when existing workflow solutions were struggling to scale with increasing data volumes and the need for greater reproducibility. The Broad Institute, a nonprofit research institution in Cambridge, MA, needed a more effective software stack for its genome analysis pipeline, which was moving to the cloud. -Several workflow management tools were considered, including Queue (integrated with the GATK), Firehose, and Zamboni. The CWL (Common Workflow Language) which was emerging at the time was also reviewed but deemed too machine-oriented. This led to the development of WDL as a user-friendly, cloud-native DSL (domain-specific language) designed for high reproducibility. Today, WDL is an open-source project supported by two main engines: [Cromwell](https://github.com/broadinstitute/cromwell) (focused on high-scale execution) and [MiniWDL](https://github.com/mlin/miniwdl) (geared towards prototyping). +This led to the development of WDL as a user-friendly, cloud-native DSL (domain-specific language) designed for high reproducibility. Today, WDL is an open-source project supported by two main engines: Cromwell (focused on high-scale execution) and MiniWDL (geared towards prototyping). ### WDL Development History From 8a807427f8254e7a94ba2320def07a6593aa8aca Mon Sep 17 00:00:00 2001 From: Marcel Ribeiro-Dantas Date: Thu, 19 Sep 2024 09:19:47 -0300 Subject: [PATCH 15/28] Add links to blog post (#313) --- ...dressing-bioinformatics-core-challenges.md | 20 +++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/src/content/blog/2024/addressing-bioinformatics-core-challenges.md b/src/content/blog/2024/addressing-bioinformatics-core-challenges.md index d6e3573e..b645fc44 100644 --- a/src/content/blog/2024/addressing-bioinformatics-core-challenges.md +++ b/src/content/blog/2024/addressing-bioinformatics-core-challenges.md @@ -12,29 +12,29 @@ community_post: true ambassador_post: true --- -I was honored to be invited to the ISMB 2024 congress to speak at the session organised by the COSI (Community of Special Interest) of Bioinformatics Cores. This session brought together bioinformatics professionals from around the world who manage bioinformatics facilities in different institutions to share experiences, discuss challenges, and explore solutions for managing and analyzing large-scale biological data. In this session, I had the opportunity to introduce Nextflow, and discuss how its adoption can help bioinformatics cores to address some of the most common challenges they face. From managing complex pipelines to optimizing resource utilization, Nextflow offers a range of benefits that can streamline workflows and improve productivity. In this blog, I'll summarize my talk and share insights on how Nextflow can help overcome some of those challenges, including meeting the needs of a wide range of users or customers, automate reporting, customising pipelines and training. +I was honored to be invited to the [ISMB 2024](https://www.iscb.org/ismb2024/home) congress to speak at the session organised by the COSI (Community of Special Interest) of Bioinformatics Cores. This session brought together bioinformatics professionals from around the world who manage bioinformatics facilities in different institutions to share experiences, discuss challenges, and explore solutions for managing and analyzing large-scale biological data. In this session, I had the opportunity to introduce Nextflow, and discuss how its adoption can help bioinformatics cores to address some of the most common challenges they face. From managing complex pipelines to optimizing resource utilization, Nextflow offers a range of benefits that can streamline workflows and improve productivity. In this blog, I'll summarize my talk and share insights on how Nextflow can help overcome some of those challenges, including meeting the needs of a wide range of users or customers, automate reporting, customising pipelines and training. ### Challenge 1: running multiple services _Challenge description: “I have a wide range of stakeholders, and my pipelines need to address different needs in multiple scientific domains”_ -One of the biggest challenges faced by bioinformatics cores is catering to a diverse range of users with varying applications. On one hand, one might need to run analyses for researchers focused on cancer or human genetics. On the other hand, one may also need to support scientists working with mass spectrometry or metagenomics. Fortunately, the nf-core community has made it relatively easy to tackle these diverse needs with their curated pipelines. These pipelines are ready to use, covering a broad spectrum of applications, from genomics and metagenomics to immunology and mass spectrometry. In one of my slides I showed a non-exhaustive list, which spans genomics, metagenomics, immunology, mass spec, and more: one can find best-practice pipelines for almost any bioinformatics application imaginable, including emerging areas like imaging and spatial-omics. By leveraging this framework, one can not only tap into the expertise of the pipeline developers but also engage with them to discuss specific needs and requirements. This collaborative approach can significantly ease the deployment of a workflow, allowing the user to focus on high-priority tasks while ensuring that the analyses are always up to date and aligned with current best practices. +One of the biggest challenges faced by bioinformatics cores is catering to a diverse range of users with varying applications. On one hand, one might need to run analyses for researchers focused on cancer or human genetics. On the other hand, one may also need to support scientists working with mass spectrometry or metagenomics. Fortunately, the [nf-core](https://nf-co.re) community has made it relatively easy to tackle these diverse needs with their curated pipelines. These pipelines are ready to use, covering a broad spectrum of applications, from genomics and metagenomics to immunology and mass spectrometry. In one of my slides I showed a non-exhaustive list, which spans genomics, metagenomics, immunology, mass spec, and more: one can find best-practice pipelines for almost any bioinformatics application imaginable, including emerging areas like imaging and spatial-omics. By leveraging this framework, one can not only tap into the expertise of the pipeline developers but also engage with them to discuss specific needs and requirements. This collaborative approach can significantly ease the deployment of a workflow, allowing the user to focus on high-priority tasks while ensuring that the analyses are always up to date and aligned with current best practices. ### Challenge 2: customising applications _Challenge description: “We often need to customise our applications and pipeline, to meet specific in-house needs of our users”_ -While ready-to-use applications are a huge advantage, there are times when customisation is necessary. Perhaps the standard pipeline that works for most users doesn't quite meet the specific needs of a facilities user or customer. Fortunately, the nf-core community has got these cases covered. With over 1,300 modules at everyone’s disposal, one can easily compose their own pipeline using the nf-core components and tooling. Should that not be enough though, one can even create a pipeline from scratch using nf-core tools. For instance, one can run a simple command like “nf-core create” followed by the name of the pipeline, and voilà! The software package will create a complete skeleton for the pipeline, filled with pre-compiled code and placeholders to ease customisation. This process is incredibly quick, as I demonstrated in a video clip during the talk, where a pipeline skeleton was created in just a few moments. +While ready-to-use applications are a huge advantage, there are times when customisation is necessary. Perhaps the standard pipeline that works for most users doesn't quite meet the specific needs of a facilities user or customer. Fortunately, the nf-core community has got these cases covered. With over 1,300 modules at everyone’s disposal, one can easily compose their own pipeline using the nf-core components and tooling. Should that not be enough though, one can even create a pipeline from scratch using nf-core tools. For instance, one can run a simple command like “[nf-core create](https://nf-co.re/docs/nf-core-tools/pipelines/create)” followed by the name of the pipeline, and voilà! The software package will create a complete skeleton for the pipeline, filled with pre-compiled code and placeholders to ease customisation. This process is incredibly quick, as I demonstrated in a video clip during the talk, where a pipeline skeleton was created in just a few moments. -Of course, customisation isn't limited to pipelines. It also applies to containers, which are a crucial enabler of portability. When it comes to containers, Nextflow users have two options: an easy way and a more advanced approach. The easy way involves using Seqera Containers, a platform that allows anyone to compose a container using tools from bioconda, pypi, and conda-forge. No need for logging in, just select the tools, and the URL of your container will be made available in no time. One can build containers for either Docker or Singularity, and for different platforms (amd64 or arm64). +Of course, customisation isn't limited to pipelines. It also applies to containers, which are a crucial enabler of portability. When it comes to containers, Nextflow users have two options: an easy way and a more advanced approach. The easy way involves using [Seqera Containers](https://seqera.io/containers/), a platform that allows anyone to compose a container using tools from bioconda, pypi, and conda-forge. No need for logging in, just select the tools, and the URL of your container will be made available in no time. One can build containers for either Docker or Singularity, and for different platforms (amd64 or arm64). -If one is looking for more control, they can use Wave as a command line. This is a powerful tool that can act as an intermediary between the user and a container registry. Wave builds containers on the fly, allowing anyone to pass a wave build command as an evaluation inside a docker run command. It's incredibly fast, and builds containers from conda packages in a matter of seconds. Wave, which is also the engine behind Seqera Containers, can be extremely handy to allow other operations like container augmentation. This feature enables a user to add new layers to existing containers without having to rebuild them, thanks to Docker's layer-based architecture. One can simply create a folder where configuration files or executable scripts are located, pass the folder to Wave which will add the folder with a new layer, and get the URL of the augmented container on the fly. +If one is looking for more control, they can use [Wave](https://seqera.io/wave/) as a command line. This is a powerful tool that can act as an intermediary between the user and a container registry. Wave builds containers on the fly, allowing anyone to pass a wave build command as an evaluation inside a docker run command. It's incredibly fast, and builds containers from conda packages in a matter of seconds. Wave, which is also the engine behind Seqera Containers, can be extremely handy to allow other operations like container augmentation. This feature enables a user to add new layers to existing containers without having to rebuild them, thanks to Docker's layer-based architecture. One can simply create a folder where configuration files or executable scripts are located, pass the folder to Wave which will add the folder with a new layer, and get the URL of the augmented container on the fly. ### Challenge 3: Reporting _Challenge description: “I need to deliver a clear report of the analysis results, in a format that is accessible and can be used for publication purposes by my users”_ -Reporting is a crucial aspect of any bioinformatics pipeline, and as for customisation Nextflow offers different ways to approach it. suitable for different levels of expertise. The most straightforward solution involves running MultiQC, a tool that collects the output and logs of a wide range of software in a pipeline and generates a nicely formatted HTML report. This is a great option if one wants a quick and easy way to get a summary of their pipeline's results. MultiQC is a widely used tool that supports a huge list (and growing) of bioinformatics tools and file formats, making it a great choice for many use cases. +Reporting is a crucial aspect of any bioinformatics pipeline, and as for customisation Nextflow offers different ways to approach it. suitable for different levels of expertise. The most straightforward solution involves running [MultiQC](https://seqera.io/multiqc/), a tool that collects the output and logs of a wide range of software in a pipeline and generates a nicely formatted HTML report. This is a great option if one wants a quick and easy way to get a summary of their pipeline's results. MultiQC is a widely used tool that supports a huge list (and growing) of bioinformatics tools and file formats, making it a great choice for many use cases. However, if the developer needs more control over the reporting process or wants to create a custom report that meets some specific needs, it is entirely possible to engineer the reports from scratch. This involves collecting the outputs from various processes in the pipeline and passing them as an input to a process that runs an R Markdown or Quarto script. R Markdown and Quarto are popular tools for creating dynamic documents that can be parameterised, allowing anyone to customize the content and the layout of a report dynamically. By using this approach, one can create a report that is tailored to your specific needs, including the types of plots and visualizations they want to include, the formatting and layouting, branding, and anything specific one might want to highlight. @@ -50,7 +50,7 @@ With Nextflow, the user can track the resources used by each process in your pip But monitoring isn't just about optimising a pipeline's performance - it's also about reducing the environmental impact where possible. A recently developed Nextflow plugin allows to track the carbon footprint of a pipeline, including the energy consumption and greenhouse gas emissions associated with running that pipeline. This information allows one to make informed decisions about their environmental impact, and gaining better awareness or even adopting greener strategies to computing. -One of the key benefits of Nextflow’s monitoring system is its flexibility. The user can either use the built-in html reports for trace and pipeline execution, or could monitor a run live by connecting to Seqera Platform and visualising its progress on a graphical interface in real time. More expert or creative users could use the trace file produced by a Nextflow execution, to create their own metrics and visualisations. +One of the key benefits of Nextflow’s monitoring system is its flexibility. The user can either use the built-in html reports for trace and pipeline execution, or could monitor a run live by connecting to [Seqera Platform](https://seqera.io/platform/) and visualising its progress on a graphical interface in real time. More expert or creative users could use the trace file produced by a Nextflow execution, to create their own metrics and visualisations. ### Challenge 5: User accessibility @@ -58,7 +58,7 @@ _Challenge description: “I could balance workloads better, by giving users a c User accessibility is a crucial aspect of pipeline development, as it enables users with varying levels of bioinformatics experience to run complex pipelines with ease. One of the advantages of Nextflow, is that a developer can create pipelines that are not only robust and efficient but also user-friendly. Allowing your users to run them with a certain level of autonomy might be a good strategy in a bioinformatics core to decentralise straightforward analyses and invest human resources on more complex projects. Empowering a facility’s users to run specific pipelines independently could be a solution to reduce certain workloads. -The nf-core template includes a parameters schema, which is captured by the nf-core website to create a graphical interface for parameters configuration of the pipelines hosted under the nf-core organisation on GitHub. This interface allows users to fill in the necessary fields for parameters needed to run a pipeline, and allows even users with minimal experience with bioinformatics or command-line interfaces to quickly set up a run. The user can then simply copy and paste the command generated by the webpage into a terminal, and the pipeline will launch as configured. This approach is ideal for users who are familiar with basic computer tasks, and have a very minimal familiarity with a terminal. +The nf-core template includes a parameters schema, which is captured by the nf-core website to create a graphical interface for parameters configuration of the pipelines hosted under the [nf-core organisation on GitHub](https://github.com/nf-core). This interface allows users to fill in the necessary fields for parameters needed to run a pipeline, and allows even users with minimal experience with bioinformatics or command-line interfaces to quickly set up a run. The user can then simply copy and paste the command generated by the webpage into a terminal, and the pipeline will launch as configured. This approach is ideal for users who are familiar with basic computer tasks, and have a very minimal familiarity with a terminal. However, for users with even less bioinformatics experience, Nextflow and the nf-core template together offer an even more intuitive solution. The pipeline can be added to the launcher of the Seqera Platform, and one can provide users with a comprehensive and user-friendly interface that allows them to launch pipelines with ease. This platform offers a range of features, including access to datasets created from sample sheets, the ability to launch pipelines on a wide range of cloud environments as well as on HPC on-premise. A simple graphical interface simplifies the entire process.The Seqera Platform provides in this way a seamless and intuitive experience for users, allowing them to run pipelines without requiring extensive bioinformatics knowledge. @@ -68,9 +68,9 @@ _Challenge description: “Training my team and especially onboarding new team m The final challenge we often face in bioinformatics facilities is training. We all know that training is an ongoing issue, not just because of staff turnover and the need to onboard new recruits, but also because the field is constantly evolving. With new tools, techniques, and technologies emerging all the time, it can be difficult to keep up with the latest developments. However, training is crucial for ensuring that pipelines are robust, efficient, and accurate. -Fortunately, there are now many resources available to help with training. The Nextflow training website, for example, has been completely rebuilt recently and now offers a wealth of material suitable for everyone, from beginners to experts. Whether you're just starting out with Nextflow or are already an experienced user, you'll find plenty of resources to help you improve your skills. From introductory tutorials to advanced guides, the training website has everything you need to get the most out of this workflow manager. +Fortunately, there are now many resources available to help with training. The [Nextflow training website](https://training.nextflow.io), for example, has been completely rebuilt recently and now offers a wealth of material suitable for everyone, from beginners to experts. Whether you're just starting out with Nextflow or are already an experienced user, you'll find plenty of resources to help you improve your skills. From introductory tutorials to advanced guides, the training website has everything you need to get the most out of this workflow manager. -Everyone can access the material at their own pace, but regular training events have been scheduled during the year. Additionally, there is now a network of Nextflow Ambassadors who often organise local training events across the world. Without making comparisons with other solutions, I can easily say that the steep learning curve to get going with Nextflow is just a myth nowadays. The quality of the training material, the examples available, the frequency of events in person or online you can attend to, and more importantly a welcoming community of users, make learning Nextflow quite easy. +Everyone can access the material at their own pace, but regular training events have been scheduled during the year. Additionally, there is now a network of [Nextflow Ambassadors](https://nextflow.io/ambassadors.html) who often organise local training events across the world. Without making comparisons with other solutions, I can easily say that the steep learning curve to get going with Nextflow is just a myth nowadays. The quality of the training material, the examples available, the frequency of events in person or online you can attend to, and more importantly a welcoming community of users, make learning Nextflow quite easy. In my laboratory, usually in a couple of months bachelor students are reasonably confident with the code and with running pipelines and debugging common issues. From f01ea61cfd58d75e7324cef42002445974158155 Mon Sep 17 00:00:00 2001 From: Phil Ewels Date: Mon, 23 Sep 2024 20:05:07 +0200 Subject: [PATCH 16/28] Update forum URL to use canonical permalink Should be more stable in the future. --- src/components/Menu.astro | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/components/Menu.astro b/src/components/Menu.astro index 8eed03b9..7a6d539d 100644 --- a/src/components/Menu.astro +++ b/src/components/Menu.astro @@ -84,7 +84,7 @@ const isHomepage = currentPath === "/" || currentPath === "/index.html";

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100644 --- a/public/robots.txt +++ b/public/robots.txt @@ -1,3 +1,11 @@ +User-agent: atlassian-bot +Allow: / +Disallow: /fonts/ +Disallow: /misc/ +Disallow: /logs/ +Disallow: /tests/ +Disallow: /releases/ + User-agent: * Disallow: /fonts/ Disallow: /misc/ From f500c35f514791495df52161c74ccc312e3c9496 Mon Sep 17 00:00:00 2001 From: Phil Ewels Date: Mon, 21 Oct 2024 17:35:21 +0200 Subject: [PATCH 24/28] Blog navbar: external link --- src/components/Menu.astro | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/components/Menu.astro b/src/components/Menu.astro index 7a6d539d..4a80fe0a 100644 --- a/src/components/Menu.astro +++ b/src/components/Menu.astro @@ -57,7 +57,12 @@ const isHomepage = currentPath === "/" || currentPath === "/index.html";

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z%1$HtC;})#$@#E;R!B|7MDGT9V}yWQ7#o-6@UAF85z|?5GMTD+d1&~lePycEoRhqR zs;j0a;B|=6j_1S3ISDYZ%vi1^dwrHYVeY7(bVnc?su4_!s^Cb!;9lpS3()o7v*YVa zeW=psWR7P6Qh>tBgvr4?!IVr%@gG` z$n?lD$2z8uq$?qlr_E@5C25TPH|2$|K|EYvDm)EMBc0~UGTWaHjBo@Yt3U|wfm1_N z+@G_R3(r*=rsC{HVadwR>PJfKZ}1#Sf60?q{!v;Q zWi71??pgThz}~Tg&wG|?u;V|*fB!sn4Z+Xo7p(RpI#xs05UE~XBv*@C?|=CakC06o zBBe_1t;s + YouTube videos thumbnails + + +### A Pivotal Moment in My Career + +In retrospect, discovering Nextflow has been a pivotal moment in my career, marking a significant transformation in the way I approach bioinformatics workflows. Before Nextflow, I was bound by the limitations of conventional scripting languages like bash, Python, and R—each tool serving its purpose but often leading to inefficiencies, version conflicts, and endless troubleshooting. However, Nextflow offered a fresh perspective, simplifying not only the technical execution of pipelines but also providing a more structured and scalable way to manage complex bioinformatics analyses. What began as a solution to streamline my own workflows quickly evolved into a key part of my professional identity. Nextflow didn't just simplify my day-to-day tasks—it opened doors to collaboration with a global community of like-minded researchers and developers, fostering a sense of connection and shared purpose. I’ve learned, contributed, and grown alongside this community, which has been incredibly rewarding both professionally and personally. +Without Nextflow, I doubt I would have been able to accomplish as much as I have in such a short time. It has allowed me to break through the limitations of manual scripting, enabling me to work on more ambitious projects involving multi-omics data, single-cell analysis, and even spatial transcriptomics. The potential for innovation in this space energizes me, and I’m eager to see how Nextflow will continue to elevate my research to new heights. With its powerful capabilities and ever-growing community, I feel confident that the future holds even greater possibilities for bioinformatics, precision oncology, and beyond. From 86f4b3b855e32d5bb9ea1226129db1d5d136f2d6 Mon Sep 17 00:00:00 2001 From: Phil Ewels Date: Sat, 5 Oct 2024 00:43:47 +0200 Subject: [PATCH 18/28] Add redirects for /vscode and /openvsx --- netlify.toml | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/netlify.toml b/netlify.toml index 0033657b..7096abfc 100644 --- a/netlify.toml +++ b/netlify.toml @@ -4,3 +4,11 @@ [build.environment] NODE_VERSION = "20.11.0" + +[[redirects]] + from = "/vscode" + to = "https://marketplace.visualstudio.com/items?itemName=nextflow.nextflow" + +[[redirects]] + from = "/openvsx" + to = "https://open-vsx.org/extension/nextflow/nextflow" From 9dc0263085a9850e4ac00fb4076d8a92a2c30cf5 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Wed, 11 Sep 2024 23:41:23 +0000 Subject: [PATCH 19/28] Bump dset from 3.1.3 to 3.1.4 Bumps [dset](https://github.com/lukeed/dset) from 3.1.3 to 3.1.4. - [Release notes](https://github.com/lukeed/dset/releases) - [Commits](https://github.com/lukeed/dset/compare/v3.1.3...v3.1.4) --- updated-dependencies: - dependency-name: dset dependency-type: indirect ... Signed-off-by: dependabot[bot] --- package-lock.json | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/package-lock.json b/package-lock.json index a72a4131..472ddd12 100644 --- a/package-lock.json +++ b/package-lock.json @@ -2851,9 +2851,9 @@ "integrity": "sha512-+HlytyjlPKnIG8XuRG8WvmBP8xs8P71y+SKKS6ZXWoEgLuePxtDoUEiH7WkdePWrQ5JBpE6aoVqfZfJUQkjXwA==" }, "node_modules/dset": { - "version": "3.1.3", - "resolved": "https://registry.npmjs.org/dset/-/dset-3.1.3.tgz", - "integrity": "sha512-20TuZZHCEZ2O71q9/+8BwKwZ0QtD9D8ObhrihJPr+vLLYlSuAU3/zL4cSlgbfeoGHTjCSJBa7NGcrF9/Bx/WJQ==", + "version": "3.1.4", + "resolved": "https://registry.npmjs.org/dset/-/dset-3.1.4.tgz", + "integrity": "sha512-2QF/g9/zTaPDc3BjNcVTGoBbXBgYfMTTceLaYcFJ/W9kggFUkhxD/hMEeuLKbugyef9SqAx8cpgwlIP/jinUTA==", "engines": { "node": ">=4" } From 7f66fe31041eb65aa638dc9a3631d497059f68a3 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 17 Sep 2024 19:13:48 +0000 Subject: [PATCH 20/28] Bump vite from 5.4.2 to 5.4.6 Bumps [vite](https://github.com/vitejs/vite/tree/HEAD/packages/vite) from 5.4.2 to 5.4.6. - [Release notes](https://github.com/vitejs/vite/releases) - [Changelog](https://github.com/vitejs/vite/blob/v5.4.6/packages/vite/CHANGELOG.md) - [Commits](https://github.com/vitejs/vite/commits/v5.4.6/packages/vite) --- updated-dependencies: - dependency-name: vite dependency-type: indirect ... Signed-off-by: dependabot[bot] --- package-lock.json | 35 +++++++++++++++-------------------- 1 file changed, 15 insertions(+), 20 deletions(-) diff --git a/package-lock.json b/package-lock.json index 472ddd12..a7ce7bba 100644 --- a/package-lock.json +++ b/package-lock.json @@ -4736,7 +4736,6 @@ "url": "https://github.com/sponsors/ai" } ], - "license": "MIT", "bin": { "nanoid": "bin/nanoid.cjs" }, @@ -5011,10 +5010,9 @@ "integrity": "sha512-Yhpw4T9C6hPpgPeA28us07OJeqZ5EzQTkbfwuhsUg0c237RomFoETJgmp2sa3F/41gfLE6G5cqcYwznmeEeOlQ==" }, "node_modules/picocolors": { - "version": "1.0.1", - "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.0.1.tgz", - "integrity": "sha512-anP1Z8qwhkbmu7MFP5iTt+wQKXgwzf7zTyGlcdzabySa9vd0Xt392U0rVmz9poOaBj0uHJKyyo9/upk0HrEQew==", - "license": "ISC" + "version": "1.1.0", + "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.0.tgz", + "integrity": "sha512-TQ92mBOW0l3LeMeyLV6mzy/kWr8lkd/hp3mTg7wYK7zJhuBStmGMBG0BdeDZS/dZx1IukaX6Bk11zcln25o1Aw==" }, "node_modules/picomatch": { "version": "2.3.1", @@ -5049,9 +5047,9 @@ } }, "node_modules/postcss": { - "version": "8.4.41", - "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.41.tgz", - "integrity": "sha512-TesUflQ0WKZqAvg52PWL6kHgLKP6xB6heTOdoYM0Wt2UHyxNa4K25EZZMgKns3BH1RLVbZCREPpLY0rhnNoHVQ==", + "version": "8.4.47", + "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.4.47.tgz", + "integrity": "sha512-56rxCq7G/XfB4EkXq9Egn5GCqugWvDFjafDOThIdMBsI15iqPqR5r15TfSr1YPYeEI19YeaXMCbY6u88Y76GLQ==", "funding": [ { "type": "opencollective", @@ -5066,11 +5064,10 @@ "url": "https://github.com/sponsors/ai" } ], - "license": "MIT", "dependencies": { "nanoid": "^3.3.7", - "picocolors": "^1.0.1", - "source-map-js": "^1.2.0" + "picocolors": "^1.1.0", + "source-map-js": "^1.2.1" }, "engines": { "node": "^10 || ^12 || >=14" @@ -5701,10 +5698,9 @@ "license": "MIT" }, "node_modules/source-map-js": { - "version": "1.2.0", - "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.0.tgz", - "integrity": "sha512-itJW8lvSA0TXEphiRoawsCksnlf8SyvmFzIhltqAHluXd88pkCd+cXJVHTDwdCr0IzwptSm035IHQktUu1QUMg==", - "license": "BSD-3-Clause", + "version": "1.2.1", + "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz", + "integrity": "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA==", "engines": { "node": ">=0.10.0" } @@ -6152,13 +6148,12 @@ } }, "node_modules/vite": { - "version": "5.4.2", - "resolved": "https://registry.npmjs.org/vite/-/vite-5.4.2.tgz", - "integrity": "sha512-dDrQTRHp5C1fTFzcSaMxjk6vdpKvT+2/mIdE07Gw2ykehT49O0z/VHS3zZ8iV/Gh8BJJKHWOe5RjaNrW5xf/GA==", - "license": "MIT", + "version": "5.4.6", + "resolved": "https://registry.npmjs.org/vite/-/vite-5.4.6.tgz", + "integrity": "sha512-IeL5f8OO5nylsgzd9tq4qD2QqI0k2CQLGrWD0rCN0EQJZpBK5vJAx0I+GDkMOXxQX/OfFHMuLIx6ddAxGX/k+Q==", "dependencies": { "esbuild": "^0.21.3", - "postcss": "^8.4.41", + "postcss": "^8.4.43", "rollup": "^4.20.0" }, "bin": { From 4e212a401952407a6237332eb5ffddb8359685f3 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Tue, 24 Sep 2024 04:16:37 +0000 Subject: [PATCH 21/28] Bump rollup from 4.21.0 to 4.22.4 Bumps [rollup](https://github.com/rollup/rollup) from 4.21.0 to 4.22.4. - [Release notes](https://github.com/rollup/rollup/releases) - [Changelog](https://github.com/rollup/rollup/blob/master/CHANGELOG.md) - [Commits](https://github.com/rollup/rollup/compare/v4.21.0...v4.22.4) --- updated-dependencies: - dependency-name: rollup dependency-type: indirect ... Signed-off-by: dependabot[bot] --- package-lock.json | 151 ++++++++++++++++++++-------------------------- 1 file changed, 67 insertions(+), 84 deletions(-) diff --git a/package-lock.json b/package-lock.json index a7ce7bba..fad1fbf9 100644 --- a/package-lock.json +++ b/package-lock.json @@ -1505,208 +1505,192 @@ "license": "MIT" }, "node_modules/@rollup/rollup-android-arm-eabi": { - "version": "4.21.0", - "resolved": "https://registry.npmjs.org/@rollup/rollup-android-arm-eabi/-/rollup-android-arm-eabi-4.21.0.tgz", - "integrity": "sha512-WTWD8PfoSAJ+qL87lE7votj3syLavxunWhzCnx3XFxFiI/BA/r3X7MUM8dVrH8rb2r4AiO8jJsr3ZjdaftmnfA==", + "version": "4.22.4", + "resolved": "https://registry.npmjs.org/@rollup/rollup-android-arm-eabi/-/rollup-android-arm-eabi-4.22.4.tgz", + "integrity": "sha512-Fxamp4aEZnfPOcGA8KSNEohV8hX7zVHOemC8jVBoBUHu5zpJK/Eu3uJwt6BMgy9fkvzxDaurgj96F/NiLukF2w==", "cpu": [ "arm" ], - "license": "MIT", "optional": true, "os": [ "android" ] }, 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