mjsteinbaugh
commented
1 week ago Thank you to the bcbio-nextgen development team for the incredible effort over the years related to this project.
Open lpantano opened 4 weeks ago
mjsteinbaugh
commented
1 week ago Thank you to the bcbio-nextgen development team for the incredible effort over the years related to this project.
Dear bcbio community,
In 2011, the Harvard Chan Bioinformatics Core began developing bcbio as an open-source framework to tackle challenges in reproducibility and scalability in the field of next-generation sequencing data analysis. Our goal was to apply best practices to applications of sequencing and develop an automated framework that could be widely used by scientists worldwide. This project has been a labor of love for members of our team, and witnessing its growth and impact over the past 13 years has been immensely gratifying. We are deeply grateful to the more than 50 bioinformaticians who have contributed to bcbio. The platform has been cited over 1,400 times, with many papers highlighting significant biological discoveries enabled by our pipelines.
In recent years, changes in personnel, advances in the field, and competing project commitments have made it increasingly challenging to support and continue the development and maintenance of bcbio. At the same time, Nextflow and the nf-core community have seen substantial growth, now hosting numerous globally-used bioinformatics pipelines. We are enthusiastic to join this larger community and to share our best practices within the Nextflow/nf-core framework. We have already contributed to the RNA-seq and small RNA-seq nf-core pipelines and plan to transition other bcbio analyses and new pipelines to nf-core.
We will continue to address bcbio issues that do not require major fixes or new development until the end of the year, after which, we will archive the bcbio-nextgen project on GitHub. We are excited to be launching a suite of open-source analysis templates, bcbioR, for downstream statistical analyses in transcriptomic and epigenomic studies. bcbioR aims to tackle challenges in extracting biological knowledge from complex study designs and data with multiple sources of variability. It offers a collection of flexible templates containing widely accepted genomics methods in commonly used formats, such as Rmarkdown, Rshiny apps, and R/Python scripts, all consolidated into a single R package. The platform integrates seamlessly with outputs from nf-core pipelines, providing a streamlined process from raw data to actionable biological insights. We are committed to assisting users with transitioning to nf-core and extend our heartfelt thanks to everyone who has been a part of the bcbio community.