The Broad Institute’s Data Sciences Platform (DSP) develops production-level data processing pipelines in collaboration with multiple consortia including BICCN. Thank you to everyone who has worked with us to create and improve these pipelines. For more details please see our BICCN collaborators and how to cite the pipelines.
Pipelines are available for multiple data types hosted in the BICCN network, including single-cell and single-nucleus transcriptomics, methylomics, and ATAC-seq data.
Pipelines are cloud-optimized and developed to ensure portability as well as data reproducibility and interoperability. To this aim, the pipelines are:
Each BICCN pipeline (see table above) has a SciCrunch resource identifier (RRID) that can be cited in publications. Follow the SciCrunch citation guidelines.
Example: (Optimus Pipeline, RRID:SCR_018908)
Additionally, please refer to the table above to cite any publications associated with the pipeline.
These pipelines produce outputs and quality control metrics that can be further analyzed and visualized with downstream community resources. Tutorials for combining single-cell transcriptomic data and pipelines with common community tools are available in the following resources:
This tutorial Terra workspace is a step-by-step guide to analyzing BICCN 10x Genomics single-cell data. Using this workspace, researchers learn how to:
This Brain Initiative Cell Census Network (BICCN) virtual workshop guides you through finding data in the Neuroscience Multi-Omic (NeMO) Archive, analyzing that data in Terra through workflows (pipelines) and interactive analysis, then publishing the results to a study in the Single Cell Portal (SCP).
This high-level overview of the BICCN Omics Workshop describes the BICCN Omics workshop content and provides a link to the webinar demonstration.
We thank the following BICCN collaborators and Broad Pipelines Team members for their work on these pipelines:
Our gratitude to the Joseph Ecker Lab and special thanks to Joseph Ecker, Chongyuan Luo, Eran Mukamel, Hanqing Liu, Benjamin Carlin, Dan Moran, and Jeff Korte.
Single-Cell ATAC (scATAC)
Our gratitude to the Bing Ren Lab and special thanks to Bing Ren, Rongxin Fang, Yang Li, Sebastian Preissl, Nick Barkas, and Kylee Degatano.
Smart-seq2 Single Nucleus
Our gratitude to the Allen Institute, the Eran Mukamel Lab, and the NeMO team. Special thanks to Eran Mukamel, Fangming Xie, Zizhen Yao, Changkyu Lee, Jeff Goldy, Brian Herb, Cindy van Velthoven, Carrie McCracken, Kishori Konwar, Farzaneh Khajouei, Jessica Way, and Kylee Degatano.
Our gratitude to Alex Dobin and the Eran Mukamel Lab. Special thanks to Kishori Konwar, Farzaneh Khajouei, Jessica Way, Ambrose Carr, Jishu Xu, Jose Soto, and Nick Barkas. This pipeline is currently being updated for the BICCN; more acknowledgments will be added as the work progresses.