BICCN Omics Workshop

Summary

The BRAIN Initiative Cell Census Network (BICCN) Omics workshop will highlight the datasets, tools, and resources generated by the BICCN. This virtual event will include hands-on exercises training attendees in the use of cloud and web resources to engage in single-cell transcriptome data analysis and visualization.

The workshop will be held across two half days: January 20th and 27th, 2021. For more information on workshop content, please visit the tabs above. Those interested in the workshop may choose to attend either one or both days.

Register for the workshop here

Agenda

Day 1: Data Exploration - January 20th 2020
12:00 PM - 4:00 PM Eastern

The Data Exploration component will focus on the query and exploration of analyzed data associated with genes and cells. This part of the workshop is geared for the biologist and will provide instruction on the use of a variety of tools for interrogating and visualizing BICCN data. Attendees will approach data in a global as well as local context through hands-on exercises employing various tools. No programming experience is required or expected.

  • Section 1 - Overview of the ecosystem (12:00-12:45)
    • An introduction to the user journeys that will be explored in the workshop and the tools that will be employed.
  • Section 2 - Tools and resources for visualization and query of results (12:45-4:00)
    • Overview of five different tools and resources with associated hands-on exercise
    • Tentative Schedule for Section 2
      • 12:45 - 1:45 NeMO Analytics
      • 1:45 - 2:00 Break
      • 2:00 - 4:00 Epiviz, Brainome, OMB, Catlas

Day 2: Data Processing - January 27th 2020
12:00 PM - 4:00 PM Eastern

The Data Processing component is geared towards bioinformaticians who would like to engage in primary analysis of data using BICCN community pipelines. This segment of the workshop will include instruction on how to find data of interest and download it so it can be used with resources such as ScanPy and Seurat and/or moved to a computational infrastructure such as Terra. Attendees will take the results of the analysis pipelines and transfer them to some of the exploration tools highlighted during the Data Exploration segment of the workshop.

  • Section 3 - Tools and resources for use of BICCN community pipelines
    • Tentative Schedule for Section 3 (12:00-4:00)
      • 12:00 - 12:30 - Intro to Terra/NeMO Portal, Search For Data, and Data Download
      • 12:30 - 1:40 - Run your Workflows
      • 1:40 - 2:30 - Explore data using Notebooks
      • 2:30 - 2:45 - Break
      • 2:45 - 3:15 - Broad Single Cell Portal
      • 3:15 - 3:45 - Wrap-up and Conclusion

Tools Covered

gEAR: Gene Expression Analysis Resource

The Neuroscience Multi-Omic (NeMO) Analytics portal enables web-based visualization and analysis of multi-omic data describing cell types in the developing and adult brain, powered by gEAR and EpiViz. The portal includes single-cell and bulk tissue RNA-seq, ATAC-seq, and ChIP-seq from the fetal human prefrontal cortex, as well as stem cell models of neural induction. The portal will expand to include multiple regions of the developing and adult brain and additional analytical tools.

https://nemoanalytics.org

Broad Single Cell Portal:

Built on top of Terra, the Broad Single Cell Portal is a cloud-based, scalable web application that aims to accelerate reproducible single-cell research through:

  • enabling scientists to transform complex data into actionable insights through interactive visualizations;
  • extending single cell genomics analysis to any scientist by providing curated pipelines and analysis;
  • centralizing downloadable data, visualizations, and analysis to enable reproducible analysis;
  • providing easy and secure sharing mechanisms to support all stages of scientific inquiry.

https://singlecell.broadinstitute.org/single_cell

Epiviz:

Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but in addition allows multiple visualizations of data within genomic regions using scatterplots, heatmaps, and other user-supplied options. It also includes data from the Gene Expression Barcode project for transcriptome visualization.

https://www.cbcb.umd.edu/software/epiviz

NeMO Archive:

The Neuroscience Multi-omic Archive (NeMO Archive) is a data repository specifically focused on the storage and dissemination of omic data generated from the BRAIN Initiative and related brain research projects.

https://nemoarchive.org

Terra:

Terra is a scalable platform for biomedical research that allows you to access data, run analysis tools and collaborate. Analysis capabilities include an automated workflow system for pipelining large scale analyses, as well as flexible computing environments for interactive analysis using popular applications such as Jupyter notebooks, RStudio (alpha), and Galaxy (alpha).

https://app.terra.bio

Brainome:

A genome browser built by the Mukamel lab (https://brainome.ucsd.edu/annoj/BICCN_MOp/) to visualize the cell type-specific transcriptomes and epigenomes of 56 neuronal cell types from the mouse primary motor cortex. Each cell type has 3 tracks, representing its DNA methylation, open chromatin, and gene expression profiles. Users can choose which tracks to show, and how they want to order and color them. The user customizations are recorded in the URL, which can be shared with others or saved for further self explorations. The browser also contains links to other related resources, including a cell browser with UMAP embeddings and clusterings, a mouse brain anatomy browser (Hongwei Dong's lab), and NeMO analytics.

https://brainome.ucsd.edu/portal/tabular/ensemble

Catlas:

The mammalian cerebrum performs high-level sensory, motion control, and cognitive functions through highly specialized cortical structures and subcortical nuclei. Recent surveys of mouse and human brains with single-cell transcriptomics and high-throughput imaging technologies have uncovered hundreds of neuronal cell types and a variety of non-neuronal cell types distributed in different brain regions, but the cell-type specific transcriptional regulatory programs responsible for the unique identity and function of each brain cell type have yet to be elucidated. Here, we probe the accessible chromatin in >800,000 individual cells from 45 regions spanning the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to define 491,818 candidate cis-regulatory DNA elements in 160 distinct cell groups. We link a significant fraction of them to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and facilitate the interpretation of non-coding risk variants associated with various neurological diseases and traits in humans.

http://catlas.org/mousebrain/

OMB: Brain Cell Methylation Viewer

DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution.

Mammalian brain cells are remarkably diverse in gene expression, anatomy, and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. We carried out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single nucleus DNA methylation sequencing (snmC-seq2) to profile 110,294 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum, and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. In the Brain Cell Methylation Viewer, you can interactively explore this single cell methylome dataset in three different ways: 1) Gene viewer: Explore the methylation diversity of one gene at single-cell or cell-type level; 2) Brain region viewer: Explore the cell type composition of adult mouse brain dissection regions and anatomical structures; 3) Cell type viewer: Explore the spatial distribution and methylation signature genes of one cell type.

http://neomorph.salk.edu/omb/home

Github: https://github.com/lhqing/omb

Participating Organizations

  • University of Maryland School Of Medicine, Baltimore MD
  • Institute for Genome Sciences, University of Maryland School of Medicine
  • The Broad Institute, Boston MA
  • The Allen Institute for Brain Sciences, Seattle WA
  • UMD/Genentech
  • University of California San Diego, San Diego, CA
  • Salk Institute
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