{"id":451,"date":"2021-10-21T14:55:05","date_gmt":"2021-10-21T14:55:05","guid":{"rendered":"https:\/\/terrabioappdev.wpenginepowered.com\/explore-biccn-and-nemo-a-treasure-trove-of-resources-for-brain-research-on-the-cloud\/"},"modified":"2023-12-27T04:55:03","modified_gmt":"2023-12-27T04:55:03","slug":"explore-biccn-and-nemo-a-treasure-trove-of-resources-for-brain-research-on-the-cloud","status":"publish","type":"post","link":"https:\/\/terra.bio\/explore-biccn-and-nemo-a-treasure-trove-of-resources-for-brain-research-on-the-cloud\/","title":{"rendered":"Explore BICCN and NeMO: A treasure trove of resources for brain research on the cloud"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">One of the most heartening current trends in the life sciences is the increasing abundance of consortium-based research projects that are explicitly committed to generating large data resources and sharing these with the wider research community. There&#8217;s a lot to say about how this approach can maximize impact, reduce duplication of effort and increase participation across the board \u2014 but what better way to make that case than by a concrete example.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Specifically, let&#8217;s take a look at the BRAIN Initiative Cell Census Network (BICCN), a research program within the <\/span><a href=\"https:\/\/braininitiative.nih.gov\/\"><span style=\"font-weight: 400;\">NIH&#8217;s BRAIN Initiative<\/span><\/a><span style=\"font-weight: 400;\"> that seeks to identify and catalog the diverse cell types in human, monkey and mouse brains. The program involves a consortium of research teams at over a dozen organizations who are conducting different projects looking at various aspects of brain development, with a variety of experimental strategies and assays.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The BICCN program recently reached its first major milestone: the completion of an effort to produce comprehensive mapping of mammalian primary motor cortical cell type identities on a molecular level. This milestone is marked by the publication of a &#8220;Flagship Release&#8221;, ie a <\/span><a href=\"https:\/\/www.nature.com\/articles\/s41586-021-03950-0\"><span style=\"font-weight: 400;\">main paper<\/span><\/a><span style=\"font-weight: 400;\"> describing the overall project and findings, as well as a <\/span><a href=\"https:\/\/www.nature.com\/collections\/cicghheddj\"><span style=\"font-weight: 400;\">Nature &#8220;Collection&#8221;<\/span><\/a><span style=\"font-weight: 400;\"> that indexes key studies published so far in the journal by consortium members, accompanied by an editorial and a handful of assorted news features. Some of the member organizations have also written up their own perspectives; for example <\/span><a href=\"https:\/\/www.broadinstitute.org\/news\/single-cell-exploration-mouse-brain-reveals-new-cell-type\"><span style=\"font-weight: 400;\">this Broad Institute news article<\/span><\/a><span style=\"font-weight: 400;\"> about the work of Evan Macosko and colleagues.\u00a0<\/span><\/p>\n<p><b><i>Save the date:<\/i><\/b><i><span style=\"font-weight: 400;\"> There will be a <\/span><\/i><a href=\"https:\/\/alleninstitute.org\/what-we-do\/brain-science\/events-training\/biccn-flagship-release\/\"><i><span style=\"font-weight: 400;\">live webinar<\/span><\/i><\/a><i><span style=\"font-weight: 400;\"> on Wednesday, October 27, 2021 featuring lead investigators from the BICCN consortium who will discuss their findings.<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400;\">What I find really exciting however is that this effort goes beyond &#8220;just&#8221; being a collection of papers from consortium members. The BICCN program dedicates significant effort to making the data and tools used in their papers widely available to the research community, so that others can reproduce and build upon the work presented in the papers.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, they have built a data repository called the <\/span><a href=\"https:\/\/nemoarchive.org\/\"><span style=\"font-weight: 400;\">Neuroscience Multi-Omic Archive<\/span><\/a><span style=\"font-weight: 400;\">, aka NeMO, that provides access to all the transcriptomic and epigenomic data generated by BICCN investigators. Importantly, this is not your typical data download portal \u2014 the data is hosted on Google Cloud, and although it is possible to download the files, the portal is designed to facilitate using the data on the cloud directly, without having to download and maintain your own copy.\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span style=\"font-weight: 400;\">From NeMO to Terra\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">The NeMO portal includes a <\/span><a href=\"https:\/\/portal.nemoarchive.org\/\"><span style=\"font-weight: 400;\">data browser interface<\/span><\/a><span style=\"font-weight: 400;\"> that allows you to explore and select BICCN data using various criteria \u2014 organism, assay technology, investigator and so on \u2014 with a &#8220;shopping cart&#8221; paradigm inspired from online stores. When you&#8217;re ready to &#8220;check out&#8221;, the portal provides options to either download a file manifest or sample metadata, or export the data to Terra for analysis on the cloud.\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone size-large wp-image-1120\" src=\"https:\/\/terra.bio\/wp-content\/uploads\/2023\/12\/NeMO-export-1024x386.png\" alt=\"\" width=\"800\" height=\"302\" \/><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Crucially, this export operation does not create a copy of the data that you would then have to maintain and pay to store. Instead, it exports the <\/span><i><span style=\"font-weight: 400;\">metadata<\/span><\/i><span style=\"font-weight: 400;\">, which includes links to the original locations of the data files in the NeMO repositories, to a Terra workspace.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Once there, you can run your own analyses on the data, either through Terra&#8217;s highly scalable workflow execution system or through one of its interactive cloud environments. These come preloaded with applications like Jupyter Notebook and RStudio, as well as popular tool suites like Bioconductor, and can be further customized by installing additional packages. You can integrate the data with your own, or with data from other cloud-based projects and repositories that are connected to Terra in the same way.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Finally, you can publish results (or simply share them privately with collaborators) in the Broad Institute&#8217;s <\/span><a href=\"https:\/\/singlecell.broadinstitute.org\/single_cell\"><span style=\"font-weight: 400;\">Single Cell Portal<\/span><\/a><span style=\"font-weight: 400;\">, which is connected to Terra and provides convenient data exploration and visualization options.\u00a0<\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span style=\"font-weight: 400;\">Get started today<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">To help researchers get started with BICCN data and tools, the NeMO and Terra teams collaborated to create a <\/span><a href=\"https:\/\/app.terra.bio\/#workspaces\/help-gatk\/BICCN_Omics_Workshop\"><span style=\"font-weight: 400;\">tutorial workspace in Terra<\/span><\/a><span style=\"font-weight: 400;\"> that includes instructions for importing example transcriptome sequencing data from NeMO (in FASTQ format) and run a few preconfigured analyses: aligning the data, producing a raw count matrix with quality metrics; filtering, normalizing, and clustering the raw count matrix; and finally, exploring the resulting single-cell data with Seurat in a Jupyter Notebook.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><img decoding=\"async\" class=\"alignnone size-large wp-image-1121\" src=\"https:\/\/terra.bio\/wp-content\/uploads\/2023\/12\/Seurat-notebook-1024x536.png\" alt=\"\" width=\"800\" height=\"419\" \/><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">The NeMO and Terra teams also deliver a variety of workshops online and at conferences, for which the materials are generally posted online. You can find the latest <\/span><a href=\"https:\/\/nemoarchive.org\/biccn-omics-workshop\/index.php\"><span style=\"font-weight: 400;\">BICCN Omics Workshop<\/span><\/a><span style=\"font-weight: 400;\"> materials on the NeMO website; make sure to click the &#8220;Tools Covered&#8221; tab to get a more detailed sense of the content, and the &#8220;Recordings&#8221; tab to access the videos. You&#8217;ll see the resources provided cover a number of topics and tools beyond the NeMO-Terra connection and analysis capabilities.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The video covering the Terra portion of the October 2021 edition of the workshop (aka &#8220;Day 2&#8221; in some descriptions) is available <strong><a href=\"https:\/\/youtu.be\/PNB4osJQ10c\">here<\/a><\/strong>. There is a version from January 2021 that is also applicable if you wanted to get started with that version. That session was given by the Terra team and is documented fully <\/span><a href=\"https:\/\/support.terra.bio\/hc\/en-us\/articles\/360058106951-BICCNomics-workshop-Jan-27-2021\"><span style=\"font-weight: 400;\">here<\/span><\/a><span style=\"font-weight: 400;\">. It introduces the Terra platform and demonstrates step-by-step how to work through the instructions provided in the tutorial workspace to analyze data from NeMO, and how to publish results in the <\/span><a href=\"https:\/\/singlecell.broadinstitute.org\/single_cell\"><span style=\"font-weight: 400;\">Single Cell Portal<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In light of the BICCN&#8217;s recent <\/span><a href=\"https:\/\/alleninstitute.org\/what-we-do\/brain-science\/events-training\/biccn-flagship-release\/\"><span style=\"font-weight: 400;\">Flagship Release<\/span><\/a><span style=\"font-weight: 400;\">, it&#8217;s tremendously exciting to see these extensive resources being made so readily accessible to the wider research community, and we look forward to seeing the many follow-on studies that will build on top of this work.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>An overview of data and analysis resources provided by the BRAIN Initiative Cell Census Network (BICCN) via the Neuroscience Multi-omic Archive (NeMO) and Terra<\/p>\n","protected":false},"author":4,"featured_media":454,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[42,78,31,19,119,66,59,14],"tags":[98,100,164],"class_list":["post-451","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-community","category-data-access","category-ecosystem","category-most-popular","category-most-recent","category-single-cell-transcriptomics","category-single-cell","category-workspaces","tag-brain","tag-nemo","tag-single-cell"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.0 - 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