diff --git a/client/index.html b/client/index.html index 2e6c82fee..cd49d006c 100644 --- a/client/index.html +++ b/client/index.html @@ -46,7 +46,7 @@ diff --git a/dev_docs/developer_guidelines.md b/dev_docs/developer_guidelines.md index c29d0839f..9af8c454f 100644 --- a/dev_docs/developer_guidelines.md +++ b/dev_docs/developer_guidelines.md @@ -58,6 +58,24 @@ Puppeteer is a dependency for e2e tests, but it's not used for running Explorer If you want to actually run e2e tests, then you'll need to set up Chromium to enable Puppeteer. [This blog post](https://broddin.be/2022/09/19/fixing-the-chromium-binary-is-not-available-for-arm64/) should show you how to do that on an M1/M2 machine. +### Mocking the dataset-metadata endpoint + +The dataset-metadata endpoint requires using data-portal. A true local build would require running an instance of data-portal locally. An easier solution that works for most use cases is to just mock the response of dataset-metadata. To do this, you can update the `DatasetMetadataAPI` class in `server/app/api/v3.py` to: + +``` +class DatasetMetadataAPI(DatasetResource): + @cache_control(public=True, no_store=True, max_age=0) + @rest_get_dataset_explorer_location_data_adaptor + def get(self, data_adaptor): + with open("server/tests/fixtures/liver_dataset_metadata_response.json", "r") as file: + mock_response = json.load(file) + + json_response = json.dumps(mock_response) + return Response(json_response, content_type='application/json') +``` + +Note that you'll need to `import json` and also add `Response` to the `flask` import. This will mock the expected response to the `liver.cxg` dataset that is in the `example-dataset/` directory. After updating the mock response, you can build the backend + frontend the same way you normally would. + ### Before you request a PR review... 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Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human liver\u2019s parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.", + "collection_links": [ + { + "link_name": "", + "link_type": "OTHER", + "link_url": "https://github.com/tallulandrews/Liver_sc_sn_paper_scripts" + }, + { + "link_name": "GSE185477", + "link_type": "RAW_DATA", + "link_url": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE185477" + }, + { + "link_name": "", + "link_type": "RAW_DATA", + "link_url": "https://data.humancellatlas.org/explore/projects/8a666b76-daaf-4b1f-9414-e4807a1d1e8b" + }, + { + "link_name": "", + "link_type": "PROTOCOL", + "link_url": "https://www.protocols.io/view/human-liver-caudate-lobe-dissociation-for-scrna-se-q26g77j1gwz1/v2" + }, + { + "link_name": "", + "link_type": "OTHER", + "link_url": "https://macparlandlab.shinyapps.io/healthylivermapspatialgui/" + }, + { + "link_type": "DOI", + "link_url": "https://doi.org/10.1002/hep4.1854" + } + ], + "collection_name": "Single-Cell, Single-Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity", + "collection_publisher_metadata": { + "authors": [ + { + "family": "Andrews", + "given": "Tallulah S." + }, + { + "family": "Atif", + "given": "Jawairia" + }, + { + "family": "Liu", + "given": "Jeff C." + }, + { + "family": "Perciani", + "given": "Catia T." + }, + { + "family": "Ma", + "given": "Xue\u2010Zhong" + }, + { + "family": "Thoeni", + "given": "Cornelia" + }, + { + "family": "Slyper", + "given": "Michal" + }, + { + "family": "Eraslan", + "given": "G\u00f6kcen" + }, + { + "family": "Segerstolpe", + "given": "Asa" + }, + { + "family": "Manuel", + "given": "Justin" + }, + { + "family": "Chung", + "given": "Sai" + }, + { + "family": "Winter", + "given": "Erin" + }, + { + "family": "Cirlan", + "given": "Iulia" + }, + { + "family": "Khuu", + "given": "Nicholas" + }, + { + "family": "Fischer", + "given": "Sandra" + }, + { + "family": "Rozenblatt\u2010Rosen", + "given": "Orit" + }, + { + "family": "Regev", + "given": "Aviv" + }, + { + "family": "McGilvray", + "given": "Ian D." + }, + { + "family": "Bader", + "given": "Gary D." + }, + { + "family": "MacParland", + "given": "Sonya A." + } + ], + "is_preprint": false, + "journal": "Hepatology Communications", + "published_at": 1648771200.0, + "published_day": 1, + "published_month": 4, + "published_year": 2022 + }, + "collection_url": "https://cellxgene.cziscience.com/collections/44531dd9-1388-4416-a117-af0a99de2294", + "dataset_id": "90c609bd-1439-4cbf-935f-201ecadf0297", + "dataset_name": "Healthy human liver: B cells" + } +} \ No newline at end of file