Fetches dataset metadata for datasets matching the search parameters. See below for parameters. Note that some sample metadata are included in the results here, unlike /datasets/{dataset_id}/metadata which only contains dataset metadata. Use query_string=* to return metadata for all datasets. Multiple parameters work as "AND" operator, so platform_type=Microarray&projects=myeloid_atlas,blood_atlas will fetch Microarray datasets under myeloid and blood atlas projects.

Optional parameters:
        dataset_id: comma separated list of dataset ids to restrict the search on
        query_string: perform text search on this query string on dataset (and sample metadata if include_samples_query)
        include_samples_query: if true, query_string will search sample metadata as well as dataset metadata

        platform_type: comma separated list of platform types to restrict the search of datasets on
        projects: comma separated list of projects to restrict the search of datasets on
        organism: comma separated list of organisms to restrict the search of datasets on

        -- The parameters below are probably more useful for the Stemformatics website UI than general use
        and the output format is also slightly different if pagination_limit is specified.
        -- parameters for returning data formatted for a plotly's sunburst plot
        sunburst_inner: sample group (eg. 'cell_type') for inner wheel of sunburst
        sunburst_outer: sample group for outer wheel of sunburst
        sunburst_inner_cutoff: max number of items in the inner wheel
        sunburst_outer_cutoff: max number of items in the outer wheel

        -- parameters filtering data after the search; these work like a sub-query if present, where the counts are not affected
        filter_Project: comma separated list of projects to apply filter on (note capital 'P')
        filter_platform_type: platform type to apply filter on (not comma separated list)
        filter_cell_type: comma separated list of cell types to apply filter on
        filter_tissue_of_origin: comma separated list of tissues to apply filter on

        -- parameters for sorting
        sort_field: sort the list of datasets based on this field; default is 'name'
        sort_ascending: default is true

        -- parameters for pagination
        pagination_limit: number of items per page
        pagination_start: start page

    Example data returned
    [
        {
            "dataset_id": 6741,
            "title": "Transcriptional specialization of human dendritic cell subsets in response to microbial vaccines",
            "authors": "Banchereau R, Baldwin N, Cepika AM, Athale S, Xue Y, Yu CI, Metang P, Cheruku A, Berthier I, Gayet I, Wang Y, Ohouo M, Snipes L, Xu H, Obermoser G, Blankenship D, Oh S, Ramilo O, Chaussabel D, Banchereau J, Palucka K, Pascual V",
            "description": "The mechanisms by which microbial vaccines interact with human APCs remain elusive. Herein, we describe the transcriptional programs induced in human DCs by pathogens, innate receptor ligands and vaccines. Exposure of DCs to influenza, Salmonella enterica and Staphylococcus aureus allows us to build a modular framework containing 204 transcript clusters. We use this framework to characterize the responses of human monocytes, monocyte-derived DCs and blood DC subsets to 13 vaccines. Different vaccines induce distinct transcriptional programs based on pathogen type, adjuvant formulation and APC targeted. Fluzone, Pneumovax and Gardasil, respectively, activate monocyte-derived DCs, monocytes and CD1c+ blood DCs, highlighting APC specialization in response to vaccines. Finally, the blood signatures from individuals vaccinated with Fluzone or infected with influenza reveal a signature of adaptive immunity activation following vaccination and symptomatic infections, but not asymptomatic infections. These data, offered with a web interface, may guide the development of improved vaccines. Abstract from Nat Commun. 2014 Oct 22;5:5283.",
            "platform": "Illumina HumanHT-12 v4.0 Expression BeadChip",
            "private": false,
            "pubmed_id": "25335753",
            "name": "Banchereau_2014_25335753_d",
            "accession": "GSE56744",
            "version": 1.0,
            "platform_type": "Microarray",
            "status": "passed",
            "projects": [
                "myeloid_atlas",
                "blood_atlas",
                "dc_atlas"
            ],
            "samples": 88,
            "cell_type": "CD1c+ dendritic cell,CD141+ dendritic cell",
            "display_name": "Banchereau (2014)"
        },
        ...
    ]
            

Fetches all available values for key in dataset metadata. If include_count is true, returns a dictionary of counts of each value. organism is another parameter available to restrict the search to that organism. Example here is for key=platform&include_count=true. For a full list of available keys, see the example data from /datasets/{dataset_id}/metadata

{
        "Affymetrix Human Genome U133 Plus 2.0 Array [HG-U133_Plus_2]": 90,
        "Affymetrix Human Gene 1.0 ST Array [HuGene-1_0-st]": 52,
        "Illumina HumanHT-12 v4.0 Expression BeadChip": 40,
        ...
    }
            

Creates one zip file containing all the files for each dataset specified. Note that this operation may take a long time for many datasets.

    Downloaded files look like this:
        2000_expression_genes.tsv
        2000_expression_probes.tsv
        2000_metadata.tsv
        2000_samples.tsv
    
            

Returns highly expressed genes in specified sample_group and sample_group_item (eg. cell_type=monocyte). The algorithm first finds all datasets where the sample_group_item is defined and find genes with high difference in mean, which is returned as rankScore.

{
        "sampleGroup": "cell_type",
        "sampleGroupItem": "monocyte",
        "rankScore": [
            {
                "geneId": "ENSG00000215458",
                "meanRank": 0.8999700898495135,
                "datasetIds": "1000,6003,6463,6638",
                "count": 4
            },
            {
                "geneId": "ENSG00000174791",
                "meanRank": 0.83232307575388,
                "datasetIds": "1000,6003,6463,6638",
                "count": 4
            },
            ...
        ]
    }
            

Return a dictionary of available atlas types and versions.

{
        "myeloid": {
            "current_version": "1.0",
            "versions": [
                "1.0"
            ],
            "release_notes": [
                "These files correspond to those from www1.stemformatics.org:/var/www/pylons-data/prod/PCAFiles/atlas/, copied on 2021-02-11, and correspond to v7.3 in this versioning system.
"
            ]
        },
        ...
    }
            

Fetches atlas data for atlas_type (one of myeloid,blood,dc). Additional parameters are applicable depending on the item. version specifies a particular version of the atlas to fetch.

For item=coordinates, returns PCA coordinates used by the atlas:
    [
        {
            "index": "1000_1674120023_B",
            "0": -0.3089953429523829,
            "1": -2.331254360290466,
            "2": -3.708666728816238
        },
        {
            "index": "1000_1674120023_F",
            "0": -1.6988969119278687,
            "1": -3.539426275611378,
            "2": -3.028939281330146
        },
        ...
    ]

    For item=samples, returns the sample table:
    [
        {
            "index": "7268_GSM2360259",
            "Cell Type": "hematopoietic multipotent progenitor",
            "Sample Source": "in vitro",
            "Progenitor Type": "pluripotent stem cell",
            "Activation Status": "growth factor",
            "Tissue": "in vitro",
            "Disease State": "normal",
            "Platform Category": "RNASeq"
        },
        ...
    ]

    For item=expression-values, returns expression values for gene_id.
    [
        {
            "index": "ENSG00000118513",
            "1000_1674120023_B": 0.9276657500763824,
            "1000_1674120023_F": 0.6500152765047357,
            "1000_1674120053_B": 0.7045142071494043,
            ...
        }
    ]

    For item=expression-file, file download is served for expression matrix
    For item=genes, file download is served for genes matrix.

    For item=colours-and-ordering, return the dictionary of colours and ordering used for the atlas
    {
        "colours": {
            "Sample Source": {
                "in vivo": "#54E4AD",
                "ex vivo": "#d87e22",
                "in vitro": "#a6611a",
                "in vivo (HuMouse)": "#4c9282"
            },
            ...
        },
        "ordering": {
            "Sample Source": [
                "in vivo",
                "ex vivo",
                "in vitro",
                "in vivo (HuMouse)"
            ],
            ...
        }
    }

    For item=possible-genes, returns matching genes in the atlas for query_string:
    [
        {
            "ensembl": "ENSG00000118513",
            "inclusion": false,
            "symbol": "MYB"
        },
        ...
    ]