BioTuring SpatialX Connector

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Project description

BioTuring SpatialX Connector

Installation

!pip install -U spatialx_connector

Import

import warnings
warnings.filterwarnings("ignore")

import os

import spatialx_connector
from spatialx_connector import SpatialXConnector
from spatialx_connector import Technologies
from spatialx_connector import DefaultGroup
from spatialx_connector import Species
from spatialx_connector import ConnectorKeys
from spatialx_connector import SubmissionElementKeys
from spatialx_connector import ExtendSegmentationSubmission
from spatialx_connector import ExtendExpressionSubmission

Domain and Token

DOMAIN = ""
TOKEN = ""

Explore Account

User's Information

connector = SpatialXConnector(domain=DOMAIN, token=TOKEN)
spatialx_connector.format_print(connector.info)

Groups

spatialx_connector.format_print(connector.groups)

{
    Personal workspace: 0eebe305688d82fe6c5ce361a43c64da
    All members: GLOBAL_GROUP
    BioTuring Public Studies: bioturing_public_studies
}
Storage

AWS buckets

spatialx_connector.format_print(connector.s3)

{
    bioturingpublic: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic
}

Personal/Shared folders

spatialx_connector.format_print(connector.folders)

{
    shared: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/shared_folder/shared
    Converted: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/converted
    Submitted: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/study
    Upload: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/upload
}

Browsing storage

connector.listdir(connector.s3["bioturingpublic"])

[
    'python3.9.13_linux.zip',
    'genes_annotation.human.json',
    'genes_annotation.mouse.json',
    'genes_annotation.primate.json',
    'ontology.mouse.sql',
    'ontology.human.sql',
    'SpatialX_datasets',
    'anotation',
    'binary',
    'examples',
    'mount'
]

connector.listdir(os.path.join(connector.s3["bioturingpublic"], "SpatialX_datasets"))

[
    'AnnData',
    'COSMX_VER1',
    'COSMX_VER2',
    'GeoMx',
    'Human_Colon_Cancer_P2',
    'MERSCOPE_VER1',
    'MERSCOPE_VER2',
    'Slide-Seq',
    'SpatialData'
]

connector.listdir(os.path.join(connector.s3["bioturingpublic"], "SpatialX_datasets/COSMX_VER1"))

['Lung6', 'Lung9_Rep1', 'Lung9_Rep2']
Browsing Studies Information

Listing studies

studies = connector.list_study(
    group=DefaultGroup.PERSONAL_WORKSPACE.value,
    species=Species.HUMAN.value,
)
spatialx_connector.format_print(studies)

Get more details of the first study

study_details = connector.get_study_detail(study_id=studies[0][ConnectorKeys.STUDY_ID.value])
spatialx_connector.format_print(study_details)

Listing samples of the first study

samples = connector.list_sample(study_id=studies[0][ConnectorKeys.STUDY_ID.value])
spatialx_connector.format_print(samples)

Get more details of the first sample of the study

sample_details = connector.get_sample_detail(sample_id=samples[0][ConnectorKeys.SAMPLE_ID.value])
spatialx_connector.format_print(sample_details)

Uploading

uploading_results = connector.upload_file(file_path="/s3/colab/content/xenium/experiment.xenium")
spatialx_connector.format_print(uploading_results)

uploading_results = connector.upload_big_file(file_path="/s3/colab/content/xenium/morphology_mip.ome.tif", debug_mode=True)
spatialx_connector.format_print(uploading_results)

uploading_results = connector.upload_folder(dir_path="/s3/colab/content/xenium", debug_mode=True)
spatialx_connector.format_print(uploading_results)

Submission

Parsing information for submission from data path and technology :

  • data_name: Name of the dataset
  • technology: Technology of the dataset
  • data_path: path to the dataset
Visium_V2_Human_Colon_Cancer_P2_submission_information = connector.parse_data_information(
    data_name="Visium_V2_Human_Colon_Cancer_P2",
    technology=Technologies.VISIUM.value,
    data_path=os.path.join(
        connector.s3["bioturingpublic"],
        "SpatialX_datasets/Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2"
    )
)
spatialx_connector.format_print(Visium_V2_Human_Colon_Cancer_P2_submission_information)

[
    {
        name: Visium_V2_Human_Colon_Cancer_P2
        submission_type: SUBMIT_SPATIAL_BULK
        technology: VISIUM
        files: [
            {
                key: images
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2_tissue_image.btf
            }
            {
                key: matrix
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2_raw_feature_bc_matrix.h5
            }
            {
                key: tissue_positions
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2/spatial/tissue_positions.csv
            }
            {
                key: scalefactors
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Visium_V2_Human_Colon_Cancer_P2/spatial/scalefactors_json.json
            }
        ]
        folders: []
        args: []
        kwargs: []
        identities: []
    }
]

Xenium_V1_Human_Colon_Cancer_P2_submission_information = connector.parse_data_information(
    data_name="Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE",
    technology=Technologies.XENIUM.value,
    data_path=os.path.join(
        connector.s3["bioturingpublic"],
        "SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE"
    )
)
spatialx_connector.format_print(Xenium_V1_Human_Colon_Cancer_P2_submission_information)

[
    {
        name: Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE
        submission_type: SUBMIT_SPATIAL_TRANSCRIPTOMICS
        technology: XENIUM
        files: [
            {
                key: experiment
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/experiment.xenium
            }
            {
                key: images
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/morphology.ome.tif
            }
            {
                key: alignment
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE_he_imagealignment.csv
            }
            {
                key: segmentation
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/cell_boundaries.csv.gz
            }
            {
                key: transcripts
                value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/transcripts.csv.gz
            }
        ]
        folders: []
        args: []
        kwargs: []
        identities: []
    }
]

Submiting new study with one sample and some data to flatform:

  • group: User's group
  • species: Species of the dataset
  • tilte: Title of new study
  • sample_name: Name of new sample
  • sample_data: Information of the data, it should be result or combine of results of connector.parse_data_information
submission_results = connector.submit(
    group=DefaultGroup.PERSONAL_WORKSPACE.value,
    species=Species.HUMAN.value,
    title="Human Colon Cancer - 10xgenomics",
    sample_name="Human_Colon_Cancer_P2",
    sample_data=Xenium_V1_Human_Colon_Cancer_P2_submission_information + Visium_V2_Human_Colon_Cancer_P2_submission_information,
)
spatialx_connector.format_print(submission_results)

{
    study_id: ST-01JMGMH3AT8HH8S23QV8ZC2G9T
    sample_id: SP-01JMGMH408Q5QDH2YPNXRR2WS6
    sample_data: [
        {
            data_id: DA-01JMGMH409ZPBZPQGHBCF4RXF6
            submit_id: SB-01JMGMH408Q5QDH2YPNWG5ZH46
            submit_name: Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE
        }
        {
            data_id: DA-01JMGMH43QEYAC44YPGTQY80XY
            submit_id: SB-01JMGMH43QEYAC44YPGWMFTJ54
            submit_name: Visium_V2_Human_Colon_Cancer_P2
        }
    ]
    submit_id: SB-01JMGMH408Q5QDH2YPNWG5ZH46
    job_id: 2
    err_message:
}

Adding new sample to submitted study:

  • study_id: ID of the submitted study
  • name: Name of new sample
  • sample_data: Information of the data, it should be result or combine of results of connector.parse_data_information
adding_sample_results = connector.add_sample(
    study_id=submission_results[ConnectorKeys.STUDY_ID.value],
    sample_name="Human_Colon_Cancer_P2 - New Sample",
    sample_data=Visium_V2_Human_Colon_Cancer_P2_submission_information,
)
spatialx_connector.format_print(adding_sample_results)

{
    study_id: ST-01JMGMH3AT8HH8S23QV8ZC2G9T
    sample_id: SP-01JMGMH7K19M32CWQ1RH5TBDKM
    sample_data: [
        {
            data_id: DA-01JMGMH7K19M32CWQ1RMY7ZF8A
            submit_id: SB-01JMGMH7K19M32CWQ1RDWJ1KDW
            submit_name: Visium_V2_Human_Colon_Cancer_P2
        }
    ]
    submit_id: SB-01JMGMH7K19M32CWQ1RDWJ1KDW
    job_id: 3
    err_message:
}

Adding new sample data to existed sample:

  • study_id: ID of the submitted study
  • sample_id: ID of the existed sample
  • sample_data: Information of the data, it should be result or combine of results of connector.parse_data_information
adding_sample_data_results = connector.add_sample_data(
    study_id=adding_sample_results[ConnectorKeys.STUDY_ID.value],
    sample_id=adding_sample_results[ConnectorKeys.SAMPLE_ID.value],
    sample_data=Xenium_V1_Human_Colon_Cancer_P2_submission_information,
)
spatialx_connector.format_print(adding_sample_data_results)

{
    study_id: ST-01JMGMH3AT8HH8S23QV8ZC2G9T
    sample_id: SP-01JMGMH7K19M32CWQ1RH5TBDKM
    sample_data: [
        {
            data_id: DA-01JMGMHCZRFGANB8H36BSEBS3V
            submit_id: SB-01JMGMHCZRFGANB8H369FA1ZP7
            submit_name: Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE
        }
    ]
    submit_id: SB-01JMGMHCZRFGANB8H369FA1ZP7
    job_id: 4
    err_message:
}

Parsing submission information for multiple samples:

  • technology: Technology of samples, only support one common technology
  • data_path: Path to directory of multiple datasets, with each sub-folder is a dataset
  • sample_name_mapping: Mapping of sub-folder to sample name
  • data_name_mapping: Mapping of sub-folder to data name
multiple_cosmx_samples_submission_information = connector.parse_multiple_samples_information(
    technology=Technologies.COSMX_VER1.value,
    data_path=os.path.join(connector.s3["bioturingpublic"], "SpatialX_datasets/COSMX_VER1"),
    sample_name_mapping={
        "Lung6": "Human Lung Cancer - Sample 6",
        "Lung9_Rep1": "Human Lung Cancer - Sample 9 Rep 1",
        "Lung9_Rep2": "Human Lung Cancer - Sample 9 Rep 2",
    },
    data_name_mapping={
        "Lung6": "Sample 6",
        "Lung9_Rep1": "Sample 9 Rep 1",
        "Lung9_Rep2": "Sample 9 Rep 2",
    },
)
spatialx_connector.format_print(multiple_cosmx_samples_submission_information)

[
    {
        sample_name: Human Lung Cancer - Sample 6
        data: [
            {
                name: Sample 6
                submission_type: SUBMIT_SPATIAL_TRANSCRIPTOMICS
                technology: COSMX_VER1
                files: [
                    {
                        key: fov_positions
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung6/Lung6-Flat_files_and_images/Lung6_fov_positions_file.csv
                    }
                    {
                        key: transcripts
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung6/Lung6-Flat_files_and_images/Lung6_tx_file.csv
                    }
                ]
                folders: [
                    {
                        key: images
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung6/Lung6-RawMorphologyImages
                    }
                    {
                        key: segmentation
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung6/Lung6-Flat_files_and_images/CellLabels
                    }
                ]
                args: [
                    {
                        key: mpp
                        value: 0.18
                    }
                ]
                kwargs: []
                identities: []
            }
        ]
    }
    {
        sample_name: Human Lung Cancer - Sample 9 Rep 1
        data: [
            {
                name: Sample 9 Rep 1
                submission_type: SUBMIT_SPATIAL_TRANSCRIPTOMICS
                technology: COSMX_VER1
                files: [
                    {
                        key: fov_positions
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep1/Lung9_Rep1-Flat_files_and_images/Lung9_Rep1_fov_positions_file.csv
                    }
                    {
                        key: transcripts
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep1/Lung9_Rep1-Flat_files_and_images/Lung9_Rep1_tx_file.csv
                    }
                ]
                folders: [
                    {
                        key: images
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep1/Lung9_Rep1-RawMorphologyImages
                    }
                    {
                        key: segmentation
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep1/Lung9_Rep1-Flat_files_and_images/CellLabels
                    }
                ]
                args: [
                    {
                        key: mpp
                        value: 0.18
                    }
                ]
                kwargs: []
                identities: []
            }
        ]
    }
    {
        sample_name: Human Lung Cancer - Sample 9 Rep 2
        data: [
            {
                name: Sample 9 Rep 2
                submission_type: SUBMIT_SPATIAL_TRANSCRIPTOMICS
                technology: COSMX_VER1
                files: [
                    {
                        key: fov_positions
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep2/Lung9_Rep2-Flat_files_and_images/Lung9_Rep2_fov_positions_file.csv
                    }
                    {
                        key: transcripts
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep2/Lung9_Rep2-Flat_files_and_images/Lung9_Rep2_tx_file.csv
                    }
                ]
                folders: [
                    {
                        key: images
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep2/Lung9_Rep2-RawMorphologyImages
                    }
                    {
                        key: segmentation
                        value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/COSMX_VER1/Lung9_Rep2/Lung9_Rep2-Flat_files_and_images/CellLabels
                    }
                ]
                args: [
                    {
                        key: mpp
                        value: 0.18
                    }
                ]
                kwargs: []
                identities: []
            }
        ]
    }
]

multiple_samples_submission_results = connector.submit_multiple_samples(
    group=DefaultGroup.PERSONAL_WORKSPACE.value,
    species=Species.HUMAN.value,
    title="Multiple Human Lung Cancer - CosMX Ver1",
    sample_data=multiple_cosmx_samples_submission_information,
)
spatialx_connector.format_print(multiple_samples_submission_results)

[
    {
        study_id: ST-01JMGMHYDGZ6G1VM6QNNYR4492
        sample_id: SP-01JMGMHZ2QWSXH2DHE3C8X6TCZ
        sample_data: [
            {
                data_id: DA-01JMGMHZ2QWSXH2DHE3FBFSD00
                submit_id: SB-01JMGMHZ2QWSXH2DHE38VKV8NS
                submit_name: Sample 6
            }
        ]
        submit_id: SB-01JMGMHZ2QWSXH2DHE38VKV8NS
        job_id: 5
        err_message:
    }
    {
        study_id: ST-01JMGMHYDGZ6G1VM6QNNYR4492
        sample_id: SP-01JMGMHZRSPPD8PH8CS157RWZX
        sample_data: [
            {
                data_id: DA-01JMGMHZRTJQXH6Z32WGYT9MDK
                submit_id: SB-01JMGMHZRSPPD8PH8CRZ0X1C30
                submit_name: Sample 9 Rep 1
            }
        ]
        submit_id: SB-01JMGMHZRSPPD8PH8CRZ0X1C30
        job_id: 6
        err_message:
    }
    {
        study_id: ST-01JMGMHYDGZ6G1VM6QNNYR4492
        sample_id: SP-01JMGMJ0ET0PYY4PRZMKQ9XXDT
        sample_data: [
            {
                data_id: DA-01JMGMJ0ET0PYY4PRZMN6R7SKW
                submit_id: SB-01JMGMJ0ET0PYY4PRZMJ5JF5H7
                submit_name: Sample 9 Rep 2
            }
        ]
        submit_id: SB-01JMGMJ0ET0PYY4PRZMJ5JF5H7
        job_id: 7
        err_message:
    }
]

Getting data_id to add extend elements add run analysis

DATA_ID = submission_results[ConnectorKeys.SAMPLE_DATA.value][0][ConnectorKeys.DATA_ID.value]

Getting more details information of the data

sample_data_info = connector.get_sample_data_detail(DATA_ID)
spatialx_connector.format_print(sample_data_info)

{
    data_id: DA-01JMGMH409ZPBZPQGHBCF4RXF6
    sample_id: SP-01JMGMH408Q5QDH2YPNXRR2WS6
    study_id: ST-01JMGMH3AT8HH8S23QV8ZC2G9T
    submit_id: SB-01JMGMH408Q5QDH2YPNWG5ZH46
    email_id: nhatnm@bioturing.com
    title: Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE
    species_version:
    submission_type: SUBMIT_SPATIAL_TRANSCRIPTOMICS
    technology: XENIUM
    files:
    files_map: [
        {
            key: experiment
            value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/experiment.xenium
        }
        {
            key: images
            value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/morphology.ome.tif
        }
        {
            key: alignment
            value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE_he_imagealignment.csv
        }
        {
            key: segmentation
            value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/cell_boundaries.csv.gz
        }
        {
            key: transcripts
            value: /data/user_data/spatialx/data/4e3de55d66ef57b14c9119c90fd7f4e1/public_cloud/bioturingpublic/SpatialX_datasets/Human_Colon_Cancer_P2/Xenium_V1_Human_Colon_Cancer_P2_CRC_Add_on_FFPE/transcripts.csv.gz
        }
    ]
    folders:
    folders_map: []
    args:
    args_map: []
    identities:
    identities_map: []
    enable_status: 2
    by_bioturing_status: 0
    percent: 1
    setting:
    map_setting: {}
    submit_result: None
    map_submit_result: None
    extend_items:
    map_extend_items: []
    created_at: 1740020158
    updated_at: 1740020159
    job_id: 1
    analysis_id:
    sub_log_path:
}

Adding new segmentation to the data

add_segmentation_result = connector.add_sample_data_element(
    title="Proteomics Segmentation",
    study_id=sample_data_info[ConnectorKeys.STUDY_ID.value],
    sample_id=sample_data_info[ConnectorKeys.SAMPLE_ID.value],
    data_id=sample_data_info[ConnectorKeys.DATA_ID.value],
    adding_types=[ExtendSegmentationSubmission.PARQUET.value],
    paths={
        SubmissionElementKeys.SEGMENTATION.value: os.path.join(
            connector.s3["bioturingpublic"],
            "mount/examples/spatialx/human_pancreas_codex/human_pancreas_segmentation.parquet",
        )
    }
)
spatialx_connector.format_print(add_segmentation_result)

{
    study_id: ST-01JMGMH3AT8HH8S23QV8ZC2G9T
    sample_id: SP-01JMGMH408Q5QDH2YPNXRR2WS6
    sample_data: None
    submit_id: SB-01JMGMJG55Z7QT8V4S8V40M8Q5
    job_id: 8
    err_message:
}

Getting existed elements in the data

sample_data_elements = connector.get_sample_data_elements(DATA_ID)
spatialx_connector.format_print(sample_data_elements)

Adding new expression matrix to the data

add_expression_result = connector.add_sample_data_element(
    title="Proteomics Expression",
    study_id=sample_data_info[ConnectorKeys.STUDY_ID.value],
    sample_id=sample_data_info[ConnectorKeys.SAMPLE_ID.value],
    data_id=sample_data_info[ConnectorKeys.DATA_ID.value],
    adding_types=[ExtendExpressionSubmission.IMPORT_ANNDATA.value],
    paths={
        SubmissionElementKeys.EXPRESSION.value: os.path.join(
            connector.s3["bioturingpublic"],
            "mount/examples/spatialx/human_pancreas_codex/human_pancreas_protein.h5ad",
        ),
    },
    args={
        SubmissionElementKeys.SPATIAL_ID.value: sample_data_elements[SubmissionElementKeys.CELL_CENTERS.value][0],
    }
)
spatialx_connector.format_print(add_expression_result)

Analysis

data_id = submission_results[ConnectorKeys.SAMPLE_DATA.value][-1][ConnectorKeys.DATA_ID.value]
data_id

Embeddings

response = connector.analysis.embeddings.pca(data_id=data_id, title="Connector - PCA")
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGGHV7N620FCZMXWHB03Z1W
    job_id: 3
}

response = connector.analysis.embeddings.scvi(data_id=data_id, title="Connector - scVI", n_top_genes=2000)
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGGKWNF53MJBN8363YJHWEE
    job_id: 4
}

embeddings = connector.analysis.list_embedding(data_id)
spatialx_connector.format_print(embeddings)

    [
        Connector - PCA
        Spatial Cell centers
    ]

response = connector.analysis.embeddings.umap(data_id=data_id, embedding_key=embeddings[0], title="Connector - UMAP")
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGGPV0M7TEWAG5F8T3GDYY1
    job_id: 5
}

response = connector.analysis.embeddings.tsne(data_id=data_id, embedding_key=embeddings[0], title="Connector - tSNE")
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGGQH9ZJE3A8P4JPZRS2JPG
    job_id: 6
}

Clustering

response = connector.analysis.clustering.louvain(
    data_id=data_id,
    embedding_key=embeddings[0],
    resolution=0.1,
    title="Connector - Louvain",
)
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGGSSRGEP7KAKC47ZVBEDPK
    job_id: 7
}

response = connector.analysis.clustering.kmeans(
    data_id=data_id,
    embedding_key=embeddings[0],
    n_clusters=5,
    title="Connector - k-means",
)
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGGY0VS4JR5VAKY5NXANJM1
    job_id: 9
}

Prediction

embeddings = connector.analysis.list_embedding(data_id)
spatialx_connector.format_print(embeddings)

[
    Connector - PCA
    Connector - UMAP
    Connector - scVI
    Connector - tSNE
    Spatial Cell centers
    UMAP - n_neighbors=15
    scVI - 20 latents - 486 top genes
    t-SNE - perplexity=30
]

metadata = connector.analysis.list_metadata(data_id)
spatialx_connector.format_print(metadata)

[
    Connector - Louvain
    Connector - Louvain (1)
    Connector - k-means
    Louvain clustering - resolution=0.1
    Louvain clustering - resolution=0.5
    Louvain clustering - resolution=1
    MetaReference prediction
    MetaReference prediction (1)
    Number of genes
    Number of mRNA transcripts
]

response = connector.analysis.prediction.metadata_reference(
    data_id=data_id,
    cluster_key=metadata[0],
    species=Species.HUMAN.value,
    title="Connector - Metadata Reference",
)
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGM66JYNBRM5E890NTXHFDJ
    job_id: 14
}

Differential Expression

response = connector.analysis.de.differential_expression_genes(
    data_id_1=data_id,
    data_id_2=data_id,
    group_1_indices=[i for i in range(10000)],
    group_2_indices=[i for i in range(10000, 20000)],
    title="Connector - DE genes",
)
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGJZ1WP9EXMFRYHTVJAQE51
    job_id: 10
}

Spatial Analysis

response = connector.analysis.spatial_analysis.region_segmentation(
    data_id=data_id,
    radius=50,
    mpp=0.2125,
    resolution=0.5,
    species=Species.HUMAN.value,
    title="Connector - Region Segmentation",
)
spatialx_connector.format_print(response)

{
    study_id: ST-01JCGFMAK3GBMXBEAE2FYE02DV
    sample_id: SP-01JCGFMB7GEV299VR986Z193DW
    data_id: DA-01JCGFMQ5GHYYEYRQKT0W061RF
    analysis_id: AN-01JCGK68MJXRWVD450CAHS42JV
    job_id: 11
}

Convert data from Lens

!pip install bioturing_connector

Requirement already satisfied: bioturing_connector in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (1.13.0)
Requirement already satisfied: numpy in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from bioturing_connector) (1.26.4)
Requirement already satisfied: pandas in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from bioturing_connector) (2.2.2)
Requirement already satisfied: requests in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from bioturing_connector) (2.32.3)
Requirement already satisfied: requests_toolbelt>=1.0.0 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from bioturing_connector) (1.0.0)
Requirement already satisfied: scipy in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from bioturing_connector) (1.12.0)
Requirement already satisfied: tqdm in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from bioturing_connector) (4.66.4)
Requirement already satisfied: charset-normalizer<4,>=2 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from requests->bioturing_connector) (3.3.2)
Requirement already satisfied: idna<4,>=2.5 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from requests->bioturing_connector) (3.10)
Requirement already satisfied: urllib3<3,>=1.21.1 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from requests->bioturing_connector) (1.26.20)
Requirement already satisfied: certifi>=2017.4.17 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from requests->bioturing_connector) (2024.8.30)
Requirement already satisfied: python-dateutil>=2.8.2 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from pandas->bioturing_connector) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from pandas->bioturing_connector) (2024.2)
Requirement already satisfied: tzdata>=2022.7 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from pandas->bioturing_connector) (2024.2)
Requirement already satisfied: six>=1.5 in /home/nhatnguyen/BioTuring/spatialx/pyapps/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas->bioturing_connector) (1.16.0)

LENS_SC_HOST: str = ""
LENS_SC_TOKEN: str = ""
lens_sc_studies = connector.list_lens_sc_studies(
    host=LENS_SC_HOST, token=LENS_SC_TOKEN,
    group=DefaultGroup.PERSONAL_WORKSPACE,
    species=Species.HUMAN.value,
)
spatialx_connector.format_print(lens_sc_studies)

Connecting to host at https://dev.bioturing.com/lens_sc/api/v1/test_connection
Connection successful
[
    {
        id: 96f6e21e9ac74f74bfe656a2a59ba058
        accession_id: XENIUM
        title: breast
        abstract: TBD
        authors: TBD
        reference: TBD
        species: human
        group_id: 662bd88b50da063e1870a4efc01fe185
    }
    {
        id: 49998dd7de8340c19a0acdd177b71fb4
        accession_id: XENIUM
        title: TBD
        abstract: TBD
        authors: TBD
        reference: TBD
        species: human
        group_id: 662bd88b50da063e1870a4efc01fe185
    }
]

# Convert a study
connector.convert_data_from_lens(lens_sc_studies[0])

LENS_BULK_HOST: str = ""
LENS_BULK_TOKEN: str = ""
lens_bulk_studies = connector.list_lens_bulk_studies(
    host=LENS_BULK_HOST, token=LENS_BULK_TOKEN,
    group=DefaultGroup.PERSONAL_WORKSPACE,
    species=Species.HUMAN.value,
)
spatialx_connector.format_print(lens_bulk_studies)

Connecting to host at https://dev.bioturing.com/lens_bulk/api/v1/test_connection
Connection successful
[
    {
        id: f92a884e42bf43749011d71593e727ba
        accession_id: VISIUM
        title: TBD
        abstract: TBD
        authors: TBD
        reference: TBD
        species: human
        group_id: 662bd88b50da063e1870a4efc01fe185
    }
    {
        id: 8b3e1737007c47fc81667f54ea998740
        accession_id: CURIO
        title: TBD
        abstract: TBD
        authors: TBD
        reference: TBD
        species: human
        group_id: 662bd88b50da063e1870a4efc01fe185
    }
]

# Convert multiple studies
connector.convert_data_from_lens(lens_bulk_studies)

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  • Author: BioTuring

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