DataImportViaDirectFileUploadApi¶
All URIs are relative to http://localhost
| Method | HTTP request | Description |
|---|---|---|
| StartImportAFileMultipart | POST /api/v1/jobs/import/file/multipart | Import a file as an attachment, optionally with a separate TSV metadata file via multipart/form-data upload |
| StartImportCellsMultipart | POST /api/v1/jobs/import/cells/multipart | Import a group of cell data objects from a TSV file via multipart/form-data upload |
| StartImportExpressionMultipart | POST /api/v1/jobs/import/expression/multipart | Import a TSV file containing any tabular data, optionally with a separate TSV metadata file via multipart/form-data upload |
| StartImportFlowCytometryMultipart | POST /api/v1/jobs/import/flow-cytometry/multipart | Import a FACS file containing flow-cytometry data, optionally with a separate TSV metadata file via multipart/form-data upload |
| StartImportLibrariesMultipart | POST /api/v1/jobs/import/libraries/multipart | Import a group of library metadata objects from a TSV file via multipart/form-data upload |
| StartImportPreparationsMultipart | POST /api/v1/jobs/import/preparations/multipart | Import a group of preparation metadata objects from a TSV file via multipart/form-data upload |
| StartImportSamplesMultipart | POST /api/v1/jobs/import/samples/multipart | Import a group of sample metadata objects from a TSV file via multipart/form-data upload |
| StartImportVariantMultipart | POST /api/v1/jobs/import/variant/multipart | Import a VCF file containing variant data, optionally with a separate TSV metadata file via multipart/form-data |
StartImportAFileMultipart¶
Info StartImportAFileMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_accession = var.study_accession, data_class = var.data_class, metadata_file = var.metadata_file)
Import a file as an attachment, optionally with a separate TSV metadata file via multipart/form-data upload
In order to import a file as an attachment to a study, please fill in the following fields: * data - a file to import as an attachment. The file will be associated with a study and will be searchable by its name and metadata. * metadata - an optional metadata file to be used as the original metadata for the created objects. The file must contain a single record describing the uploaded attachment. * studyAccession - an accession of a study the file will be associated with. * dataClass - file data class with the following possible values: Bulk transcriptomics, Single-cell transcriptomics, Differential abundance (FC, pval, etc.), Pathway analysis, Proteomics, Single-cell proteomics, Metabolomics, Lipidomics, Epigenomics, DNA methylation, Chemoinformatics, Imaging features, Gene panel data, Biomarker data, Physical measures, Blood counts, Other body fluid counts, Long-read sequencing (Nanopore, PacBio), Flow Cytometry (FCS), Spatial transcriptomics, Phenomics, Copy number alterations, Microbiome / Metagenomics, Immune repertoire, Genetic screens (CRISPR / RNAi), Cell imaging, Document, Other. When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"accession\": \"GSF1234567\" }
Example¶
library(odmApi)
# Import a file as an attachment, optionally with a separate TSV metadata file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame | A file to import as an attachment. The file will be associated with a study and will be searchable by its name and metadata.
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_accession <- "study_accession_example" # character | An accession of a study the file will be associated with. (Optional)
var_data_class <- "data_class_example" # character | A mandatory parameter with the value from a limited set of values (see request description). (Optional)
var_metadata_file <- File.new('/path/to/file') # data.frame | The metadata file to be used as the original metadata for the created objects. The file must contain a single record describing the uploaded attachment. (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportAFileMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_accession = var_study_accession, data_class = var_data_class, metadata_file = var_metadata_filedata_file = "result.txt")
result <- api_instance$StartImportAFileMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_accession = var_study_accession, data_class = var_data_class, metadata_file = var_metadata_file)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | A file to import as an attachment. The file will be associated with a study and will be searchable by its name and metadata. | |
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_accession | character | An accession of a study the file will be associated with. | [optional] |
| data_class | character | A mandatory parameter with the value from a limited set of values (see request description). | [optional] |
| metadata_file | data.frame | The metadata file to be used as the original metadata for the created objects. The file must contain a single record describing the uploaded attachment. | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportCellsMultipart¶
Info StartImportCellsMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id)
Import a group of cell data objects from a TSV file via multipart/form-data upload
The endpoint initiates a job to import cell data and creates a Cell Group to manage it. When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"groupAccession\": \"GSF1234567\" } Embedding constraints: * UMAP/t-SNE - Allowed number of dimensions per cell: 0 (absent) or ≥ 2. - If exactly 1 UMAP/t-SNE dimension is provided, the request is invalid. - At most 3 UMAP/t-SNE dimensions are stored; if more than 3 are provided, only the first 3 are kept and the rest are ignored. * PCA - Allowed number of components per cell: 0 (absent) or ≥ 2. - If exactly 1 PCA component is provided, the request is invalid. - At most 100 PCA components are stored; components beyond 100 are ignored.
Example¶
library(odmApi)
# Import a group of cell data objects from a TSV file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportCellsMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_iddata_file = "result.txt")
result <- api_instance$StartImportCellsMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportExpressionMultipart¶
Info StartImportExpressionMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id, template_id = var.template_id, previous_version = var.previous_version, number_of_feature_attributes = var.number_of_feature_attributes, data_class = var.data_class, measurement_separator = var.measurement_separator, metadata_file = var.metadata_file)
Import a TSV file containing any tabular data, optionally with a separate TSV metadata file via multipart/form-data upload
File This operation necessitates a tabular data file. Consult the user guide for a comprehensive understanding of the file content requirements. The endpoint is capable of handling uploads of any data type, which can be detailed in the parameters section, not only Gene Expression data. ## MetadataFile It is also possible to optionally provide a metadata file. This metadata will be used as the original metadata for the created objects. The file is expected to contain single record with metadata describing the uploaded signal file. ## File format * Format: Tab-separated format (TSV), attribute names and record values are separated with tabs (U+0009), lines are separated with CRLF sequence (U+000D U+000A) * Extension: .zip, .gz, .br, .lz4 are supported, treated as archives and get decompressed * Header: the first line is treated as table header that contains attribute names * Records: the second line contains the values for each of the attributes described in the header line. Values represent single string or list of strings. List values are separated using the \"pipe\" | (U+007C) separator. Values are trimmed of whitespace before parsing, and a literal | (U+007C) character may be escaped by repeating it twice. * Skip zeros in original data file: If this option is selected, zeros in the file will be ignored, thus conserving time and space. This option is particularly useful for handling very sparse data such as Single Cell data.¶
Example¶
library(odmApi)
# Import a TSV file containing any tabular data, optionally with a separate TSV metadata file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
var_template_id <- "template_id_example" # character | (Optional)
var_previous_version <- "previous_version_example" # character | (Optional)
var_number_of_feature_attributes <- 56 # integer | Integer value that specifies the number of columns related to the feature in the uploaded data frame, and indicates the starting position of the sample data. This attribute is not needed if the uploaded file is in GCT format. (Optional)
var_data_class <- "data_class_example" # character | A mandatory parameter with the following possible values: `Bulk transcriptomics`, `Single-cell transcriptomics`, `Differential abundance (FC, pval, etc.)`, `Pathway analysis`, `Proteomics`, `Single-cell proteomics`, `Metabolomics`, `Lipidomics`, `Epigenomics`, `DNA methylation`, `Chemoinformatics`, `Imaging features`, `Gene panel data`, `Biomarker data`, `Physical measures`, `Blood counts`, `Other body fluid counts`, `Long-read sequencing (Nanopore, PacBio)`, `Flow Cytometry (FCS)`, `Spatial transcriptomics`, `Phenomics`, `Copy number alterations`, `Microbiome / Metagenomics`, `Immune repertoire`, `Genetic screens (CRISPR / RNAi)`, `Cell imaging`, `Document`, `Other`. In case the parameter is not set the dataClass is automatically defined as `Other`. (Optional)
var_measurement_separator <- "measurement_separator_example" # character | This parameter is necessary when your file contains multiple measurement columns for each sample, library, or preparation. It represents the character that distinguishes the sample/library/preparation name from the measurement name in column headers. Supported separators include `. , : ; _ - / \\\\ |`, with the allowance for multi-character separators. (Optional)
var_metadata_file <- File.new('/path/to/file') # data.frame | (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportExpressionMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id, previous_version = var_previous_version, number_of_feature_attributes = var_number_of_feature_attributes, data_class = var_data_class, measurement_separator = var_measurement_separator, metadata_file = var_metadata_filedata_file = "result.txt")
result <- api_instance$StartImportExpressionMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id, previous_version = var_previous_version, number_of_feature_attributes = var_number_of_feature_attributes, data_class = var_data_class, measurement_separator = var_measurement_separator, metadata_file = var_metadata_file)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
| template_id | character | [optional] | |
| previous_version | character | [optional] | |
| number_of_feature_attributes | integer | Integer value that specifies the number of columns related to the feature in the uploaded data frame, and indicates the starting position of the sample data. This attribute is not needed if the uploaded file is in GCT format. | [optional] |
| data_class | character | A mandatory parameter with the following possible values: `Bulk transcriptomics`, `Single-cell transcriptomics`, `Differential abundance (FC, pval, etc.)`, `Pathway analysis`, `Proteomics`, `Single-cell proteomics`, `Metabolomics`, `Lipidomics`, `Epigenomics`, `DNA methylation`, `Chemoinformatics`, `Imaging features`, `Gene panel data`, `Biomarker data`, `Physical measures`, `Blood counts`, `Other body fluid counts`, `Long-read sequencing (Nanopore, PacBio)`, `Flow Cytometry (FCS)`, `Spatial transcriptomics`, `Phenomics`, `Copy number alterations`, `Microbiome / Metagenomics`, `Immune repertoire`, `Genetic screens (CRISPR / RNAi)`, `Cell imaging`, `Document`, `Other`. In case the parameter is not set the dataClass is automatically defined as `Other`. | [optional] |
| measurement_separator | character | This parameter is necessary when your file contains multiple measurement columns for each sample, library, or preparation. It represents the character that distinguishes the sample/library/preparation name from the measurement name in column headers. Supported separators include `. , : ; _ - / \\ | `, with the allowance for multi-character separators. |
| metadata_file | data.frame | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportFlowCytometryMultipart¶
Info StartImportFlowCytometryMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id, template_id = var.template_id, previous_version = var.previous_version, metadata_file = var.metadata_file)
Import a FACS file containing flow-cytometry data, optionally with a separate TSV metadata file via multipart/form-data upload
This operation necessitates a gated flow cytometry data file, which must be in FACS format. Consult the user guide for a comprehensive understanding of the file content requirements. For flow cytometry data in FCS format use expression endpoint. When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"groupAccession\": \"GSF1234567\" }
Example¶
library(odmApi)
# Import a FACS file containing flow-cytometry data, optionally with a separate TSV metadata file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
var_template_id <- "template_id_example" # character | (Optional)
var_previous_version <- "previous_version_example" # character | (Optional)
var_metadata_file <- File.new('/path/to/file') # data.frame | (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportFlowCytometryMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id, previous_version = var_previous_version, metadata_file = var_metadata_filedata_file = "result.txt")
result <- api_instance$StartImportFlowCytometryMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id, previous_version = var_previous_version, metadata_file = var_metadata_file)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
| template_id | character | [optional] | |
| previous_version | character | [optional] | |
| metadata_file | data.frame | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportLibrariesMultipart¶
Info StartImportLibrariesMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id, template_id = var.template_id)
Import a group of library metadata objects from a TSV file via multipart/form-data upload
When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"groupAccession\": \"GSF1234567\" }
Example¶
library(odmApi)
# Import a group of library metadata objects from a TSV file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
var_template_id <- "template_id_example" # character | (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportLibrariesMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_iddata_file = "result.txt")
result <- api_instance$StartImportLibrariesMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
| template_id | character | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportPreparationsMultipart¶
Info StartImportPreparationsMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id, template_id = var.template_id)
Import a group of preparation metadata objects from a TSV file via multipart/form-data upload
When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"groupAccession\": \"GSF1234567\" }
Example¶
library(odmApi)
# Import a group of preparation metadata objects from a TSV file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
var_template_id <- "template_id_example" # character | (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportPreparationsMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_iddata_file = "result.txt")
result <- api_instance$StartImportPreparationsMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
| template_id | character | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportSamplesMultipart¶
Info StartImportSamplesMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id, template_id = var.template_id)
Import a group of sample metadata objects from a TSV file via multipart/form-data upload
When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"groupAccession\": \"GSF1234567\" }
Example¶
library(odmApi)
# Import a group of sample metadata objects from a TSV file via multipart/form-data upload
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
var_template_id <- "template_id_example" # character | (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportSamplesMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_iddata_file = "result.txt")
result <- api_instance$StartImportSamplesMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
| template_id | character | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |
StartImportVariantMultipart¶
Info StartImportVariantMultipart(file, source_attachment_accession = var.source_attachment_accession, transformation_name = var.transformation_name, transformation_version = var.transformation_version, study_id = var.study_id, template_id = var.template_id, previous_version = var.previous_version, metadata_file = var.metadata_file)
Import a VCF file containing variant data, optionally with a separate TSV metadata file via multipart/form-data
When job finishes successfully the following result object can be obtained using GET /job/{id}/output request: { \"groupAccession\": \"GSF1234567\" }
Example¶
library(odmApi)
# Import a VCF file containing variant data, optionally with a separate TSV metadata file via multipart/form-data
#
# prepare function argument(s)
var_file <- File.new('/path/to/file') # data.frame |
var_source_attachment_accession <- "source_attachment_accession_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_name <- "transformation_name_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_transformation_version <- "transformation_version_example" # character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. (Optional)
var_study_id <- "study_id_example" # character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. (Optional)
var_template_id <- "template_id_example" # character | (Optional)
var_previous_version <- "previous_version_example" # character | (Optional)
var_metadata_file <- File.new('/path/to/file') # data.frame | (Optional)
api_instance <- DataImportViaDirectFileUploadApi$new()
# Configure API key authorization: Access-token
api_instance$api_client$api_keys["Authorization"] <- Sys.getenv("API_KEY")
# Configure API key authorization: Genestack-API-Token
# api_instance$api_client$api_keys["Genestack-API-Token"] <- Sys.getenv("API_KEY")
# to save the result into a file, simply add the optional `data_file` parameter, e.g.
# result <- api_instance$StartImportVariantMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id, previous_version = var_previous_version, metadata_file = var_metadata_filedata_file = "result.txt")
result <- api_instance$StartImportVariantMultipart(var_file, source_attachment_accession = var_source_attachment_accession, transformation_name = var_transformation_name, transformation_version = var_transformation_version, study_id = var_study_id, template_id = var_template_id, previous_version = var_previous_version, metadata_file = var_metadata_file)
dput(result)
Parameters¶
| Name | Type | Description | Notes |
|---|---|---|---|
| file | data.frame | ||
| source_attachment_accession | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_name | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| transformation_version | character | The property is automatically populated by the attachment transformation pipeline and must not be provided during regular multipart uploads. | [optional] |
| study_id | character | The ID (accession) of the study for organising files in the internal storage; linking to the target entity must be done through a separate endpoint. | [optional] |
| template_id | character | [optional] | |
| previous_version | character | [optional] | |
| metadata_file | data.frame | [optional] |
Return type¶
Authorization¶
Access-token, Genestack-API-Token
HTTP request headers¶
- Content-Type: multipart/form-data
- Accept: application/json
HTTP response details¶
| Status code | Description | Response headers |
|---|---|---|
| 200 | successful operation | - |