Contentupload Resource
==========================================================================
Resource URL: ``http://mytorrentserver/rundb/api/v1/contentupload/``
Schema URL: ``http://mytorrentserver/rundb/api/v1/contentupload/schema/``
.. include:: ../manual_api_ref_docs/contentupload.rst
Fields table
------------
================ ====================================== ======= ======== ======== ===== ====== =======
field help text default nullable readonly blank unique type
================ ====================================== ======= ======== ======== ===== ====== =======
**status** Unicode string data. Ex: "Hello World" false false true false string
---------------- -------------------------------------- ------- -------- -------- ----- ------ -------
**meta** Unicode string data. Ex: "Hello World" {} false false true false string
---------------- -------------------------------------- ------- -------- -------- ----- ------ -------
**file_path** Unicode string data. Ex: "Hello World" n/a false false false false string
---------------- -------------------------------------- ------- -------- -------- ----- ------ -------
**resource_uri** Unicode string data. Ex: "Hello World" n/a false true false false string
---------------- -------------------------------------- ------- -------- -------- ----- ------ -------
**id** Integer data. Ex: 2673 false false true true integer
================ ====================================== ======= ======== ======== ===== ====== =======
Example request
---------------
Request URL: ``http://mytorrentserver/rundb/api/v1/contentupload/?format=json&limit=1``
Python example
^^^^^^^^^^^^^^
.. code-block:: python
import requests
ts_api_request = requests.get("http://mytorrentserver/rundb/api/v1/contentupload/", params={"format": "json", "limit": 1})
ts_api_response = ts_api_request.json()
contentuploads = ts_api_response["objects"]
for contentupload in contentuploads:
print contentupload
Torrent Server response
^^^^^^^^^^^^^^^^^^^^^^^
.. code-block:: javascript
{
"meta": {
"previous": null,
"total_count": 25,
"offset": 0,
"limit": 1,
"next": "/rundb/api/v1/contentupload/?offset=1&limit=1&format=json"
},
"objects": [
{
"status": "Successfully Completed",
"meta": {
"upload_date": "2014-03-27T00:28:46",
"description": "Comp Cancer Panel",
"reference": "hg19",
"is_ampliseq": true,
"hotspot": true,
"choice": "proton",
"design": {
"status": "ORDERABLE",
"pipeline": "DNA",
"min_number_amplicons_per_pool": 3991,
"type": "FIXED_PANEL",
"description": "The Ion AmpliSeq™ Comprehensive Cancer Panel provides highly multiplexed target selection of genes implicated in cancer research. Encompassing over 50% of the Wellcome Trust Sanger Institute Cancer Gene Census, this is the most comprehensive cancer gene panel available. With all-exon coverage of 409 genes, the Ion AmpliSeq™ Comprehensive Cancer Panel delivers fast, FFPE-compatible, target selection for a broad survey of key genes for semiconductor sequencing. \r\nLearn more![](\"/resources/images/linkout.png\")
\r\n\r\n\r\n \r\n | COSMIC mutation targets\r\n 15,749 | \r\n Amplicon length\r\n 125–175 bp (average 155 bp) | \r\n Primer pool size\r\n ~16,000 primers in 4 tubes | \r\n Input DNA required\r\n 10 ng per pool, 40 ng per DNA sample | \r\n Read length\r\n 1 x 200 | \r\n
\r\n
",
"order_number": 90,
"design_name": "Comp Cancer Panel",
"results_uri": "/ws/tmpldesign/14011153/download/results",
"pipeline_version": null,
"request_id_and_solution_ordering_id": "CCP",
"configuration_choices": [
"pgm",
"proton"
],
"target_size": 1293547,
"genome": "HG19",
"solution_name": null,
"created_date": "2013-10-07T14:21:51.388+0000",
"plan": {
"missed_bed": null,
"hotspot_bed": "CCP.20131001.hotspots.bed",
"coverage_summary": null,
"designed_bed": "CCP.20131001.designed.bed",
"target_mutations": null,
"primer_bed": null,
"selectedPlugins": {
"variantCaller": {
"features": [],
"ampliSeqVariantCallerConfig": {
"torrent_variant_caller": {
"snp_min_allele_freq": "0.02",
"snp_strand_bias": "0.95",
"hotspot_min_coverage": "6",
"hotspot_min_cov_each_strand": "2",
"hotspot_min_allele_freq": "0.01",
"snp_min_variant_score": "6",
"hotspot_strand_bias": "0.95",
"hp_max_length": "8",
"filter_insertion_predictions": "0.2",
"indel_min_variant_score": "6",
"indel_min_coverage": "15",
"heavy_tailed": "3",
"outlier_probability": "0.005",
"data_quality_stringency": "6.5",
"snp_min_cov_each_strand": "0",
"hotspot_min_variant_score": "6",
"indel_strand_bias": "0.9",
"downsample_to_coverage": "2000",
"filter_unusual_predictions": "0.3",
"indel_min_allele_freq": "0.05",
"do_snp_realignment": "1",
"prediction_precision": "1.0",
"indel_min_cov_each_strand": "2",
"filter_deletion_predictions": "0.2",
"suppress_recalibration": "0",
"snp_min_coverage": "6"
},
"meta": {
"repository_id": "",
"ts_version": "4.0",
"name": "Panel-optimized - Comp Cancer Panel",
"user_selections": {
"chip": "proton_p1",
"frequency": "germline",
"library": "ampliseq",
"panel": "/rundb/api/v1/contentupload/48/"
},
"trimreads": true,
"tooltip": "Panel-optimized parameters from AmpliSeq.com",
"tvcargs": "tvc",
"built_in": true,
"configuration": "",
"compatibility": {
"panel": "/rundb/api/v1/contentupload/48/"
}
},
"long_indel_assembler": {
"min_indel_size": "4",
"short_suffix_match": "5",
"output_mnv": "0",
"min_var_count": "5",
"min_var_freq": "0.15",
"kmer_len": "19",
"max_hp_length": "8",
"relative_strand_bias": "0.8"
},
"freebayes": {
"gen_min_coverage": "6",
"allow_mnps": "1",
"allow_complex": "0",
"read_max_mismatch_fraction": "1.0",
"read_mismatch_limit": "10",
"allow_indels": "1",
"min_mapping_qv": "4",
"gen_min_alt_allele_freq": "0.035",
"allow_snps": "1",
"gen_min_indel_alt_allele_freq": "0.1"
}
},
"userInput": {
"torrent_variant_caller": {
"snp_min_allele_freq": "0.02",
"snp_strand_bias": "0.95",
"hotspot_min_coverage": "6",
"hotspot_min_cov_each_strand": "2",
"hotspot_min_allele_freq": "0.01",
"snp_min_variant_score": "6",
"hotspot_strand_bias": "0.95",
"hp_max_length": "8",
"filter_insertion_predictions": "0.2",
"indel_min_variant_score": "6",
"indel_min_coverage": "15",
"heavy_tailed": "3",
"outlier_probability": "0.005",
"data_quality_stringency": "6.5",
"snp_min_cov_each_strand": "0",
"hotspot_min_variant_score": "6",
"indel_strand_bias": "0.9",
"downsample_to_coverage": "2000",
"filter_unusual_predictions": "0.3",
"indel_min_allele_freq": "0.05",
"do_snp_realignment": "1",
"prediction_precision": "1.0",
"indel_min_cov_each_strand": "2",
"filter_deletion_predictions": "0.2",
"suppress_recalibration": "0",
"snp_min_coverage": "6"
},
"meta": {
"repository_id": "",
"ts_version": "4.0",
"name": "Panel-optimized - Comp Cancer Panel",
"user_selections": {
"chip": "proton_p1",
"frequency": "germline",
"library": "ampliseq",
"panel": "/rundb/api/v1/contentupload/48/"
},
"trimreads": true,
"tooltip": "Panel-optimized parameters from AmpliSeq.com",
"tvcargs": "tvc",
"built_in": true,
"configuration": "",
"compatibility": {
"panel": "/rundb/api/v1/contentupload/48/"
}
},
"long_indel_assembler": {
"min_indel_size": "4",
"short_suffix_match": "5",
"output_mnv": "0",
"min_var_count": "5",
"min_var_freq": "0.15",
"kmer_len": "19",
"max_hp_length": "8",
"relative_strand_bias": "0.8"
},
"freebayes": {
"gen_min_coverage": "6",
"allow_mnps": "1",
"allow_complex": "0",
"read_max_mismatch_fraction": "1.0",
"read_mismatch_limit": "10",
"allow_indels": "1",
"min_mapping_qv": "4",
"gen_min_alt_allele_freq": "0.035",
"allow_snps": "1",
"gen_min_indel_alt_allele_freq": "0.1"
}
},
"version": "4.1-r74477",
"id": 698,
"name": "variantCaller"
}
},
"coverage_detail": null,
"primer_sequences": "CCP.20131001.primerDataSheet.csv",
"runType": "AMPS",
"submitted_bed": null,
"well_plate_data": null
},
"design_id": "CCP",
"number_of_amplicons": 15992,
"id": 14011153,
"amplicons_coverage_summary": "95.349763093262169",
"number_of_amplicon_pools": 4
}
},
"file_path": "/results/uploads/BED/48/CCP.20131001.results.zip",
"resource_uri": "/rundb/api/v1/contentupload/48/",
"id": 48
}
]
}
Allowed HTTP methods
--------------------
- get
- post
- put
- delete
- patch