This is a web application that renders QTL "type" data. There are multiple components and moving parts, but 2 different main projects make up the QTL Viewer: QTL API and QTL Web.
Docker and Docker Compose are the recommended way of running the QTL API so it can be easily managed. A Docker image for the QTL API can be found on Docker Hub at mattjvincent/rqtlapi.
This image contains all the necessary code to run the QTL API. An example docker-compose.yml can be found in the churchill-lab/qtlapi GitHub repository.
An example to start this Docker image is:
docker run --rm -p 8000:8000 --network netapi \
-v /path/to/my.RData:/app/qtlapi/data/data.RData \
-v /path/to/ccfoundersnps.sqlite:/app/qtlapi/data/ccfounders.sqlite \
-v /path/to/qtlapi.R:/app/qtlapi/qtlapi.R \
mattjvincent/qtlapi /app/qtlapi/qtlapi.R
For more in depth documentation, please refer to churchill-lab/qtlapi.
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Behind the QTL API is a RData file which MUST be formatted according to the following definition: QTL API Data File Definition
The API generated is used by the QTL Web app. The following API's are supplied:
Description: This is the initial API called by QTL Web. The data returned is dependent upon if the dataType is mRNA, protein, or phenotype. The purpose of this API is to define and describe the datasets used in the viewer.
Parameters: None
Response: The response will be JSON.
Example response:
{"dataSets": [{
"id": "some.dataset.identifier",
"displayName": "Some Dataset",
"dataType": "mRNA",
"gene_ids": [
"ENSMUSG00000000001",
"ENSMUSG00000000028",
"ENSMUSG00010203821",
...
],
"protein_ids": [],
"phenotypes" : [],
"covarFactors":[{
"column.name":"sex",
"display.name":"Sex"
}, {
"column.name":"gen",
"display.name":"Generation"}]
},
...
],
"ensemblVersion": 75,
"numMarkers": 68433
}
Description: Perform a LOD Scan.
Parameters:
| Parameter | Description |
|---|---|
| dataset | dataset identifier |
| id | the identifer to perform LOD scan on |
| regressLocal | TRUE to regress on local genotype, FALSE to not |
| nCores | number of cores to use |
| expand | TRUE to expand the JSON, FALSE to condense |
Response: The response will be JSON.
Example Response:
{"result": [
{"id":"1_4530778","chr":"1","pos":4.5308,"lod":1.688},
{"id":"1_4533435","chr":"1","pos":4.5334,"lod":1.6709},
...
{"id":"1_4536092","chr":"1","pos":4.5361,"lod":1.6539}
],
"time":5.3
}
Description: Get founder coefficients.
Parameters:
| Parameter | Description |
|---|---|
| dataset | dataset identifier |
| id | the identifer to perform LOD scan on |
| chrom | the chromosome |
| regressLocal | TRUE to regress on local genotype, FALSE to not |
| blup | TRUE to perform Best Linear Unbiased Predictors |
| center | TRUE to center around 0 |
| nCores | number of cores to use |
| expand | TRUE to expand the JSON, FALSE to condense |
Response: The response will be JSON.
Example Response:
{"result":[{"id":"2_4292516","chr":"2","pos":4.2925,
"A":0.012,"B":-0.0267,"C":0.0345,"D":0.1994,
"E":0.1305,"F":-0.4769,"G":0.1217,"H":0.0055},
{"id":"2_4337139","chr":"2","pos":4.3371,
"A":0.0114,"B":-0.0267,"C":0.0343,"D":0.2,
"E":0.1307,"F":-0.4769,"G":0.1218,"H":0.0055},
...
{"id":"2_4369263","chr":"2","pos":4.3693,
"A":0.012,"B":-0.0259,"C":0.0407,"D":0.2006,
"E":0.1323,"F":-0.4783,"G":0.1134,"H":0.0052}
],
"time":2.3
}
Description: Get the expression data.
Parameters:
| Parameter | Description |
|---|---|
| dataset | dataset identifier |
| id | the identifer to perform LOD scan on |
Response: The response will be JSON.
Example Response:
{"data":[{"mouse_id":"F01","Sex":"F","Generation":"G4","Litter":2,
"Diet":"hf","Coat.Color":"agouti","GenerationLitter":"G4_2",
"expression":0.2243,"_row":"F01"},
...
{"mouse_id":"F02","Sex":"F","Generation":"G4","Litter":2,
"Diet":"hf","Coat.Color":"black","GenerationLitter":"G4_2",
"expression":0.3498,"_row":"F02"}
],
"time":2.3
}
Description: Perform mediation analysis.
Parameters:
| Parameter | Description |
|---|---|
| dataset | dataset identifier |
| id | the identifer to perform LOD scan on |
| mid | marker identifier |
| expand | TRUE to expand the JSON, FALSE to condense |
Response: The response will be JSON.
Example Response:
{"result":[{"gene_id":"ENSMUSG00000000001","symbol":"Gnai3",
"chr":"3","pos":108.1267,"LOD":1.3625},
{"gene_id":"ENSMUSG00000000028","symbol":"Cdc45",
"chr":"16","pos":18.7962,"LOD":1.605},
...
{"gene_id":"ENSMUSG00000000037","symbol":"Scml2",
"chr":"X","pos":161.1877,"LOD":1.2535}
],
"time":10.3
}
Description: SNP Association Mappting
Parameters:
| Parameter | Description |
|---|---|
| dataset | dataset identifier |
| id | the identifer to perform LOD scan on |
| chrom | the chromosome |
| location | chromosomal location |
| windowSize | the window size, distance on each size of location |
| nCores | number of cores to use |
| expand | TRUE to expand the JSON, FALSE to condense |
Response: The response will be JSON.
Example Response:
{"result":[{"snp":"rs245710663","chr":"1","pos":14.5001,
"alleles":"G|C","sdp":64,"ensembl_gene":"",
"csq":"intergenic_variant","index":1,"interval":147,
"on_map":false,"lod":0.0015},
{"snp":"rs263649601","chr":"1","pos":14.5002,
"alleles":"C|T","sdp":64,"ensembl_gene":"",
"csq":"intergenic_variant","index":1,"interval":147,
"on_map":false,"lod":0.0015},
...
{"snp":"rs32279922","chr":"1","pos":14.5004,
"alleles":"C|T","sdp":153,"ensembl_gene":"",
"csq":"intergenic_variant","index":3,"interval":147,
"on_map":false,"lod":3.5395e-06}
],
"time":11.1
}
Description: Peak LOD scors for a dataset.
Parameters:
| Parameter | Description |
|---|---|
| dataset | dataset identifier |
| expand | TRUE to expand the JSON, FALSE to condense |
Response: The response will be JSON.
Example Response:
{"result":[
{"marker":"1_100007442","chr":"1","pos":100.0074,
"gene_id":"ENSMUSG00000028028","symbol":"Alpk1",
"gene_chrom":"3","middle":127.7255,"lod":6.1147
},
{"marker":"1_100078094","chr":"1","pos":100.0781,
"gene_id":"ENSMUSG00000024727","symbol":"Trpm6",
"gene_chrom":"19","middle":18.8212,"lod":6.048
},
...
{"marker":"1_100148722","chr":"1","pos":100.1487,
"gene_id":"ENSMUSG00000045725","symbol":"Prr15",
"gene_chrom":"6","middle":54.3286,"lod":6.5079
}],
"time":3.9
}
Docker and Docker Compose are the recommended way of running the QTL Web so it can be easily managed. A Docker image for the QTL API can be found on Docker Hub at mattjvincent/rqtlweb.
This image contains all the necessary code to run the QTL Web. An example docker-compose.yml can be found in the churchill-lab/qtlapi GitHub repository.
An example to start this Docker image is:
docker-compose up --scale api=3
For more in depth documentation, please refer to churchill-lab/qtlweb.
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