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This particular pipeline requires a bowtie index and an annotation model:
The request to launch the pipeline needs to specify one resource ID for each input.
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wget -q -O - "http://localhost:8080/flow/api/v1/library_files/list${AUTHDETAILS}&assembly=hg19" | python -m json.tool | gvim - |
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[
{
"annotationModel": "",
"assembly": "hg19",
"description": "Reference sequence",
"fileType": "Genome sequence",
"id": 100
},
{
"annotationModel": "",
"assembly": "hg19",
"description": "Cytoband",
"fileType": "cytoBand.txt",
"id": 101
},
{
"annotationModel": "",
"assembly": "hg19",
"description": "Bowtie index",
"fileType": "Bowtie Index",
"id": 102
},
{
"annotationModel": "hg19_refseq_15_05_07_v2",
"assembly": "hg19",
"description": "Annotation file: hg19_refseq_15_05_07_v2",
"fileType": "Annotation model",
"id": 103
}
] |
The pipeline can be launched in any project using RunPython.py
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python RunPipeline.py -v --server http://localhost:8080 --user admin --password $FLOW_TOKEN --project_id 0 --pipeline AlignAndQuantify --inputs 102,103,102 |
This action will cause two tasks to start running:
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python UploadSamples.py -v --server http://localhost:8080 --user admin --password $FLOW_TOKEN --files ~/sampleA.fastq.gz ~/sampleB.fastq.gz --project NewProject --pipeline AlignAndQuantify --inputs 102,103,102 |
Add a collaborator to a project
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Monitor a folder and upload files as they are created
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#!/bin/bash inotifywait -m $PATH_TO_MONITOR -e create -e moved_to | while read path action file; do if [[ $file == *.fastq.gz ]]; then echo "Uploading $file" python UploadSamples.py -v --server $SERVER --user $USER --password $TOKEN --files $path/$file --project "$PROJECT" fi done |
Monitor the queue and send a notification if there are too many waiting tasks
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#!/bin/bash while true; do result=`python QueueStatistics.py --server $SERVER --user $USER --password $TOKEN --max_waiting $MAX_WAITING` if [ $? -eq 1 ]; then /usr/bin/notify-send $result exit 1 fi sleep $INTERVAL done |
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