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The new project will appear on the Flow homepage:

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Upload a group of samples

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This operation will generate a data node on the Analyses tab for the imported samples:

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Assign sample attributes

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 The sample attributes can be viewed and managed on the data tab:

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Run a pipeline

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wget -q -O - http://localhost:8080/flow/api/v1/pipelines/list$AUTHDETAILS | python -m json.tool | gvim -

Get Many pipelines also require that library files are specified.  

You can get the list of required inputs for the pipeline from the API:

http://localhost:8080/flow/api/v1/pipelines/inputs?project_id=iDEA0&pipeline=AlignAndQuantify

This particular pipeline requires a bowtie index and an annotation model:

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The request to launch the pipeline needs to specify one resource ID for each input.

These IDs can be found using the API:

Get the IDs for the library files that match the required inputs

wget -q -O - "http://localhost:8080/flow/api/v1/library_files/

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list${AUTHDETAILS}&assembly=hg19" |  python -m json.tool | gvim -

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The pipeline can be launched in any project using RunPython.py

python RunPipeline.py  -v --server http://localhost:8080 --user admin --password $FLOW_TOKEN --project_id 0 --pipeline AlignAndQuantify --inputs 103,102 

This action will cause two tasks to start running:

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Alternatively, UploadSamples.py can create the project, upload the samples and launch the pipeline in one step:

python UploadSamples.py -v --server http://localhost:8080 --user admin --password $FLOW_TOKEN --files ~/sample1sampleA.fastq.gz ~/sample2sampleB.fastq.gz --project NewProject --pipeline AlignAndQuantify --inputs 28061103,145855102

Add a collaborator to a project

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