rm-plugin-part1

This video demonstrates the the construction of the taverna part of our classification workflow

The finished workflows collects a GEO dataset, uploads it RA, reformats the data, splits the dataset in half, trains a classifier on one half, tests the classifier model on the other half, then reports the classifier performance in the users web-browser

1. make a workflow input with a default value and description

2. make a string constant that is used to build a url

3. add a REST service to download a summary of a GEO dataset from NCBI (shows how the rest service combine input values into a url)

4. add an xpath service to extract assay ids from the xml output (demonstrates how it allows you to debug the xpath and preview extracted output using example xml)

5. add an xpath service to extract assay labels (e.g. control, mutant)

6. add a rest service to get the raw assay data for each id

7. add an xpath service to extract the raw data

8. add a flatten list service to put the data into a single list

9. add a beanshell to combine these data into a CSV formatted table

10.  use a rest service to HTTP PUT the csv data into the RapidAnalytics repository, shows more advanced config e.g. "accept:" and "content-type:" http headers