CVD workshop night 2

David Dorr and Ted Laderas

Genetics and CVD: in data/slides

An example of using the machine learning package caret is available as caretOnIrisData.Rmd.

Your worksheet for tonight is available as cohortMLAssignment.Rmd.

Data has been partitioned into multiple sets and is available in the data folder.

Outline for Night 2

Task 4. An Introduction to molecular biomarkers (20 min)

Learning Objective: Discuss the potential impact of molecular biomarkers on a larger cohort. Format: Short Lecture (15 min) + Questions (5 min)

Task 5. Machine Learning/Modeling Tutorial (60 min)

Learning Objective: Use multiple machine methods (through the caret package) to explore subgroups and their CVD risk in the data. How well do we predict? What variables are useful in predicting CVD? How can we quantify this as a risk score? Format: Short Lecture (10 minutes) + Interactive Workshop (50 minutes). Output: Error + Risk Score

Task 6. Discussion (60 min)

Learning objective: Students give a 1 minute presentation to attempt to answer the questions: Did we do any better? Is genetic testing worth it?

Licensing and Attribution

This workshop was produced with support from NIH's Big Data to Knowledge (BD2K) Initiative at OHSU.

Workshop Materials are Licensed under a Creative Commons 4.0 Non Commercial License

Code is licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and limitations under the License.