machine learning using the TCGA data (introduction to data science course
Budget: $30 – $100 USD
Question: Use machine learning algorithms to predict a clinical condition related to cancer from omics data
Instructions:
Use R Markdown and upload the final scripts and outputs in HTML format. Also upload a working R script. (20 points)
1. Explore the TCGA data and identify a problem that you would like to solve using machine learning.
2. Select the appropriate clinical condition (e.g: Tumor vs normal, Primary tumor vs Metastatic etc) and omics datasets (e.g: gene expression, methylation etc).
3. Load the data in R, use appropriate preprocessing, generate test and train datasets, train at least 5 different machine learning models, and evaluate and compare the performance.
Instructions:
Use R Markdown and upload the final scripts and outputs in HTML format. Also upload a working R script. (20 points)
1. Explore the TCGA data and identify a problem that you would like to solve using machine learning.
2. Select the appropriate clinical condition (e.g: Tumor vs normal, Primary tumor vs Metastatic etc) and omics datasets (e.g: gene expression, methylation etc).
3. Load the data in R, use appropriate preprocessing, generate test and train datasets, train at least 5 different machine learning models, and evaluate and compare the performance.