CAGE

Classification After Gene Expression

Aim

• find gene expression features for use in patient classification.

• investigate the pros and cons of features based on principal components

Data Source

The gene expression data come from,

Xu K, Shi X, Husted C, Hong R et al.
Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways.
Sci Rep 2022 Oct 28;12(1):18168.

GEO archive as GSE210271. Series Matrix File downloaded from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE210271.

Study Design

• mRNA gene expression from 505 nasal epithelial brushings
  
  
• Profiled using Affymetrix Gene 1.0 ST microarrays .. 21685 probes
  
  
• 505 patients came from two Airway Epithelial Gene Expression in the Diagnosis of Lung Cancer (AEGIS) trials
  
  
• AEGIS-1: 243 with lung cancer, 132 with benign lung disease
  
• AEGIS-2: 66 with lung cancer, 64 with benign lung disease

Project Plan

• Use AEGIS-1 for training and AEGIS-2 for validation
  
  
• Develop the analysis on a sub-sample of 1000 probes
  
  
• Predict Cancer/Benign using Logistic Regression (LR)
  
  
• Compare 5 feature selection methods
  • Rank Probes .. Select the M best probes for LR
  • PCA of Covariances .. Select first M PCs for LR
  • Rank PCs .. Select the M best PCs for LR
  • PCA of Correlations .. Select first M PCs for LR
  • Rank PCs .. Select the M best PCs for LR
    
    
• Once the code is working, use same workflow on all 21,685 probes

Loss Function

Compare models using the Cross-Entropy Loss

−1NN∑i=1yilog(ˆyi)+(1−yi)log(1−ˆyi)

N is the number of subjects,
yi is 0 for benign cases and 1 for cancer cases
ˆyi is the predicted probability of the case being cancer under whatever model is being used

• Measures the average prediction error
• Equivalent to -log-Likelihood of the binomial distribution used in logistic regression

Documentation

• Commented Scripts, Diary, Dashboard, Reports on all intermediate stages
  
  
• Slide presentation on the final analysis
  
  
• Draft journal article (PLoS)
  
  
• Website describing the project