This repository contains the preliminary data analysis for my qPCR study evaluating viral gene expression (H5N1, H7N2) across different vaccine groups and administration routes.
- Prelim-Data Analysis Semester Project.qmd – Quarto document containing R code, data visualization, and model selection explanation.
- Prelim-Data Analysis Semester Project.pdf – Rendered PDF version of the analysis.
- ENT_Project_Tracheal_qPCR_Clean.xlsx – Cleaned qPCR dataset used for analysis.
The preliminary analysis included exploratory visualization (histograms, QQ plots) and assessment of data normality.
Given the nested experimental design (Bird_ID within Timepoint within Virus), a Linear Mixed Model (LMM) was identified as the most suitable model for normally distributed outcomes (Ct, log10GE).
For future analyses, if residual skew persists, a Tweedie GLMM will be considered to handle positive, right-skewed data.
`
This repository contains the final data analysis for my qPCR study evaluating tracheal viral load in broiler chickens vaccinated with a bovine adenovirus–vectored avian influenza vaccine (BAds-AIV). Birds were challenged with H5N1 or H7N2 and sampled at three post-challenge timepoints (DPC2, DPC4, DPC6).
Final Semester Project-Data-Analysis-ENT6907.qmd
Quarto document containing all R code for data import, wrangling, visualization, model fitting, and diagnostics.
Rendered report with figures, model results, and interpretation.
Clean qPCR dataset with an added Metadata sheet describing variables and data structure.
The final analysis uses Gaussian linear mixed-effects models for two continuous outcomes:
- Ct (cycle threshold)
- log10GE (log10 genome equivalents)
Both models include Vaccine_Group, Virus, Route, and Timepoint as fixed effects and Bird_ID as a random intercept to account for repeated measures. Model diagnostics (residual plots, Q–Q plots) support the use of Gaussian mixed models. Results show strong virus-specific differences in viral load (H7N2 > H5N1) and partial vaccine effects, especially for H7N2, with little influence of administration route.