Title: Exploring a Bayesian sparse factor model-based strategy for the genetic analysis of thousands of MIR-spectra traits for animal breeding
Table S1. number of records of milk mid-infrared (MIR) spectra, fat percentage (Fat), methane (CH4), and somatic cell score (SCS) within the first parity (number of total animals is 3,302)
Figure S1. Example trace plot of the first 10 principal components on the saved MCMC samples for the G matrix of analysis in the Average fat percentage (AFP) and milk MIR spectra dataset. The chain includes 100,000 iterations, and the first 10,000 are burn-in.
Figure S2. Example trace plot of the first 10 principal components on the saved MCMC samples for the G matrix of analysis in the Average CH4 (ACH4) and milk MIR spectra dataset. The chain includes 100,000 iterations, and the first 10,000 are burn-in.
Figure S3. Example trace plot of the first 10 principal components on the saved MCMC samples for the G matrix of analysis in the Average SCS (ASCS) and milk MIR spectra dataset. The chain includes 100,000 iterations, and the first 10,000 are burn-in.