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Title: Exploring a Bayesian sparse factor model-based strategy for the genetic analysis of thousands of MIR-spectra traits for animal breeding

Here are included Supplemental File 1 and Supplemental File 2.

Supplemental File 1 included 1 Table

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)

Supplemental File 2 included 3 Figures.

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.

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