Logistic Regression Models of the Distribution of TTN Truncation Variants

All statistical analysis was performed in R (3.1.1). The primary goal of this work was to understand how variants found in cases differ from those found in controls, according to the characteristics of the variant (where it is found in the protein, is it alternatively spliced, etc.). My starting point was a list of variants found in cases and a corresponding list found in controls. I annotated each variant according to its location in the protein (taking into account regions of the sarcomere and the position of the internal promoter), as well as the extent of alternative splicing for the exon in which it is found. The data of the 1143 truncation variants (247 from DCM cases and 896 from controls) were analyzed using logistic regression to identify the factors that characterize mutations found in cases and controls.

The same 1143 data points were used for every analysis described below. For transparency, I have also provided an R Markdown file that describes all analyses performed and plots generated here (File I in the Data Supplement).