Analyse tryx results — tryx.analyse • tryx

This returns various heterogeneity statistics, IVW estimates for raw, adjusted and outlier removed datasets, and summary of peripheral traits detected etc.

tryx.analyse(
  tryxscan,
  plot = TRUE,
  id_remove = NULL,
  filter_duplicate_outliers = TRUE
)

Arguments

tryxscan	Output from `tryx.scan`
plot	Whether to plot or not. Default is TRUE
id_remove	List of IDs to exclude from the adjustment analysis. It is possible that in the outlier search a candidate trait will come up which is essentially just a surrogate for the outcome trait (e.g. if you are analysing coronary heart disease as the outcome then a variable related to heart disease medication might come up as a candidate trait). Adjusting for a trait which is essentially the same as the outcome will erroneously nullify the result, so visually inspect the candidate trait list and remove those that are inappropriate.
duplicate_outliers_method	Sometimes more than one trait will associate with a particular outlier. TRUE = only keep the trait that has the biggest influence on heterogeneity

Value

List of - adj_full: data frame of SNP adjustments for all candidate traits - adj: The results from adj_full selected to adjust the exposure-outcome model - Q: Heterogeneity stats - estimates: Adjusted and unadjested exposure-outcome effects - plot: Radial plot showing the comparison of different methods and the changes in SNP effects ater adjustment