In total 30 immunological expression values were measured per individual. Initial examination of the data indicated a small number of individuals in which most or all of the readings were extremely high. In order to characterize this group each variable was log transformed (log10 [x+1]) and standardized ([x2mean]/ standard deviation) and then outlying observations in each variable were determined as those occurring .1.56 the interquartile range above the third data quartile. Individual mice with $10 such outlying values were classified as part of an ''extreme expression'' group. Examining the subset of 22 variables in which there were few missing values and considering animals with a full set of observations for these, we also used hierarchical cluster analysis (HCA) (average link) and ordinations against the principal axes derived from principal co-ordinates analysis (PCO) and principal components analysis (PCA) to assess the distribution of individuals in phenotypic space. Data were log-transformed and standardized prior to HCA and PCO and log-transformed prior to PCA on the correlation matrix.