Clustering data with heatmap algorithm for (Study ST003203)

This analysis uses the 'heatmap.2' function of gplots package in the R statistics environment

The rows are scaled to have mean=0 and standard deviation=1

Factors:

F1	Sample source:Tear | Study Arm:1 | Timepoint:Week 10 | PZC (< 660 ug/L):N
F2	Sample source:Tear | Study Arm:1 | Timepoint:Week 10 | PZC (< 660 ug/L):Y
F3	Sample source:Tear | Study Arm:1 | Timepoint:Week 18 | PZC (< 660 ug/L):N
F4	Sample source:Tear | Study Arm:1 | Timepoint:Week 18 | PZC (< 660 ug/L):Y
F5	Sample source:Tear | Study Arm:1 | Timepoint:Week 2 | PZC (< 660 ug/L):N
F6	Sample source:Tear | Study Arm:1 | Timepoint:Week 2 | PZC (< 660 ug/L):Y
F7	Sample source:Tear | Study Arm:2 | Timepoint:Week 10 | PZC (< 660 ug/L):N
F8	Sample source:Tear | Study Arm:2 | Timepoint:Week 10 | PZC (< 660 ug/L):Y
F9	Sample source:Tear | Study Arm:2 | Timepoint:Week 18 | PZC (< 660 ug/L):N
F10	Sample source:Tear | Study Arm:2 | Timepoint:Week 18 | PZC (< 660 ug/L):Y
F11	Sample source:Tear | Study Arm:2 | Timepoint:Week 2 | PZC (< 660 ug/L):N
F12	Sample source:Tear | Study Arm:2 | Timepoint:Week 2 | PZC (< 660 ug/L):Y

Data matrix