Clustering data with heatmap algorithm for (Study ST003256)

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	Genotype:shCtrl | Treatment:DMSO | Treatment Time:2 h
F2	Genotype:shCtrl | Treatment:RSL3 (10 µM) | Treatment Time:2 h
F3	Genotype:shCtrl | Treatment:RSL3 (1 µM) | Treatment Time:2 h
F4	Genotype:shZeb1 | Treatment:DMSO | Treatment Time:2 h
F5	Genotype:shZeb1 | Treatment:RSL3 (10 µM) | Treatment Time:2 h
F6	Genotype:shZeb1 | Treatment:RSL3 (1 µM) | Treatment Time:2 h
F7	Genotype:WT | Treatment:DMSO | Treatment Time:24 h
F8	Genotype:WT | Treatment:DMSO | Treatment Time:2 h
F9	Genotype:WT | Treatment:DMSO | Treatment Time:4 h
F10	Genotype:WT | Treatment:DMSO | Treatment Time:6 h
F11	Genotype:WT | Treatment:RSL3 (10 µM) | Treatment Time:24 h
F12	Genotype:WT | Treatment:RSL3 (10 µM) | Treatment Time:2 h
F13	Genotype:WT | Treatment:RSL3 (10 µM) | Treatment Time:4 h
F14	Genotype:WT | Treatment:RSL3 (10 µM) | Treatment Time:6 h
F15	Genotype:WT | Treatment:RSL3 (1 µM) | Treatment Time:24 h
F16	Genotype:WT | Treatment:RSL3 (1 µM) | Treatment Time:2 h
F17	Genotype:WT | Treatment:RSL3 (1 µM) | Treatment Time:4 h
F18	Genotype:WT | Treatment:RSL3 (1 µM) | Treatment Time:6 h

Data matrix