Clustering data with heatmap algorithm for (Study ST001829)

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:

F1Treatments:PC15;0/18;1-d7 | Treatment times:no treatment | Air conditions:-
F2Treatments:PC16;0/18;2, AAPH+hemin | Treatment times:4h | Air conditions:18O2 air
F3Treatments:PC16;0/18;2, AAPH+hemin | Treatment times:4h | Air conditions:normal air
F4Treatments:PC16;0/18;2, AAPH | Treatment times:4h | Air conditions:normal air
F5Treatments:PC16;0/18;2, Autoxidation | Treatment times:24h | Air conditions:normal air
F6Treatments:PC16;0/18;2, control | Treatment times:no treatment | Air conditions:-
F7Treatments:PC16;0/18;2, CuSO4+AsA | Treatment times:72h | Air conditions:normal air
F8Treatments:PC16;0/20;4, AAPH+hemin | Treatment times:4h | Air conditions:normal air
F9Treatments:PC16;0/20;4, control | Treatment times:no treatment | Air conditions:-
F10Treatments:PC16;0/22;6, AAPH+hemin | Treatment times:4h | Air conditions:normal air
F11Treatments:PC16;0/22;6, control | Treatment times:no treatment | Air conditions:-
F12Treatments:Standard oxPCs | Treatment times:no treatment | Air conditions:-
F13Treatments:Standard PCs | Treatment times:no treatment | Air conditions:-
Data matrix
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