Clustering data with heatmap algorithm for (Study ST003036)

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	treatment:BR_Blank_broth_B0
F2	treatment:BR_Blank_broth_B1
F3	treatment:BR_Blank_broth_B2
F4	treatment:BR_Blank_broth_B3
F5	treatment:BR_Blank_broth_B4
F6	treatment:Extraction blank
F7	treatment:M_Cefto_3g_143h
F8	treatment:M_Cefto_3g_167h
F9	treatment:M_Cefto_3g_23h
F10	treatment:M_Cefto_3g_47h
F11	treatment:M_Cefto_3g_71h
F12	treatment:M_Cefto_3g_7h
F13	treatment:M_Cefto_3g_95h
F14	treatment:M_Cefto_6g_143h
F15	treatment:M_Cefto_6g_167h
F16	treatment:M_Cefto_6g_23h
F17	treatment:M_Cefto_6g_47h
F18	treatment:M_Cefto_6g_71h
F19	treatment:M_Cefto_6g_7h
F20	treatment:M_Cefto_6g_95h
F21	treatment:M_Control_143h
F22	treatment:M_Control_167h
F23	treatment:M_Control_23h
F24	treatment:M_Control_47h
F25	treatment:M_Control_71h
F26	treatment:M_Control_7h
F27	treatment:M_Control_95h
F28	treatment:Pooled QC

Data matrix