Clustering data with heatmap algorithm for (Study ST003604)

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	time (h):0 | Dead E coli treatment:no | inhibitor:none | | genotype:RagA GTP mutant
F2	time (h):0 | Dead E coli treatment:no | inhibitor:none | | genotype:WT
F3	time (h):18 | Dead E coli treatment:yes | inhibitor:150 nM concanamycin A | | genotype:WT
F4	time (h):18 | Dead E coli treatment:yes | inhibitor:50 nM bafilomycin A1 | | genotype:WT
F5	time (h):18 | Dead E coli treatment:yes | inhibitor:none | | genotype:RagA GTP mutant
F6	time (h):18 | Dead E coli treatment:yes | inhibitor:none | | genotype:WT
F7	time (h):6 | Dead E coli treatment:yes | inhibitor:150 nM concanamycin A | | genotype:WT
F8	time (h):6 | Dead E coli treatment:yes | inhibitor:50 nM bafilomycin A1 | | genotype:WT
F9	time (h):6 | Dead E coli treatment:yes | inhibitor:none | | genotype:RagA GTP mutant
F10	time (h):6 | Dead E coli treatment:yes | inhibitor:none | | genotype:WT

Data matrix