Clustering data with heatmap algorithm for (Study ST003603)

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	Timepoint (h):18 | LPS treatment (ng/ml):0 | E coli viability:dead | Multiplicity of infection:25 | well vs insert source:NA
F2	Timepoint (h):18 | LPS treatment (ng/ml):0 | E coli viability:dead | Multiplicity of infection:50 | well vs insert source:well
F3	Timepoint (h):18 | LPS treatment (ng/ml):0 | E coli viability:live | Multiplicity of infection:25 | well vs insert source:NA
F4	Timepoint (h):18 | LPS treatment (ng/ml):0 | E coli viability:NA | Multiplicity of infection:NA | well vs insert source:insert
F5	Timepoint (h):18 | LPS treatment (ng/ml):0 | E coli viability:NA | Multiplicity of infection:NA | well vs insert source:NA
F6	Timepoint (h):18 | LPS treatment (ng/ml):0 | E coli viability:NA | Multiplicity of infection:NA | well vs insert source:well
F7	Timepoint (h):18 | LPS treatment (ng/ml):500 | E coli viability:NA | Multiplicity of infection:NA | well vs insert source:NA
F8	Timepoint (h):6 | LPS treatment (ng/ml):0 | E coli viability:dead | Multiplicity of infection:50 | well vs insert source:well
F9	Timepoint (h):6 | LPS treatment (ng/ml):0 | E coli viability:NA | Multiplicity of infection:NA | well vs insert source:insert

Data matrix