Clustering data with heatmap algorithm for White Wine Study (Study ST000006)

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	White wine type and source:Chardonnay, Carneros, CA 2003 (CH01)
F2	White wine type and source:Chardonnay, Carneros, CA 2003 (CH02)
F3	White wine type and source:Chardonnay, Carneros, CA 2004
F4	White wine type and source:Chardonnay, Monterey, CA 2003
F5	White wine type and source:Chardonnay, Napa, CA 2003
F6	White wine type and source:Chardonnay, SE Australia, 2004
F7	White wine type and source:Elevage Blanc, Napa, CA 2004
F8	White wine type and source:Fume Blanc, Napa, CA 2004
F9	White wine type and source:Pinot gris, Napa, CA 2004
F10	White wine type and source:Pinot gris, Oregon 2003
F11	White wine type and source:Riesling, CA 2004
F12	White wine type and source:Riesling, Finger Lakes, NY 2004
F13	White wine type and source:Sauvignon Blanc, Lake County, CA 2001
F14	White wine type and source:Sauvignon Blanc, Napa, CA 2004 (SB03)
F15	White wine type and source:Sauvignon Blanc, Napa, CA 2004 (SB04)
F16	White wine type and source:Viognier, Dunnigan Hills, CA 2004
F17	White wine type and source:Viognier, Napa, CA 2004

Data matrix