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Mathematical correlation				Phenotype measurement	Gene expression probeset data instance
Pearson	Sex	No. of Strains	Scatter plot		Gene	Approximate chr location	Probeset	Data set
behavior – visuospatial learning
r = 0.913   p = 0.000087	m	11	Plot	Brown2   probe_corr_pct	Gab3	X:75026150	10024409319	liver_Su1
r = 0.903   p = 0.000138	m	11	Plot	Brown2   probe_corr_dur	Gab3	X:75026150	10024409319	liver_Su1
r = –0.864   p = 0.000599	f	11	Plot	Brown2   acq_lat_d1	Gab3	X:75026150	10024409319	liver_Su1
blood – hematology – cell counts – WBC – lymphocytes
r = 0.811   p = 0.000429	f	14	Plot	Peters4   pctLYMPH_M12	Gab3	X:75026150	10024409319	liver_Su1
body composition – fat
r = –0.748   p = 0.000868	f	16	Plot	Naggert1   pctfat_fat8	Gab3	X:75026150	10024409319	liver_Su1
cardiovascular – blood pressure
r = 0.784   p = 0.000900	m	14	Plot	Maurer1   BP_ctrl	Gab3	X:75026150	10024409319	liver_Su1

[6 instances listed above]

Correlations with r < 0.5 or p > 0.005 or nstrains < 10 are not retained. The large number of eligible probeset data instances increases the liklihood of strong mathematical correlations occurring by chance. For gene symbols, current MGI coordinates take precendence over GX annotation so additional flank may be helpful. [1] DPV = data point variance filter. Stricter settings will omit instances where data points have more variance. To see DPV hover your mouse pointer over the p value.