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Basic experimental design for comparing glycosylation with lectin arrays Wild-type C57BL/6 (Healthy control) Glycosyltransferase deficient (Disease model) cells, serum, plasma, or protein prep used in labeling rxn Labeled control and labeled unknown preps incubated on 2 different microarray slides NHS -Cy5 reactive dye Slides are clamped in frames that creates wells NHS dye reaction killed (Tris pH 8) 1 Control slide sample Incoming slide sample

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1 st slide, a control, 12 subgrids, triplicate read averaged, H/L calculated for each lectin High and low for each lectin become the boundaries for no change L6 L5 L1 L2 L3 L4 H1 H6 H5 H4 H3 H2 High Value Low value No change region 2

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A second slide, an unknown or incoming sample, 12 subgrids, triplicate read averaged, median calculated for each lectin Median calculated Less sensitive to outliers L6 L5 L1 L2 L3 L4 H1 H6 H5 H4 H3 H2 A AMA 3

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Comparison of unknown median read to control high and low boundary L6 H6 Control high value boundary Control low value boundary No change region Control Within boundaries, digitization = 0 Above boundary, digitization = 1 Below boundary, digitization = -1 4

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For each lectin in the unknown which has a 0 digitization value, a confidence factor is assigned based on its position relative to the control high low range Midpoint of H/L median value for the unknown is placed within a bin in the L/H control range the distance from the mid point of the control range sets the bin # (certainty level) A bin # of -1 or 1 is near the high or the low control boundaries has a small percentage confidence value has a negative or positive value depending on position relative to mid point L6 H6 Bin 10 Bin 8 Bin 1 Bin -10 Bin -5 Bin -0 confidence border +0 confidence border Ex#2: Median value of unknown (bin 8) +0.8 confidence Confidence=1 For digitization = 0 Confidence assignments for digitization =0 Ex#1: Median value of unknown (bin -1) -0.1 confidence 5

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For each lectin in the unknown which has a -1 or +1 digitization value a confidence factor is assigned based on its signal position relative to: either the control low boundary or control high boundary Point A would have a better confidence factor then B: i.e.- less relative signal Control range midpoint Low boundary High boundary B A digitization = -1 area digitization = 1 area Confidence assignments for digitization = -1 and +1 6

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Large decrease, in relation to large value low boundary, gives high confidence similarly Small decrease in relation to a small value low boundary gives a high confidence (HB-control High Boundary) Control H/L range (LB-control Low Boundary value) DS- Incoming Decreased Signal Relative Fluoresence Units Confidence factor= (DS-LB)/DS EX. 500 – 1000 /500 = -1 confidence factor (a 50% decrease in signal) Example calculation of the confidence level for a digitization = -1 1000 RFU 500 RFU Incoming value point (DS) 7

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