Table 4.

Peptide clusters that were used as predictors in both the logistic regression model and the random forest classifier model

Core motifMean peptide count in INH groupMean peptide count in INH+ groupFold changeFVIII domainNumber of unique peptides in cluster (%)Peptide count of cluster (%)
kxPxstw 133 1826 13.70 24 (0.09%) 55 764 (0.16%) 
hntMels 38 119 3.10 11 (0.04%) 20 460 (0.06%) 
hTnln 151 454 3.01 A3 48 (0.17%) 66 660 (0.19%) 
nqkms 140 365 2.60 A2 31 (0.11%) 66 660 (0.19%) 
dxxYxlxm 438 1114 2.54 34 (0.12%) 63 368 (0.18%) 
Yvntxxxt 193 475 2.46 11 (0.04%) 25 499 (0.07%) 
LtqM 159 302 1.90 31 (0.11%) 61 253 (0.17%) 
pQyxnxxk 454 738 1.63 51 (0.18%) 52 743 (0.15%) 
sxnKP 325 483 1.49 53 (0.19%) 52 537 (0.15%) 
WDVpPxxxxt 301 445 1.48 21 (0.08%) 33 105 (0.09%) 
KxxHyxk 459 459 1.00 15 (0.05%) 39 173 (0.11%) 
qTAkfh 41 40 0.96 41 (0.15%) 48 928 (0.14%) 
Core motifMean peptide count in INH groupMean peptide count in INH+ groupFold changeFVIII domainNumber of unique peptides in cluster (%)Peptide count of cluster (%)
kxPxstw 133 1826 13.70 24 (0.09%) 55 764 (0.16%) 
hntMels 38 119 3.10 11 (0.04%) 20 460 (0.06%) 
hTnln 151 454 3.01 A3 48 (0.17%) 66 660 (0.19%) 
nqkms 140 365 2.60 A2 31 (0.11%) 66 660 (0.19%) 
dxxYxlxm 438 1114 2.54 34 (0.12%) 63 368 (0.18%) 
Yvntxxxt 193 475 2.46 11 (0.04%) 25 499 (0.07%) 
LtqM 159 302 1.90 31 (0.11%) 61 253 (0.17%) 
pQyxnxxk 454 738 1.63 51 (0.18%) 52 743 (0.15%) 
sxnKP 325 483 1.49 53 (0.19%) 52 537 (0.15%) 
WDVpPxxxxt 301 445 1.48 21 (0.08%) 33 105 (0.09%) 
KxxHyxk 459 459 1.00 15 (0.05%) 39 173 (0.11%) 
qTAkfh 41 40 0.96 41 (0.15%) 48 928 (0.14%) 

Total number of unique peptides were 27 775. Total peptide count was 35 452 858. The “-” indicates lack of good alignment on linear sequence of FVIII.

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