Additional file 2 of Correcting nucleotide-specific biases in high-throughput sequencing data [stub]

Jeremy Wang, Bryan Quach, Terrence Furey
2017 Figshare  
Table S1. Area under curve (AUC) values for the ROC curves representing sensitivity and specificity of footprint detection for several transcription factors. AUC values at increasing false positive rates (FPR) are computed independently for each motif before and after correction. For all factors except SP1, bias correction improved our ability to accurately predict footprints using protein interaction quantification (PIQ), especially at low to moderate FPR. SP1 motifs often appear in promoters
more » ... ppear in promoters and coincide with binding sites for other factors, which may explain itâ s high AUC and the increase in false positives caused by other detectable footprints after correction. (PDF 250 kb)
doi:10.6084/m9.figshare.c.3841099_d2.v1 fatcat:4i2ozmwa7zf5hcgolssxopesim