%0 Journal Article
%T PECAplus: statistical analysis of time-dependent regulatory changes in dynamic single-omics and dual-omics experiments
%A Christine Vogel
%A Guoshou Teo
%A Hyungwon Choi
%A Yun Bin Zhang
%J Archive of "NPJ Systems Biology and Applications".
%D 2018
%R 10.1038/s41540-017-0040-1
%X a Schematic diagram of PECAplus modules. The pre-processing module performs data smoothing and missing data imputation. The processed data goes through a mass action modeling module of user¡¯s choice, and post-processing GSA module is applied to summarize time-dependent regulation patterns for biological functions. b PECA core analysis input and output in SLC39A14 gene. The four panels show the RNA and protein expression data, with solid dots and clear circles representing observed and GP-smoothed data points, respectively. Red circle and blue solid circle are imputed protein expression value at 16£¿h by GP and k-nearest neighbor imputation method. Fitted trajectory is the consensus time course profile across the two replicates reported from the PECA model. c The panels on the right side show the inferred rate ratios and CPS values for RNA-level and protein-level regulation. Red dashed lines are the CPS thresholds at 5% FDR (0.83 for RNA, 0.88 for protein
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5736550/