RPC Strategy

Published: 23 January 2024| Version 2 | DOI: 10.17632/zgftdrtrxx.2
Contributor:
Reyna Hernandez-Benitez

Description

Recurrent Pattern Classification (RPC) is an strategy to sort data in categories, which traces the relative mean abundances of compounds over time . RPC enabled us to visualize and identify recurrent patterns of chemicals abundance, even those exhibiting subtle increases in specific windows, allowing us to classify them into cumulative, reductive, u-shaped, or bell waves and exclude them from those that did not change over time. While the set is created for metabolomics data, other type of data like curated levels of gene expression by transcriptomics could be used with similar approach. IMPORTANT: The datasets available here as uploaded files, include three examples of metabolomic profiles classified using RPC belonging to MB (myoblasts undergoing differentiation), NSCs (neural stem cells undergoing differentiation), and MSCs (mesenchymal stem cells undergoing differentiation), all in vitro setups (files Dataset_S1.5_RPC-Strategy_MBs, Dataset_S1.6_RPC-Strategy_NSCs, and Dataset_S1.7_RPC-Strategy_MSCs) plus empty file "to apply the strategy" with user-custom data (Dataset S1.1_RPC-Strategy). Finally the files that explain the content and rules of this strategy (files Dataset_S1.4_Formulas.txt, Dataset_S1.3_Code.txt, and Dataset_S1.2_Instructions for RPC-Strategy.pdf).

Files

Steps to reproduce

RPC strategy: Classifies the compounds based on the dynamics of their concentrations along an intermediate interval of time, taking as reference the initial and terminal concentration values. Formulas below can be applied in any .exe file or equivalent. MaxValue =MAX(F2:L2) where F2=Initial, G2=t1, H2=t2, I2=t3, J2=t4, K2=t5, L2=Terminal OR =MAX(Initial, t1:t5, Terminal) SD =STDEV(F2:L2) Time_MaxValue =IFS($M2=F2, "Initial", $M2=G2, "t1", $M2=H2, "t2", $M2=I2, "t3", $M2=J2, "t4", $M2=K2, "t5", $M2=L2, "Terminal") No_change =IF(N2<0.09, "No_change") U-shape =IF(AND(F2>((AVERAGE(G2:L2)*1.1)), L2>((AVERAGE(F2:K2)*1.1))), "U-shape") Reductive =IF(AND(F2=M2, Q2<>$Q$1), "Reductive") Cumulative1 =IF(AND(L2=M2, Q2<>$Q$1), "Cumulative1") Cumulative2 =IF(AND(S2<>$S$1, Q2<>$Q$1, U2<>$U$1, V2<>$V$1, W2<>$W$1, X2<>$X$1, Y2<>$Y$1, (OR(F2<G2, F2<H2, F2<I2, F2<J2, F2<K2))), "Cumulative2") t5_Wave =IF(AND(K2=M2, L2<(K2*0.9), Q2<>$Q$1), "t5_Wave") t4_Wave =IF(AND(J2=M2, L2<(J2*0.9), Q2<>$Q$1), "t4_Wave") t3_Wave =IF(AND(I2=M2, L2<(I2*0.9), Q2<>$Q$1), "t3_Wave") t2_Wave =IF(AND(H2=M2, L2<(H2*0.9), Q2<>$Q$1), "t2_Wave") t1_Wave =IF(AND(G2=M2, L2<(G2*0.9), Q2<>$Q$1), "t1_Wave")

Categories

Cell Biology, Metabolomics, Mouse Model, Neural Stem Cell, Adipose-Derived Mesenchymal Stem Cell, Myoblast

Licence