The pipeline was designed to integrate following aspects:
Reproducibility: Analysis needs to be easily reproduced by external researchers.
Easy-to-Use: The pipeline was designed to be user-friendly and applicable for non-expert users.
Compatible: The pipeline should be feasible for multiple designs of MEA layouts
The full pipeline could be used by following commands:
# Define your data structures with ctr and treatment conditions
#Example (shape file):
# files def
# 1 filename1.mat Basline
# 2 filename2.mat TR_X
# 3 filename3.mat TR_Y
# 4 filena44e.mat TR_Z
# load MEA and shape file (experimental shape) data into a MEA object
object=MEA(path, def, TR="Post_Glutatate")
object@Shape=shape
#Define a dynamic basline based on your "Basline" input
object=Align_Zero(object,STD=10,Edges=1000,Exp_start=100000,Exp_end=500000, Exp_chanel=21,plot=T)
object=Finde_Peaks(object)
object=Find_IPI(object,samp_freq=1000)
#optional
saveRDS(object, "object_233.R")
#Layout file defines your MEA layout
layout=read.csv("Layout.csv", sep=";")
#Analysis and plotting of the raster- or a scatterplot
Plot_Events_Scatter(object,RasterP=T,layout)
D. H. Heiland & K. Joseph, Translational Research Group, Medcal-Center Freiburg, University of Freiburg