TDARACNE {TDARACNE} | R Documentation |
Main function, see P. Zoppoli, S. Morganella, M. Ceccarelli. TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach. BMC Bioinformatics 2010, 11:154.
TDARACNE(eSet,N,delta=3,likehood=1.2,norm=2,logarithm=1,thresh=0,ksd=1,tolerance=0.15,plot=FALSE,dot=FALSE,name="youHaveForgottenIt",adj=FALSE)
eSet |
eSet is the ExpressionSet object |
N |
N is respectively the number of bins in percentile normalization or in rank normalization |
delta |
delta is the maximum time delay allowed to infer connections |
likehood |
likehood is the fold change used as threshold to state the initial change expression (IcE) |
norm |
if you want column percentile normalization put norm == 1; if you want Rank normalization put norm == 2; |
logarithm |
if z is log put logarithm == 0; |
thresh |
the Influence threshold. if you have a threshold and a SD put them here in this format: c(thresh,SD) if you don't have threshold put 0 in thresh; |
ksd |
ksd is the standard deviation multiplier; |
tolerance |
tolerance is the DPI tolerance; 0 means no tolerance 1 means no DPI 0.15 is the default ARACNE tolerance as it is for TDARACNE |
plot |
plot must be TRUE to obtain automatically the graph |
dot |
dot must be TRUE to obtain a .dot file |
name |
name must be written with quotation marks(like this:'examplename') and is the name of the .dot file produced; |
adj |
adj must be TRUE to obtain an adjacent matrix |
## take paper data library(TDARACNE) data(dataIRMAon) data(threshIRMAon) ## main function; in output gives to you and adj matrix and a .dot file # eSet is the ExpressionSet object # N is respectively the number of bins in percentile normalization or in rank normalization # delta is the maximum time delay allowed to infer connections # likehood is the fold change used as threshold to state the initial change expression (IcE) # if you want column percentile normalization put norm == 1; # if you want Rank normalization put norm == 2; # if z is log put logarithm == 0; # if you don't have threshold put 0 in thresh; # ksd is the standard deviation multiplier; # tolerance is the DPI tolerance; # plot must be TRUE to obtain automatically the graph # dot must be TRUE to obtain a .dot file # name must be written with quotation marks(like this:'examplename') and is the name of the .dot file produced; # adj must be TRUE to obtain an adjacent matrix TDARACNE(dataIRMAon,11,"netIRMAon",delta=3,likehood=1.2,norm=2,logarithm=1,thresh=threshIRMAon,ksd=0,tolerance=0.15);