Description Usage Arguments Value See Also Examples
From the dataset in data, the function extracts a set of association
rules, with a certain item in their right-hand-side. Each rule extracted has
support greater than minsupp and confidence greater than
minconf. The extraction is made using the apriori
function implemented in the arules package.
minsupp and minconf thresholds are set by the user in order
to extract a limited number of most relevant association rules.
1 |
data |
a GRanges object in which the metadata columns contain the Indicator of presence matrix i.e., a matrix with 1 and 0 values representing presence or absence, respectively (in case other values different from 0 are present, all of them are considered as representing presence). |
TF |
a string with the name of the trancription factor wanted in the right-hand-side of the extracted rules. |
minsupp |
an integer, the minimal support of the extracted rules. |
minconf |
an integer, the minimal confidence of the extracted rules. |
type |
a logical parameter; if |
A data frame with the association rules extracted and their quality measures of support, confidence and lift.
apriori
1 2 3 4 5 6 7 8 9 | # Load the dataset:
data('MCF7_chr1')
# To extract association rules from data, with TEAD4=1 in the right-hand-side
# and support greater than 0.005 and confidence greater than 0.62:
# r_TEAD4 <- rulesGen(data, 'TEAD4=1', minsupp=0.005, minconf=0.62,
# type=TRUE)
r_TEAD4 <- rulesGen(MCF7_chr1, 'TEAD4=1', 0.005, 0.62, TRUE)
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