JaccardCoef {ScISI} | R Documentation |
The JaccardCoef function takes the return values of
compareComplex
function and calculates, for each pair
of complexes C-i and K-j (where C-i is in first bipartite graph matrix
and K-j is second), the similarity coefficient of Jaccard.
JaccardCoef(dataMat)
dataMat |
A list which is the output from
compareComplex , which is a list of three matrices:
intersect, cminusk, and kminusc which are explained in the details. |
The argument of this function is a list of three matrices all of whom are indexed exactly in the same manner - the rows of each of the matrix is indexed by the complexes, {C-i}, of the first bipartite graph, bg1, and the colunms are indexed by the complexes, {K-j} of the second bipartite graph, bg2.
The first matrix of the list is the intersect matrix, I. The (i,j) entry of I is the cardinality of complex C-i of bg1 and K-j of bg2.
The second matrix of the list is the cminusk matrix, Q. The (i,j) entry of Q is the cardinality of the set difference between C-i and K-j.
The third matrix of the list is the kminusc matrix, P. The (i,j) entry of P is the cardinality of the set difference between K-j and C-i.
The Jaccard Coefficient between two sets (here between two complexes) C-i and K-j is given by the quotient of cardinality(C-i intersect K-j) and cardinality(C-i union K-j). Note that cardinality(C-i intersect K-j) is the (i,j) entry of I, and that cardinality(C-i union K-j) is the sum of the (i,j) entry of I, Q, P.
The return value is a matrix consisting of the Jaccaard coefficient for each pair of complexes C-i and K-j with rows in indexed by C-i and columns indexed by K-j.
Tony Chiang
#go = getGOInfo(wantAllComplexes=FALSE) #mips = getMipsInfo(wantSubComplexes=FALSE) #goM = createGOMatrix(go) #mipsM = createMipsMatrix(mips) #cc = runCompareComplex(mipsM, goM, byWhich = "ROW") #cc$simInd