clm mate - compute best matches between two clusterings
clmmate is not in actual fact a program. This manual page documents the
behaviour and options of the clm program when invoked in mode
mate. The
options
-h,
--apropos,
--version,
-set,
--nop are accessible in all
clm modes. They are described in the
clm manual page.
clm mate [-o fname (
output file name)
] [-b
(
omit headers)
] [--one-to-many (
require multiple hits
in <clfile1>)
] [-h (
print synopsis,
exit)
] [--apropos (
print synopsis, exit)
]
[--version (
print version, exit)
] <clfile1>
<clfile2>
clm mate computes for each cluster X in clfile1 all clusters Y in clfile2
that have non-empty intersection and outputs a line with the data points
listed below.
overlap(X,Y) # 2 * size(meet(X,Y)) / (size(X)+size(Y))
index(X) # name of cluster
index(Y) # name of cluster
size(meet(X,Y))
size(X-Y) # size of left difference
size(Y-X) # size of right difference
size(X)
size(Y)
projection(X, clfile2) # see below
projection(Y, clfile1) # see below
The projected size of a cluster X relative to a clustering K is simply the sum
of all the nodes shared between any cluster Y in K and X, duplications
allowed. For example, the projected size of (0,1) relative to {(0,2,4),
(1,4,9), (1,3,5)} equals 3.
The overlap between X and Y is exactly 1.0 if the two clusters are identical,
and for nearly identical clusterings the score will be close to 1.0.
All of this information can also be obtained from the contingency matrix defined
for two clusterings. The [i,j] row-column entry in a contigency matrix between
to clusterings gives the number of entries in the intersection between
cluster i and cluster j from the respective clusterings. The other
information is implicitly present; the total number of nodes in
clusters i and j for example can be obtained as the sum of entries
in row i and column j respectively, and the difference counts can
then be obtained by substracting the intersection count. The contingency
matrix can easily be computed using
mcx; e.g.
mcx /clfile2 lm /clfile1 lm tp mul /ting wm
will create the contingency matrix in mcl matrix format in the file ting, where
columns range over the clusters in clfile1.
The output can be put to good use by sorting it numerically on that first score
field. It is advisable to use a stable sort routine (use the
-s option
for UNIX sort) From this information one can quickly extract the closest
clusters between two clusterings.
-o fname (
output file name)
Specify the name of the output file.
-b (
omit headers)
Batch mode, omit column names.
--one-to-many (
require multiple hits in <clfile1>)
Do not output information for clusters in the first file that are subset of a
cluster in the second file.
Stijn van Dongen.
mclfamily(7) for an overview of all the documentation and the utilities
in the mcl family.