Clustering for exact matching and BABLBS matching
is the result of the call_acm function in the format of ULI ULI numbands numbands num_matches
is the result of the call_bablbs, call_gd1 or call_gd2 function in the format of ULI ULI
is where the datasets should be stored
value ("exact", "bablbs", "gd1", "gd2") indicating if you want exact matching or BABLBS/Genetic Distance. Default is "exact" i.e. exact matching.
A list with 7 components. The first (SINGLE) is a 3 column matrix of all fingerprint IDs that do not belong to a cluster. The columns correspond to the Cluster_Number, the Cluster_size, and the Fingerprint ID. The second (CLUSTERED) is a matrix of all fingerprint IDs that do belong to a cluster. The columns correspond to the Cluster_Number, the Cluster_size, and the Fingerprint IDs that belong to that cluster. The third (BOTH) combines the others into one matrix. The fourth and fifth calculate RTIN and RTIn-1. The last two are used for the histograms that are produced by a call to this function.
Andrea Benedetti email@example.com
Sahir Rai Bhatnagar
Salamon et. al (1998) Accommodating Error Analysis in Comparison and Clustering of Molecular Fingerprints. Emerging Infectious Diseases Vol. 4, No. 2, April-June 1998
Abasci LLC. JAMES v1.0 User Documentation. 2002.
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#synthesize the results # Exact matching clusters exact<-clusters(input=res1,type="exact") names(exact) exact$RTIN exact$RTIN1 # Clustering based on BABLBS bablbs<-clusters(input=res1, bablbs=res_bab,type="bablbs") names(bablbs) bablbs$RTIN bablbs$RTIN1 # Clustering based on GD1 gd1<-clusters(input=res1, bablbs=res_gd1,type="gd1") names(gd1) gd1$RTIN gd1$RTIN1
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