MCL implements Markov cluster algorithm. Among its applications is the assignment of proteins into families based on precomputed sequence similarity information. This approach does not suffer from the problems that normally hinder other protein sequence clustering algorithms, such as the presence of multi-domain proteins, promiscuous domains and fragmented proteins.
Allocate an interactive session and run the program. Sample session:
[user@biowulf]$ sinteractive [user@cn3200 ~]$ module load mcl [+] Loading MCL 14-137 ... [user@cn3200 ~]$ cp $MCL_DATA/* . [user@cn3200 ~]$ mcl cathat --abc -o out2.cathat [mcl] new tab created [mcl] pid 10660 ite ------ chaos time hom(avg,lo,hi) m-ie m-ex i-ex fmv 1 ...... 0.47 0.00 0.87/0.80/0.95 1.33 1.33 1.33 100 2 ...... 0.53 0.00 0.86/0.69/0.95 1.24 1.21 1.67 100 3 ...... 0.35 0.00 0.95/0.88/1.00 1.00 0.67 1.14 100 4 ...... 0.44 0.00 0.94/0.88/1.00 1.08 0.68 0.81 100 5 ...... 0.24 0.00 0.89/0.78/1.00 1.17 0.67 0.57 100 6 ...... 0.20 0.00 0.89/0.80/0.99 0.92 0.92 0.57 100 7 ...... 0.12 0.00 0.95/0.95/0.95 0.92 0.92 0.57 100 8 ...... 0.20 0.00 0.92/0.85/1.00 0.92 0.92 0.57 100 9 ...... 0.25 0.00 0.88/0.76/1.00 0.92 0.69 0.43 100 10 ...... 0.15 0.00 0.93/0.85/1.00 0.90 0.90 0.43 100 11 ...... 0.02 0.00 0.99/0.98/1.00 0.90 0.90 0.43 100 12 ...... 0.00 0.00 1.00/1.00/1.00 0.90 0.90 0.43 100 13 ...... 0.00 0.00 1.00/1.00/1.00 0.90 0.60 0.29 100 [mcl] jury pruning marks: <100,99,99>, out of 100 [mcl] jury pruning synopsis: <99.6 or perfect> (cf -scheme, -do log) [mcl] output is in out.cathat [mcl] 2 clusters found [mcl] output is in out.cathat ... ...End the interactive session:
[user@cn3200 ~]$ exit salloc.exe: Relinquishing job allocation 46116226 [user@biowulf ~]$