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+f3m(1) -- Count all the 3-node subgraphs of a directed graph
+======
+
+## SYNOPSIS
+
+`f3m` <graph_in> [<num_random>]
+
+## DESCRIPTION
+
+`f3m` performs a motif analysis on <graph_in>, i.e., it counts all the
+3-node subgraphs and computes the z-score of that count with respect
+to the corresponding configuration model ensemble.
+
+## PARAMETERS
+
+* <graph_in>:
+    input graph (edge list). It must be an existing file.
+
+* <num_random>: 
+    The number of random graphs to sample from the configuration model
+    for the computation of the z-score of the motifs.
+
+
+## OUTPUT
+
+`f3m` prints on the standard output a table with 13 rows, one for each
+of the 13 possible 3-node motifs. Each line is in the format:
+
+        motif_number  count  mean_rnd  std_rnd  z-score
+
+where `motif_number` is a number between 1 and 13 that identifies the
+motif (see [MOTIF NUMBERS][] below), `count` is the number of
+subgraphs ot type `motif_number` found in <graph_in>, `mean_rnd` is
+the average number of subgraphs of type `motif_number` in the
+corresponding configuration model ensemble, and `std_rnd` is the
+associated standard deviation. Finally, `z-score` is the quantity:
+
+       (count - mean_rnd) / std_rnd
+
+The program also prints a progress bar on STDERR.
+
+
+## MOTIF NUMBERS
+
+We report below the correspondence between the 13 possible 3-node
+subgraphs and the corresponding `motif_number`. In the diagrams,
+'O--->O' indicates a single edge form the left node to the right node,
+while 'O<==>O' indicates a double (bi-directional) edge between the
+two nodes:
+            
+       (1)  O<---O--->O
+            
+       (2)  O--->O--->O
+
+       (3)  O<==>O--->O
+
+       (4)  O--->O<---O
+       
+       (5)  O--->O--->O
+             \        ^
+              \_______|
+        
+       (6)  O<==>O--->O
+             \        ^
+              \_______|
+              
+       (7)  O<==>O<---O
+          
+       (8)  O<==>O<==>O
+           
+       (9)  O<---O<---O
+             \        ^
+              \_______|
+        
+      (10)  O<==>O<---O
+             \        ^
+              \_______|
+              
+      (11)  O--->O<==>O
+             \        ^
+              \_______|
+     
+      (12)  O<==>O<==>O
+             \        ^
+              \_______|
+
+      (13)  O<==>O<==>O
+            ^\       ^/ 
+             \\_____//
+              \_____/
+
+
+
+## EXAMPLES
+
+To perform a motif analysis on the E.coli transcription regulation
+graph, using 1000 randomised networks, we run the command:
+
+        $ f3m e_coli.net 1000
+        1          4760         4400.11    137.679     +2.614
+        2           162          188.78      8.022     -3.338
+        3             0            0.89      3.903     -0.228
+        4           226          238.32      7.657     -1.609
+        5            40            6.54      2.836    +11.800
+        6             0            0.01      0.077     -0.078
+        7             0            0.12      0.642     -0.192
+        8             0            0.00      0.032     -0.032
+        9             0            0.01      0.109     -0.110
+        10            0            0.00      0.000     +0.000
+        11            0            0.00      0.032     -0.032
+        12            0            0.00      0.000     +0.000
+        13            0            0.00      0.000     +0.000
+        $
+
+Notice that the motif `5` (the so-called "feed-forward loop") has a
+z-score equal to 11.8, meaning that it is highly overrepresented in
+the E.coli graph with respect to the corresponding configuration model
+ensemble. Conversely, the motif `2` (three-node chain) is
+underrepresented, as made evident by value of the z-score (-3.338).
+
+## SEE ALSO
+
+johnson_cycles(1)
+
+## REFERENCES
+
+* R\. Milo et al. "Network Motifs: Simple Building Blocks of Complex
+  Networks".  Science 298 (2002), 824-827.
+
+* R\. Milo et al. "Superfamilies of evolved and designed networks."
+  Science 303 (2004), 1538-1542
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Chapter 8, Cambridge University Press
+  (2017)
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Appendix 16, Cambridge University Press
+  (2017)
+
+
+## AUTHORS
+
+(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 `<v.nicosia@qmul.ac.uk>`.