From 3aee2fd43e3059a699af2b63c6f2395e5a55e515 Mon Sep 17 00:00:00 2001 From: KatolaZ Date: Wed, 27 Sep 2017 15:06:31 +0100 Subject: First commit on github -- NetBunch 1.0 --- doc/f3m.1 | 156 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 156 insertions(+) create mode 100644 doc/f3m.1 (limited to 'doc/f3m.1') diff --git a/doc/f3m.1 b/doc/f3m.1 new file mode 100644 index 0000000..fb1a919 --- /dev/null +++ b/doc/f3m.1 @@ -0,0 +1,156 @@ +.\" generated with Ronn/v0.7.3 +.\" http://github.com/rtomayko/ronn/tree/0.7.3 +. +.TH "F3M" "1" "September 2017" "www.complex-networks.net" "www.complex-networks.net" +. +.SH "NAME" +\fBf3m\fR \- Count all the 3\-node subgraphs of a directed graph +. +.SH "SYNOPSIS" +\fBf3m\fR \fIgraph_in\fR [\fInum_random\fR] +. +.SH "DESCRIPTION" +\fBf3m\fR performs a motif analysis on \fIgraph_in\fR, 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\. +. +.SH "PARAMETERS" +. +.TP +\fIgraph_in\fR +input graph (edge list)\. It must be an existing file\. +. +.TP +\fInum_random\fR +The number of random graphs to sample from the configuration model for the computation of the z\-score of the motifs\. +. +.SH "OUTPUT" +\fBf3m\fR 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: +. +.IP "" 4 +. +.nf + + motif_number count mean_rnd std_rnd z\-score +. +.fi +. +.IP "" 0 +. +.P +where \fBmotif_number\fR is a number between 1 and 13 that identifies the motif (see \fIMOTIF NUMBERS\fR below), \fBcount\fR is the number of subgraphs ot type \fBmotif_number\fR found in \fIgraph_in\fR, \fBmean_rnd\fR is the average number of subgraphs of type \fBmotif_number\fR in the corresponding configuration model ensemble, and \fBstd_rnd\fR is the associated standard deviation\. Finally, \fBz\-score\fR is the quantity: +. +.IP "" 4 +. +.nf + + (count \- mean_rnd) / std_rnd +. +.fi +. +.IP "" 0 +. +.P +The program also prints a progress bar on STDERR\. +. +.SH "MOTIF NUMBERS" +We report below the correspondence between the 13 possible 3\-node subgraphs and the corresponding \fBmotif_number\fR\. In the diagrams, \'O\-\-\->O\' indicates a single edge form the left node to the right node, while \'O\fI==\fRO\' indicates a double (bi\-directional) edge between the two nodes: +. +.IP "" 4 +. +.nf + + (1) O<\-\-\-O\-\-\->O + + (2) O\-\-\->O\-\-\->O + + (3) O<==>O\-\-\->O + + (4) O\-\-\->O<\-\-\-O + + (5) O\-\-\->O\-\-\->O + \e ^ + \e_______| + + (6) O<==>O\-\-\->O + \e ^ + \e_______| + + (7) O<==>O<\-\-\-O + + (8) O<==>O<==>O + + (9) O<\-\-\-O<\-\-\-O + \e ^ + \e_______| + + (10) O<==>O<\-\-\-O + \e ^ + \e_______| + + (11) O\-\-\->O<==>O + \e ^ + \e_______| + + (12) O<==>O<==>O + \e ^ + \e_______| + + (13) O<==>O<==>O + ^\e ^/ + \e\e_____// + \e_____/ +. +.fi +. +.IP "" 0 +. +.SH "EXAMPLES" +To perform a motif analysis on the E\.coli transcription regulation graph, using 1000 randomised networks, we run the command: +. +.IP "" 4 +. +.nf + + $ 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 + $ +. +.fi +. +.IP "" 0 +. +.P +Notice that the motif \fB5\fR (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 \fB2\fR (three\-node chain) is underrepresented, as made evident by value of the z\-score (\-3\.338)\. +. +.SH "SEE ALSO" +johnson_cycles(1) +. +.SH "REFERENCES" +. +.IP "\(bu" 4 +R\. Milo et al\. "Network Motifs: Simple Building Blocks of Complex Networks"\. Science 298 (2002), 824\-827\. +. +.IP "\(bu" 4 +R\. Milo et al\. "Superfamilies of evolved and designed networks\." Science 303 (2004), 1538\-1542 +. +.IP "\(bu" 4 +V\. Latora, V\. Nicosia, G\. Russo, "Complex Networks: Principles, Methods and Applications", Chapter 8, Cambridge University Press (2017) +. +.IP "\(bu" 4 +V\. Latora, V\. Nicosia, G\. Russo, "Complex Networks: Principles, Methods and Applications", Appendix 16, Cambridge University Press (2017) +. +.IP "" 0 +. +.SH "AUTHORS" +(c) Vincenzo \'KatolaZ\' Nicosia 2009\-2017 \fB\fR\. -- cgit v1.2.3