Commit 350c55a6 authored by Mathieu Giraud's avatar Mathieu Giraud

vidjil.cpp, doc/algo.org: explains that the -n/-e clustering is not exported in vidjil.data

Additionaly, use everywhere 'clustering' instead of 'clusteri[sz]ation'
parent 1c7e9d80
......@@ -171,10 +171,10 @@ void usage(char *progname)
<< " -r <nb> minimal number of reads containing a window (default: " << MIN_READS_WINDOW << ")" << endl
<< endl
<< "Clusterisation" << endl
<< " -e <file> manual clusterisation -- a file used to force some specific edges" << endl
<< " -n <int> maximum distance between neighbors for automatic clusterisation (default " << DEFAULT_EPSILON << "). No automatic clusterisation if =0." << endl
<< " -N <int> minimum required neighbors for automatic clusterisation (default " << DEFAULT_MINPTS << ")" << endl
<< "Additional clustering (not output in vidjil.data and therefore not used in the browser)" << endl
<< " -e <file> manual clustering -- a file used to force some specific edges" << endl
<< " -n <int> maximum distance between neighbors for automatic clustering (default " << DEFAULT_EPSILON << "). No automatic clusterisation if =0." << endl
<< " -N <int> minimum required neighbors for automatic clustering (default " << DEFAULT_MINPTS << ")" << endl
<< " -S generate and save comparative matrix for clustering" << endl
<< " -L load comparative matrix for clustering" << endl
<< " -C <string> use custom Cost for automatic clustering : format \"match, subst, indels, homo, del_end\" (default "<<Cluster<<" )"<< endl
......@@ -435,7 +435,7 @@ int main (int argc, char **argv)
#endif
break;
// Clusterisation
// Clustering
case 'n':
epsilon = atoi(optarg);
......
......@@ -16,7 +16,7 @@ from a set of reads and detects "windows" overlapping the actual CDR3.
This is based on an fast and reliable seed-based heuristic and allows
to output the most abundant clones. The analysis is extremely fast
because, in the first phase, no alignment is performed with database
germline sequences. Vidjil can also clusterize similar
germline sequences. Vidjil can also cluster similar
clones, or leave this to the user after a manual review.
The method is described in the following paper:
......@@ -70,7 +70,7 @@ These dependencies have no consequences on the visualization through the
browser. They are intented for a command-line use only.
- clustalw :: to compute alignments between windows from a same clone (with =-a= option)
- neato :: to display graph of neighbors for the automatic clusterisation
- neato :: to display graph of neighbors for the additional clustering
* Vidjil parameters
......@@ -127,7 +127,7 @@ Limits to segment a clone
The =-r/-R/-%= options are strong thresholds: if a clone does not have
the requested number of reads, the clone is discarded (except when
using =-l=, see below).
The =-r= option is applied before the additional clusterization, the
The =-r= option is applied before the additional clustering, the
=-R/-%= options after it.
The default =-r 10 -R 10= options are meant to only output clones that
have a significant read support. You can safely put =-r 1 -R 1= if you
......@@ -164,7 +164,14 @@ The first column of the file is the window to be followed
while the remaining columns consist of the window's label.
In Vidjil output, the labels are output alongside their windows.
** Manual clustering
** Further clustering
These options have no consequences on the visualization through the
browser. They are intented for a command-line use only.
Setting the =-n= option triggers an additional automatic
clustering using DBSCAN algorithm (Ester and al., 1996).
The =-e= option allows to specify a file for manually clustering two windows
considered as similar. Such a file may be automatically produced by vidjil
......@@ -220,7 +227,7 @@ CTATGATAGTAGTGGTTATTACGGGGTAGGGCAGTACTACTACTACTACATGGACGTCTG
#+BEGIN_SRC sh
./vidjil -c clones -G germline/IGH -x -r 1 -R 5 -n 5 -d ./data/clones_simul.fa
# Window extraction + clone gathering,
# with automatic clusterisation, distance five (-n 5)
# with automatic clustering, distance five (-n 5)
#+END_SRC
#+BEGIN_SRC sh
......
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