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CAGEscan clustering tools

Copyright: 2011-2013 RIKEN Omics Science Center
           2013-2015 RIKEN Center for Life Science Technologies, Division of Genomics Technologies
Author: Nicolas Bertin <[email protected]>
License: GNU public license version 2 (GPL v2)

This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.

This work was supported by a research grant from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) for the RIKEN Omics Science Center to Yoshihide Hayashizaki, and by a research grant from MEXT to the RIKEN Center for Life Science Technologies.

CAGEscan-Clustering

Create CAGEscan clusters from paired-end data in BED12, BAM or SAM format, using the data itself as a guide or an optional list of CAGE Tag Starting Site (CTSS) clusters in BED6 format.

CAGEscan-Clustering is a Perl script written at RIKEN, that calls pairedBamToBed12 and other programs from the BEDTools suite. It is fully documented in the file CAGEscan-Clustering.pod.

Release history

Version 1.0

  • Initial public release

Version 1.1

  • Added a new option fit_to_guiding_cluster_size.
  • Made more portable with regard to awk versions.
  • Updated for backwards-incompatible changes in BEDTools 2.20.0.

Version 1.2

  • Use ;; as internal separator, to accomodate for the presence of single semicolons in the name field of SAM, BAM or BED12 input (in particular for workflows using TagDust 2).

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Create CAGEscan clusters from CAGE paired-end reads

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