# HG changeset patch # User rnateam # Date 1404839896 14400 # Node ID 27dde42069e0daecd180efd95ddbc4ba8041f119 # Parent f973ec6e5192ab06f5a12696ce1f3d0874e11e60 Uploaded diff -r f973ec6e5192 -r 27dde42069e0 blockclust.xml --- a/blockclust.xml Tue Jul 08 13:04:30 2014 -0400 +++ b/blockclust.xml Tue Jul 08 13:18:16 2014 -0400 @@ -163,7 +163,7 @@ BlockClust runs in three modes: 1) Pre-processing - converts given mapped reads (BAM) into BED file of tags -2) Clustering and classification - of given input block groups (from blockbuster tool) as explained in [1]_ +2) Clustering and classification - of given input block groups (from blockbuster tool) as explained in the original paper. 3) Post-processing - extracts distribution of clusters searched against Rfam database and plots hierarchical clustering made out of centroids of each BlockClust predicted cluster. For a thorough analysis of your data, we suggest you to use complete blockclust workflow, which contains all three modes of operation. @@ -199,13 +199,9 @@ ------ -**Licenses** - -If **BlockClust** is used to obtain results for scientific publications it should be cited as [1]_. - **References** -[1] Pavankumar Videm, Dominic Rose, Fabrizio Costa, and Rolf Backofen. "BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles." Bioinformatics 30, no. 12 (2014): i274-i282. +Pavankumar Videm, Dominic Rose, Fabrizio Costa, and Rolf Backofen. "BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles." Bioinformatics 30, no. 12 (2014): i274-i282.