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comparison blockclust.xml @ 3:27dde42069e0 draft

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author rnateam
date Tue, 08 Jul 2014 13:18:16 -0400
parents f973ec6e5192
children 49e600128a73
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2:f973ec6e5192 3:27dde42069e0
161 fast graph-kernel techniques. BlockClust allows both clustering and 161 fast graph-kernel techniques. BlockClust allows both clustering and
162 classification of small non-coding RNAs. 162 classification of small non-coding RNAs.
163 163
164 BlockClust runs in three modes: 164 BlockClust runs in three modes:
165 1) Pre-processing - converts given mapped reads (BAM) into BED file of tags 165 1) Pre-processing - converts given mapped reads (BAM) into BED file of tags
166 2) Clustering and classification - of given input block groups (from blockbuster tool) as explained in [1]_ 166 2) Clustering and classification - of given input block groups (from blockbuster tool) as explained in the original paper.
167 3) Post-processing - extracts distribution of clusters searched against Rfam database and plots hierarchical clustering made out of centroids of each BlockClust predicted cluster. 167 3) Post-processing - extracts distribution of clusters searched against Rfam database and plots hierarchical clustering made out of centroids of each BlockClust predicted cluster.
168 168
169 For a thorough analysis of your data, we suggest you to use complete blockclust workflow, which contains all three modes of operation. 169 For a thorough analysis of your data, we suggest you to use complete blockclust workflow, which contains all three modes of operation.
170 170
171 **Inputs** 171 **Inputs**
197 Distribution of clusters with annotations searched against Rfam database 197 Distribution of clusters with annotations searched against Rfam database
198 hierarchical clustering made out of centroids of each BlockClust predicted cluster 198 hierarchical clustering made out of centroids of each BlockClust predicted cluster
199 199
200 ------ 200 ------
201 201
202 **Licenses**
203
204 If **BlockClust** is used to obtain results for scientific publications it should be cited as [1]_.
205
206 **References** 202 **References**
207 203
208 [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. 204 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.
209 205
210 206
211 </help> 207 </help>
212 </tool> 208 </tool>