Revision 5a00bea33ef214bd26e0e78885f9609a936c0a66 authored by Luca Venturini on 06 November 2015, 13:41:36 UTC, committed by Luca Venturini on 06 November 2015, 13:41:36 UTC
1 parent 7462deb
DESCRIPTION.md
Mikado is a lightweight Python3 pipeline whose purpose is to facilitate the identification
of expressed loci from RNA-Seq data * and to select the best models in each locus.
The logic of the pipeline is as follows:
1. In a first step, the annotation (provided in GTF/GFF3 format) is parsed to locate *superloci* of overlapping features on the **same strand**.
2. The superloci are divided into different *subloci*, each of which is defined as follows:
* For multiexonic transcripts, to belong to the same sublocus they must share at least a splicing junction (i.e. an intron)
* For monoexonic transcripts, they must overlap for at least one base pair
* All subloci must contain either only multiexonic or only monoexonic transcripts
3. In each sublocus, the pipeline selects the best transcript according to a user-defined prioritization scheme.
4. The resulting *monosubloci* are merged together, if applicable, into *monosubloci_holders*
5. The best non-overlapping transcripts are selected, in order to define the *loci* contained inside the superlocus.
* At this stage, monoexonic and multiexonic transcript are checked for overlaps
* Moreover, two multiexonic transcripts are considered to belong to the same locus if they share a splice *site* (not junction)
6. Once the loci have been defined, the program backtracks and looks for transcripts which can be assigned unambiguously to a single locus and constitute valid alternative splicing isoforms of the main transcripts.
The criteria used to select the "*best*" transcript are left to the user's discretion, using specific configuration files.
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