A Python3 annotation program to select the best gene model in each locus
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:
In a first step, the annotation (provided in GTF/GFF3 format) is parsed to locate superloci of overlapping features on the same strand.
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
In each sublocus, the pipeline selects the best transcript according to a user-defined prioritization scheme.
The resulting monosubloci are merged together, if applicable, into monosubloci_holders
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)
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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