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A Python3 annotation program to select the best gene model in each locus

Project Description

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.

Release History

Release History

This version
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1.0.0b10

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1.0.0b8

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1.0.0b5.post5

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1.0.0b5.post4

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1.0.0b5.post3

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1.0.0b5.post2

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1.0.0b5.post1

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Mikado-1.0.0b10.tar.gz (17.2 MB) Copy SHA256 Checksum SHA256 Source Feb 15, 2017

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