Roadmap

[HadrienG]

Overview

the goal of the project is to create a (meta)genomics reads simulator, i.e. a program capable of simulating realistic high-throughput sequencing data

This issue is aimed at being a todo list for the project.

• Make a roadmap

V1.0.0

Simulating reads

• From a genome, output perfect reads in fastq format: Issue Genome -> Reads #2
• From a set of genomes, output perfect reads in fastq format given abundance parameters: Issue MetaGenome -> Reads #3
• Generate paired-end reads: Issue Paired-end reads #4
• Add a simple error model: Issue Simple Error Model #5
• Add a more complicated error model, (based on real read data, or literature on Illumina error model?): Issue Advanced error model(s) #6
• Refine the error model from Advanced error model(s) #6: 2D KDE, GC bias and Insert size distribution
• Provide at least 1 good HiSeq and 1 good MiSeq model: Issue Errors models in 0.2.1 don't work #13 and Issue Update error models #26

Input

• The user provides a single-fasta file and coverage information: Issue Genome -> Reads #2
• The user provides a multi-fasta file and abundance parameters: Issue MetaGenome -> Reads #3
• The user provides a multi-fasta file, and choose the type of distribution: Issue Distribution of genomes #12
• The user chooses nothing, and random genomes from RefSeq genomes are selected: Issue Input Genomes from RefSeq #15

Testing and packaging

• Add Travis and Codecov integration
• Add proper logging and error handling: Issue Logging and Error Handling #7
• Refactor to avoid duplicated code when possible: Issue Refactoring #8
• Write tests: Issue Testing #9
• Write documentation: Issue Write documentation #10
• Submit package to PyPi: Issue Submit to PyPi #11
• Add multiprocessing support: Issue Multiprocessing #17
• User testing