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…t-structure feat: new manuscript structure
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## Introduction | ||
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- Importance of computation in biological research and scope. | ||
- Importance to reproducibility in computational biology. | ||
- Mentioning previous literature and some of their major takeaways and topics not fully covered in here (what kind of languages to learn, advanced text editors/IDEs, | ||
- The computational biology best-practices continuum: reproducibility at the personal level, sharing our research with others and over time. | ||
- Addressing the audience: computational biologists researchers – data analysts, workflow designers, software developers, mathematical modelers, etc. | ||
- Structure of this manuscript: mention Figure 1 and Figure 2. | ||
- **Figure 1:** Funnel structure for better computational biology. | ||
- **Figure 2:** Types of computational biology projects per level. |
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## Level 1: Personal Research | ||
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Goal: How should you manage your computational biology project? | ||
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Topics: | ||
- Literate programming: R Markdown, Jupyter Notebooks | ||
- Version control: Git / GitHub (commits) | ||
- Software versioning and environment managers (Conda, python-env) | ||
- Modularize, snippets | ||
- Coding style: variable naming, linter, pep8, commenting | ||
- Programming practices: paradigms (object-oriented, procedural), assertions, pair-programming |
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## Level 2: Collaboration | ||
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Goal: How to allow your collaborators to reproduce and interact with your research/software? | ||
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Topics: | ||
- Sharing notebooks: R Markdowns and Jupyter Notebooks (Binder, Google CoLab) | ||
- Sharing apps: Shiny apps, Dashboard. | ||
- GitHub (branching, pull requests) | ||
- Workflow automation: Snakemake (NextFlow, Make, Bash script) | ||
- Sharing data and metadata |
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## Level 3: Community | ||
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Goal: How to develop and maintain a computational biology project with community feedback over time? | ||
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Topics: | ||
- GitHub releases and semantic versioning | ||
- Git Flow, GitHub Issues | ||
- Continuous integration and unit tests | ||
- Dependencies per user: pip-tools | ||
- Sharing software as Python packages, Conda/Bioconda or containers (Docker, Singularity) | ||
- Include license (MIT) and DOIs | ||
- Documentation: read the docs. |
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## Case studies | ||
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- Example of computational biology project 1: RNA-seq analysis (workflow) | ||
- Example of computational biology project 2: Genome-scale metabolic model (systems biology project) | ||
- Example of computational biology project 3: Software development (computational tool) |
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## Conclusion | ||
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Pending |
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## Acknowledgments | ||
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Pending |