[MILESTONE CHECKLIST] 2. First pass polish of chapter 8

[NatalieZelenka]

Chapter 8: Combining gene expression data sets

This is a milestone rather than just an issue since this will be the first chapter that is properly finished and that I will commit to not refactoring, changing, or adding to... and that's going to be a big deal: deep breath.

Preparations

• [x] Read through and plan (#38)

  Chapter to-do

• [x] A once over of the structure, and quality of the written sections.
  • [x] Introduction
  • [x] Background
  • [x] Ontolopy (#33, )
    • [x] Ontolopy polished into a proper thing that is properly released on pypi with a sphinx website (#33,) https://github.com/NatalieThurlby/ontolopy
      • [x] Basic documentation (sphinx)
      • [x] Roadmap
      • [x] Tests (minimal)
      • [x] Website (sphinx)
      • [x] Can be pip'd into #34
  • [x] Future work
• [x] All research for this chapter finished/in ipynb/reproducible:
  • [x] Data acquisition (#39, )
  • [x] Data wrangling (#34)
  • [x] Results Moved to appendix:
  • [x] Test data simulation (add as separate R ipynb?) Moved to future work:
  • [x] Batch Correction

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Checklist

• [x] Citations done
• [x] Cross-references to other parts of the book
• [x] Figures, captions and references in text done
• [x] TODOs for other sections based on this chapter (e.g. in intro/abstract/discussion) written.

• [x] Headings sorted (right amount of ## everywhere)

  Not doing here

  It's okay not to have finished:

• some signposting text/cross-references to later chapters (since it will be easier to do this after later chapters are done).
• nice-to-haves like epigraphs, fun asides, hand-illustrations
• complete polish (i.e. of word choice, things like active/passive, decisions on how to refer to certain things, acronyms explained, etc)
• Binder links: since I should try an easier (non-R) chapter first.
• Interactive figure captions
• IRkernel figure captions
• Every single TODO

[NatalieZelenka]

Order to do this in:

• [x] Data #39
• [ ] Data wrangling #34
• [x] Uberon-py #33
• [ ] Read through #38
• [ ] Test data simulation 😱
• [x] Background
• [ ] Batch correction (simulation)
• [ ] Batch correction (combined set)
• [ ] Results
• [ ] Intro/discussion/future work
• [ ] Other section notes

[NatalieZelenka]

I will be SO proud of myself when this is finished!

[NatalieZelenka]

I originally planned that I would finish this Chapter first as a warm-up for the other two, however, due to the email from FENG, I decided to do the Snowflake chapter first as it is the least finished.

This milestone is a little bit strange now as the point of it was to get in the hang of finishing a Chapter - and the first chapter to be finished may well be Snowflake.

This is also why I'm changing the due date of this milestone.

I still hope that I will be able to do some of this work to make this chapter more complete before submitting/examination.

[NatalieZelenka]

Originally wanted to use .Rmd for data chapters, and triedusing jupytext c05-combining/3-data-wrangling.Rmd --to md:myst to convert from Rmarkdown to Myst. (Not properly tested). The reason I want to use Rmd is the ability to use R and Python in one notebook. I'm not sure if this will work in Myst/Jupyter Book. I decided to use the alternative, which is splitting up chapter sections into things that only use one format, i.e. move the data downloading into the 'data' chapter (as an R ipynb) and then have the 'data wrangling' chapter be a python ipynb.

[NatalieZelenka]

Removed description of SVA: not relevant

SVA is used in cases where you do not have a covariate that drives batch effect (i.e. you do not have information about processing date, technicians, processing centres, etc), but you expect that batch effects will be present. SVA estimates which samples belong to which batches, before using ComBat to remove the effect due to those batches.

[NatalieZelenka]

Closed by #45