2023-02-07
This is Maëlle's DBGI daily open-notebook.
Today is 2023.02.07
meeting with pma
Start of Master thesis!
See open-notebook.pmallard.2023.02.07.md
Regulations: Must do a formal written thesis (~30-40 pages) and an oral presentation
TODO
-
Read articles/look examples from open-notebook.pmallard.2023.02.07.md
- https://microbeatlas.org/
- https://www.nature.com/articles/s41592-021-01339-5
- https://pubmed.ncbi.nlm.nih.gov/34662515/
- https://jcheminf.biomedcentral.com/articles/10.1186/s13321-020-00445-4
- https://pubs.acs.org/doi/full/10.1021/acs.jnatprod.8b00767
- https://academic.oup.com/gigascience/article/doi/10.1093/gigascience/giac124/6980761
-
Familiarize with tools
- datawarrior
- tmap
- molplotly
- vega grammar
CODE
NOTES
tmap
python
Visualization => Python package Faerun for large scale data sets - Faster than matplotlib/pyplot - interactive plots
molplotly
python
allows 2D images of molecules to be shown in plotly figures when hovering over the data points
vega
visualizations are described in JSON, and generate interactive views using either HTML5 Canvas or SVG
Lots of possible plots => geographic maps, tree diagrams & network diagrams might be interesting
datawarrior
Important features:
- Plots interacting with each other
- 'contains' ...
- Search by structure
- Check for similarity
Features needed for the vizualisation project
- Plots interacting with each other (datawarrior)
- 'contains' ... (datawarrior)
- Search by structure (datawarrior)
- Check for similarity (datawarrior)
- phylogeny by MASST (https://masst.gnps2.org/microbemasst/) (NP classifier)
TODO NEXT
- prepare presentation for DBGI meeting
- Search for best way to create dashboard
- Java
- Python
- HTML
- Read articles/look examples from open-notebook.pmallard.2023.02.07.md
- https://microbeatlas.org/
- https://www.nature.com/articles/s41592-021-01339-5
- https://pubmed.ncbi.nlm.nih.gov/34662515/
- https://jcheminf.biomedcentral.com/articles/10.1186/s13321-020-00445-4
- https://pubs.acs.org/doi/full/10.1021/acs.jnatprod.8b00767
- https://academic.oup.com/gigascience/article/doi/10.1093/gigascience/giac124/6980761