meyer-lab / tHMM

A general Python framework for using hidden Markov models on binary trees or cell lineage trees.
https://asmlab.org
MIT License
10 stars 1 forks source link

barcoding experiment #858

Closed Farnazmdi closed 3 years ago

Farnazmdi commented 3 years ago

Figure S16 (histogram) and figure S17 (Sankey plots)

I added a new property for cells (barcode) but since each lineage has a unique barcode, I didn't really need to use it, but I thought it wouldn't hurt to keep it as a cell's property. I understand the histogram figures are not very elegant for going into a publication. If we are only showing them to the editors, they may suffice? If we are planning to insert them into the supp figures, please let me know.

I was not sure how to link a go figure to our getSetup. I created those figures in the terminal and saved them. I can manually upload them to the output folder if we want to have them in the repo. But the figure for both drugs is in the thmm channel in Slack.

codecov[bot] commented 3 years ago

Codecov Report

Merging #858 (8030a47) into master (22e51a2) will decrease coverage by 0.06%. The diff coverage is 100.00%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #858      +/-   ##
==========================================
- Coverage   74.16%   74.09%   -0.07%     
==========================================
  Files          24       24              
  Lines        1912     1915       +3     
==========================================
+ Hits         1418     1419       +1     
- Misses        494      496       +2     
Flag Coverage Δ
unittests 74.09% <100.00%> (-0.07%) :arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files Coverage Δ
lineage/CellVar.py 97.43% <100.00%> (-1.24%) :arrow_down:
lineage/LineageTree.py 100.00% <100.00%> (ø)
lineage/states/stateCommon.py 92.92% <0.00%> (-1.02%) :arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more Δ = absolute <relative> (impact), ø = not affected, ? = missing data Powered by Codecov. Last update 22e51a2...8030a47. Read the comment docs.

Farnazmdi commented 3 years ago

Thanks, could you please also merge this?