Add NB-GLMM to master branch.

[MikeDMorgan]

This major update to Milo (2.0) introduces a mixed effect model. This can be used to model dependence between observations, including genetic relationships. Therefore, Milo can now be used to identify cell state quantitative trait loci (csQTL). More details are included in https://github.com/MorganResearchLab/Milo2.0Analysis_2023

[codecov-commenter]

Codecov Report

Merging #295 (47fb880) into master (3e4e264) will decrease coverage by 5.96%.
The diff coverage is 50.94%.

❗ Current head 47fb880 differs from pull request most recent head 1633c34. Consider uploading reports for the commit 1633c34 to get more accurate results

@@            Coverage Diff             @@
##           master     #295      +/-   ##
==========================================
- Coverage   61.65%   55.69%   -5.96%     
==========================================
  Files          19       30      +11     
  Lines        1476     3065    +1589     
==========================================
+ Hits          910     1707     +797     
- Misses        566     1358     +792     

Files	Coverage Δ
R/buildGraph.R	61.81% <ø> (ø)
R/findNhoodGroupMarkers.R	68.42% <ø> (ø)
R/graphSpatialFDR.R	72.46% <ø> (+1.03%)	⬆️
R/makeNhoods.R	94.49% <100.00%> (ø)
R/plotNhoods.R	27.04% <ø> (ø)
R/milo.R	66.66% <0.00%> (ø)
R/annotateNhoods.R	91.30% <84.61%> (-3.70%)	⬇️
R/checkSeparation.R	91.66% <91.66%> (ø)
R/utils.R	87.27% <90.90%> (+2.42%)	⬆️
src/invertPseudoVar.cpp	74.07% <74.07%> (ø)
... and 10 more