Open ciszew opened 11 months ago
Hi @ciszew,
MCMICRO uses a variant of Minerva called Auto-Minerva, which generates a basic view of the stitched and registered image. You can turn this feature on by adding viz: true
to the workflow
section of your params.yml
:
workflow:
viz: true
This will generate a viz/
subdirectory, and you can view the resulting Auto-Minerva visualization by opening index.html
in that subdirectory.
As mentioned above, this will only show the stitched and registered image. To introduce additional manual annotations, you will need to run Minerva Story software directly (https://github.com/labsyspharm/minerva-story). You should be able to just import the segmentation masks generated by MCMICRO inside Minerva Story. There are also some modules that can generate cell state clustering from single-cell features. They are relatively quick to run, so you can try all of them by adding:
workflow:
stop-at: downstream
downstream: [naivestates, scimap, fastpg, scanpy, flowsom]
Hello Thank you so much for getting back to me and for making this pipeline avaiable to the community, it is a fantastic tool. I have been using auto generated minerva visualization within MCMICR, its is great and fast option to have a quick look at the data but i find full fledged minerva suit much more powerful and flexible in creating visually guided analysis/presentations and would like to explore its full capabilities. Specifically i was wondering if its possible and how to create "Mask (cellID, State).csv file using mcmicro (screenshot attached), without Mask.csv file only all_cells are avaiable as a mask.
I have also tried couple mcmicro runs with downstream modules: [naivestates, scimap, flowsom] but im not sure i fully understand how this modules work (specifically scimap) when launch within mcmicro, what type of different parameters are avaiable for fine tuning and setting options for this modules when run within mcmicro and more specifically if there is a possibility of configuring nextflow params file so the output integrates better with Minerva story/author (and possibly Minerva analysis, somrthing im just starting to explor) thus my request for documentation in my initial post.
You can use any clustering or cell type calling module in the "downstream" section to define the "Mask.csv" file. The column names and precise file name do vary across the different modules, but I think all of them provide an output file with per-cell clustering. You should just need to rename the cell id and cluster label columns to exactly CellID
and State
.
I'll tweak the modules this weekend to produce the correct column names.
@ciszew If you take the output of one of the modules (e.g., fastpg
) where it assigns cells to clusters and change the Cluster
column name to State
, are you able to load it in Minerva Author?
# Replace the column name Cluster with State
/workspace/exemplar-001/downstream/fastpg $ sed 's/Cluster/State/g' exemplar-001--mesmer_cell-cells.csv > exemplar-001--mesmer_cell-states.csv
# Confirm that the column has been renamed
/workspace/exemplar-001/downstream/fastpg $ head -n 5 exemplar-001--mesmer_cell-states.csv
CellID,State,Method
1,0,FastPG
2,0,FastPG
3,1,FastPG
4,16,FastPG
so I havent run fastpg but i used flowsom, scimap and naivestates, all without any options (just downstream: [flowsom, scimap, naivestates] in worflow in params file) so im guessing default settings (and im not sure what those settings are)
Hi @ciszew,
Some basic information about these clustering methods (what method it runs, what the parameters are, etc.) can be found at https://mcmicro.org/parameters/core.html#clustering
Naivestates will attempt to infer whether a given marker is expressed in each cell or not. The three lines in those plots are:
(So, for example, it was not able to distinguish the two populations for CD68, because it's not a bi-modal distribution.)
Each cell is then assigned a probability of whether it belongs to the "red" population. If you provide a two-column file mapping markers to cell states (example: https://github.com/labsyspharm/naivestates/blob/master/typemap.csv), it will also combine the probabilities of individual marker expression to assign a cell type / state to individual cells. To specify this file, you can use naivestates-model
workflow parameter:
workflow:
naivestates-model: marker-to-cellstate-map.csv
Lastly, MCMICRO only runs the clustering tools from Scimap, but Scimap also has a whole bunch of tools for additional analysis (https://scimap.xyz/). If you install that software directly, it should be compatible with the MCMICRO output. (@ajitjohnson can help if you run into any issues.)
Thank you so much, this is exactly what i was looking for.
Hello I was wondering if it would be possible to obtain short documentation on how to generate and use different MCMICRO output files in Minerva Author (and possibly Minerva analysis) . For example it is unclear to me how to generate files that could be used for data visualization (as described here: https://github.com/labsyspharm/minerva-story/wiki/How-to-make-a-Minerva-Story%3F#44-import-data-visualizations) Or how to generate additional mask files as described here https://github.com/labsyspharm/minerva-story/wiki/How-to-make-a-Minerva-Story%3F#45-import-cell-segmentation-masks can all this be done in MCMICRO directly?