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iSEE app for snRNA-seq data
#12
Open
lcolladotor
opened
1 year ago
lcolladotor
commented
1 year ago
[ ] Create a subsetted SCE object similar to
https://github.com/LieberInstitute/septum_lateral/blob/main/snRNAseq_mouse/code/03_iSEE_apps/snRNA-seq_app/subset.R
which is based off
https://github.com/LieberInstitute/septum_lateral/blob/b0893a51cf71c685a66aa3d4165d2a829badabd7/snRNAseq_mouse/code/02_analyses/03_reducedDimensions_clustering.R#L998-L1070
. Aka, keep only
logcounts
and drop any large memory components. The final object should ideally be less than 2.5 GB of RAM.
[ ] Adapt the
app.R
script from
https://github.com/LieberInstitute/septum_lateral/tree/main/snRNAseq_mouse/code/03_iSEE_apps/snRNA-seq_app
, then test it locally.
[ ] From the local app, find the display settings that we'd like to share by default (talk with @heenadivecha about this). You'll need a list of genes to highlight on the default heatmap (max 10 genes).
[ ] Then adapt the
deploy.R
script from
https://github.com/LieberInstitute/septum_lateral/tree/main/snRNAseq_mouse/code/03_iSEE_apps/snRNA-seq_app
.
[ ] Edit the shinyapps.io settings to match those we typically use for
iSEE
apps (talk to @heenadivecha again).
logcountsand drop any large memory components. The final object should ideally be less than 2.5 GB of RAM.app.Rscript from https://github.com/LieberInstitute/septum_lateral/tree/main/snRNAseq_mouse/code/03_iSEE_apps/snRNA-seq_app, then test it locally.deploy.Rscript from https://github.com/LieberInstitute/septum_lateral/tree/main/snRNAseq_mouse/code/03_iSEE_apps/snRNA-seq_app.iSEEapps (talk to @heenadivecha again).