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xpose's Introduction

XPoSE

This repo contains code to reproduce figures in the manuscript "MultipleXed Population Selection and Enrichment single nucleus RNA sequencing (XPoSE-seq) enables sample identity retention during transcriptional profiling of rare populations"

https://www.biorxiv.org/content/10.1101/2023.09.27.559834v1

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xpose's Issues

01_assign_metadata error

image

is there something that's missing here? I don't fully understand what the function is doing

lines 62-67 from the 01_assign_metadata_make_initial_object.R file:

#order them
invisible(lapply(objects, function(name) {
        df <- get(name)  # Get the data frame from the environment
        modified_df <- sort_dataframe(df)  # Apply the function to the data frame
        assign(name, modified_df, envir = .GlobalEnv)  # Update the data frame in the environment
}))

Proportion plot stats

F2stats is the first attempt to calculate the proportions for F2
image

Steps in my head:

  1. calculate counts with calc_counts
  2. split by rat_group then calculate proportions
  3. find z score from the proportions with homecage as control
  4. run 2 way anova on the z scored data

Figure 1 code and add_STreads

image Inspiration, the new object has streads as metadata. Want to automate making this plot

Uploaded F1 script and add_STreads.R

source()

@DJT333 can you make changes to line 22: use source() and not have a dependency on the output of another script

Prep and make_upset underscore issue

If the cluster name has an underscore, there is an issue with prep_upset and make_upset.

~Line 17 within prep_upset, involves string split and underscores!

make_heatmap.R function

image the inspiration, want to automate for glut and gaba. Need 2 outputs, the pdf and a csv of the markers to upload as supplemental data.

Added code from Kareem when he manually plotted these into the start of the function file.

UMAP coloring

general plots have been color coded with the hex codes from the Formatting document.

image

need to pick colors to split by groups, ratID, and sex.

subset_reclust.R not working as expected

Please help!!

I define clusters to keep in the subset as clust_tokeep. When I run line 57 I get

Cannot find the following identities in the object: 0123456781213141516171920212429

I think this means it's not separating the clust_tokeep into different idents.

Proportion table calculating proportion for all rows/column

calc_proportions.R

When it calculates the proportion, it's for the total of all factors.

For example, if we are using it to calculate cluster populations for each rat/population, we need it to calculate the proportion relative to the nuclei collected from each rat's population.

Inclusion threshold for pseudobulk

In figure2.R line 66, I expect all clusters to be ran for glut since there are > 100 nuclei per cluster in each cluster.

         CTL6 CTL6b ITL23 ITL56 NPL56 PTL5

Active 334 6 525 737 26 233
Homecage 2817 295 2824 2913 464 1271
Non-active 1121 100 1306 1262 180 598

Table:
Non-active Homecage
ITL56 737 2913
ITL23 525 2824
CTL6 334 2817
PTL5 233 1271

However, I think it's still using Active for the inclusion criteria despite what is in the comp_vect spot

save_vlnplot.R tweaks

Trying to automate this to produce nCount_RNA and nFeature_RNA for glut and gaba:
image

-set the plot to be a certain size. If testing between glut/gaba there is a difference in cluster name length, and the violins get squished. In the plot it's 1.5 x 1.5 inches.
-No labels, was adding them back as correct font, size, and color.

Shiny: Cluster-specific option

(Adding here to keep organized)

Can there be another tab or option for 'cluster specific plots' where there is a dropdown for which cluster you want to look at?

Right now when it groups by group/sex/rat it collapses by cluster

Shiny GABA dataset v2 feedback

Giving this a try :)

I tweaked a few things, but here are things I don't know how to change immediately:

Can the correlation plot between 2 genes be worked in? Perhaps it has to be a different tab? The first tab could be 'Single gene analysis' instead of 'GABA dataset' on the output section, then another tab for 'Multiple gene analysis'. This is me assuming multiple tabs are an option

Can all features be italic? This will conform with gene naming standards.

I noticed on the 'split by: group' feature plots, the i's are capitalized in negative and positive.

Can you make the colors specific to the hex codes in the formatting file? This might be a larger issue that we need to mod the base seurat objects (along with 'renaming' the clusters from the numbers to the cluster names)

PS: I like the hover color on the drop downs!

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