Fig.2D. Ventrobasal thalamus

Last updated: 2023-08-17

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Knit directory: Hevesi_2023/

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File	Version	Author	Date	Message
Rmd	54541d8	Evgenii O. Tretiakov	2023-08-17	updated output
html	9014631	Evgenii O. Tretiakov	2023-08-17	Build site.
Rmd	d1dcfea	Evgenii O. Tretiakov	2023-08-02	alternative stacked violin plot may be helpful for ventrobasal thalamus where we show two clusters with dotplot relative scale
Rmd	edcb936	Evgenii O. Tretiakov	2023-03-14	update methods
html	263f215	Evgenii O. Tretiakov	2023-03-13	Build site.
Rmd	3111dee	Evgenii O. Tretiakov	2023-03-13	workflowr::wflow_publish(c("analysis/eda.Rmd", "analysis/figure_2d-THP7.Rmd",
html	4ef209f	Evgenii O. Tretiakov	2023-03-05	Build site.
Rmd	e584a94	Evgenii O. Tretiakov	2023-03-04	workflowr::wflow_publish(c("analysis/eda.Rmd", "analysis/figure_2d-THP7.Rmd",

Load dataset

srt <- LoadH5Seurat(here(data_dir, "THP7_clusters.h5Seurat"))
Idents(srt) <- "sep_clstr"
neurons <- subset(srt, subset = Rbfox3 > 0 | Elavl4 > 0 | Snap25 > 0 | Stmn2 > 0)
gneurons <- subset(neurons, subset = Gal > 0)

We check list of genes based on our prior knowledge.

gene_of_interest <-
  c("Gal", "Galr1", "Galr2", "Galr3",
    "Slc17a7", "Slc6a4", "Ache", 
    "Prkaca", "Adcy1", "Grin1", 
    "Cck", "Oxt", "Npy", "Sst", "Avp")

genes_present <- Gene_Present(data = srt, gene_list = gene_of_interest)
genes_present

$found_features
 [1] "Gal"     "Galr1"   "Galr2"   "Slc17a7" "Slc6a4"  "Ache"    "Prkaca" 
 [8] "Adcy1"   "Grin1"   "Cck"     "Npy"     "Sst"    

$bad_features
[1] "Galr3" "Oxt"   "Avp"  

$wrong_case_found_features
[1] "NA (check not performed.  Set 'case_check = TRUE' to perform check."

DotPlot_scCustom(
  seurat_object = srt,
  assay = "RNA",
  features = genes_present$found_features,
  flip_axes = TRUE,
  x_lab_rotate = TRUE,
  colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"))

Version	Author	Date
9014631	Evgenii O. Tretiakov	2023-08-17
4ef209f	Evgenii O. Tretiakov	2023-03-05

DimPlot_scCustom(
  srt,
  label = TRUE,
  repel = TRUE,
  pt.size = 2,
  figure_plot = TRUE
  ) + ggtitle("Clusters") + NoLegend()

Version	Author	Date
4ef209f	Evgenii O. Tretiakov	2023-03-05

Derive and filter matrix of neurons

mtx_neurons <-
    gneurons %>%
    GetAssayData("data", "RNA") %>%
    as.data.frame() %>%
    t()
rownames(mtx_neurons) <- colnames(gneurons)

# Filter features
filt_low_genes <-
    colSums(mtx_neurons) %>%
    .[. > quantile(., 0.4)] %>%
    names()
mtx_neurons %<>% .[, filt_low_genes]

min_filt_vector <-
    mtx_neurons %>%
    as_tibble() %>%
    select(all_of(filt_low_genes)) %>%
    summarise(across(.fns = ~ quantile(.x, .1))) %>%
    as.list %>%
    map(as.double) %>%
    simplify %>%
    .[colnames(mtx_neurons)]

# Prepare table of intersection sets analysis
content_mtx_neuro <-
    (mtx_neurons > min_filt_vector) %>%
    as_tibble() %>%
    mutate_all(as.numeric)

Visualise intersections sets that we are going to use (highlighted)

upset(as.data.frame(content_mtx_neuro),
  order.by = "freq",
  sets.x.label = "Number of cells",
  text.scale = c(2, 1.6, 2, 1.3, 2, 3),
  nsets = 15,
  sets = c("Gad1", "Gad2", "Slc32a1", "Slc17a6"),
  queries = list(
    list(
      query = intersects,
      params = list("Gad1", "Gad2", "Slc32a1"),
      active = T
    ),
    list(
      query = intersects,
      params = list("Slc17a6"),
      active = T
    )
  ),
  nintersects = 60,
  empty.intersections = "on"
)

Version	Author	Date
263f215	Evgenii O. Tretiakov	2023-03-13

upset(as.data.frame(content_mtx_neuro),
  order.by = "freq",
  sets.x.label = "Number of cells",
  text.scale = c(2, 1.6, 2, 1.3, 2, 3),
  nsets = 15,
  sets = c("Gal", "Slc32a1", "Slc17a6"),
  queries = list(
    list(
      query = intersects,
      params = list("Gal", "Slc32a1"),
      active = T
    ),
    list(
      query = intersects,
      params = list("Gal", "Slc17a6"),
      active = T
    )
  ),
  nintersects = 60,
  empty.intersections = "on"
)

Version	Author	Date
263f215	Evgenii O. Tretiakov	2023-03-13

Make subset of stable neurons

gneurons$gaba_status <-
  content_mtx_neuro %>%
  select(Gad1, Gad2, Slc32a1) %>%
  mutate(gaba = if_all(.fns = ~ .x > 0)) %>%
  .$gaba

gneurons$gaba_expr <-
  content_mtx_neuro %>%
  select(Gad1, Gad2, Slc32a1) %>%
  mutate(gaba = if_any(.fns = ~ .x > 0)) %>%
  .$gaba

gneurons$glut_status <-
  content_mtx_neuro %>%
  select(Slc17a6) %>%
  mutate(glut = Slc17a6 > 0) %>%
  .$glut

neuro_fin <-
  subset(gneurons,
    cells = union(
      WhichCells(gneurons,
        expression = gaba_status == TRUE & glut_status == FALSE),
      WhichCells(gneurons,
        expression = glut_status == TRUE & gaba_expr == FALSE)))

Check contingency tables for neurotransmitter signature

neuro_fin@meta.data %>%
  janitor::tabyl(glut_status, gaba_status)

Make splits of neurons by neurotransmitter signature

neuro_fin$status <- neuro_fin$gaba_status %>%
  if_else(true = "GABAergic",
    false = "glutamatergic")
Idents(neuro_fin) <- "status"
SaveH5Seurat(
  object    = neuro_fin,
  filename  = here(data_dir, "neuro_fin-THP7"),
  overwrite = TRUE,
  verbose   = TRUE
)

## Split on basis of neurotrans and test for difference
neuro_fin_neurotrans <- SplitObject(neuro_fin, split.by = "status")

DotPlots grouped by orig.ident

Expression of GABA receptors in GABAergic Gal positive cells

DotPlot(object = neuro_fin_neurotrans$GABAergic,
        features = gabar,
        group.by = "orig.ident",
        cols = c("#adffff", "#0084ff"),
        col.min = -1, col.max = 1
) + RotatedAxis()

Version	Author	Date
263f215	Evgenii O. Tretiakov	2023-03-13

Expression of GABA receptors in glutamatergic Gal positive cells

DotPlot(object = neuro_fin_neurotrans$glutamatergic,
        features = gabar,
        group.by = "orig.ident",
        cols = c("#ffc2c2", "#ff3c00"),
        col.min = -1, col.max = 1
) + RotatedAxis()

Version	Author	Date
263f215	Evgenii O. Tretiakov	2023-03-13

Expression of glutamate receptors in GABAergic Gal positive cells

DotPlot(object = neuro_fin_neurotrans$GABAergic,
        features = glutr,
        group.by = "orig.ident",
        cols = c("#adffff", "#0084ff"),
        col.min = -1, col.max = 1
) + RotatedAxis()

Version	Author	Date
263f215	Evgenii O. Tretiakov	2023-03-13

Expression of glutamate receptors in glutamatergic Gal positive cells

DotPlot(object = neuro_fin_neurotrans$glutamatergic,
        features = glutr,
        group.by = "orig.ident",
        cols = c("#ffc2c2", "#ff3c00"),
        col.min = -1, col.max = 1
) + RotatedAxis()

Version	Author	Date
263f215	Evgenii O. Tretiakov	2023-03-13

DotPlots