Cell cycling analysis of bloodstream for trypanosoma brucei

library(tidyverse)

Registered S3 methods overwritten by 'dbplyr':
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  print.tbl_lazy     
  print.tbl_sql      
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✓ readr   1.4.0     ✓ forcats 0.5.1
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PrctCellExpringGene <- function(object, genes, group.by = "all"){
  if(group.by == "all"){
    prct = unlist(lapply(genes,calc_helper, object=object))
    result = data.frame(Markers = genes, Cell_proportion = prct)
    return(result)
  }
  
  else{        
    list = SplitObject(object, group.by)
    factors = names(list)
    
    results = lapply(list, PrctCellExpringGene, genes=genes)
    for(i in 1:length(factors)){
      results[[i]]$Feature = factors[i]
    }
    combined = do.call("rbind", results)
    return(combined)
  }
}

calc_helper <- function(object,genes){
  counts = object[['RNA']]@counts
  ncells = ncol(counts)
  if(genes %in% row.names(counts)){
    sum(counts[genes,]>0)/ncells
  }else{return(NA)}
}

part one

genes_10 <- genes_10prct$Markers

Error: object 'genes_10prct' not found

PART TWO

Order slender cells with trajectory analysis

tryp_subset <- subset(tryp, subset = cluster == c("LS A", "LS B"))

longer object length is not a multiple of shorter object lengthlonger object length is not a multiple of shorter object length

tryp_subset <- subset(tryp, subset = cluster == c("LS A", "LS B"))

longer object length is not a multiple of shorter object lengthlonger object length is not a multiple of shorter object length

tryp_subset <- RunUMAP(tryp_subset, dims = 1:8, reduction = "pca", min.dist = 0.1)

12:55:33 UMAP embedding parameters a = 1.577 b = 0.8951
12:55:33 Read 996 rows and found 8 numeric columns
12:55:33 Using Annoy for neighbor search, n_neighbors = 30
12:55:33 Building Annoy index with metric = cosine, n_trees = 50
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
12:55:33 Writing NN index file to temp file /var/folders/rd/tjq29jm572b7j_j3fg5k_s340000gn/T//RtmpyjyWIo/file14b5387342dd
12:55:33 Searching Annoy index using 1 thread, search_k = 3000
12:55:33 Annoy recall = 100%
12:55:34 Commencing smooth kNN distance calibration using 1 thread
12:55:36 Initializing from normalized Laplacian + noise
12:55:36 Commencing optimization for 500 epochs, with 40024 positive edges
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
12:55:38 Optimization finished

tryp_subset <- subset(tryp, subset = cluster == c("LS A", "LS B"))

longer object length is not a multiple of shorter object lengthlonger object length is not a multiple of shorter object length

tryp_subset <- RunUMAP(tryp_subset, dims = 1:8, reduction = "pca", min.dist = 0.1)

12:55:39 UMAP embedding parameters a = 1.577 b = 0.8951
12:55:39 Read 996 rows and found 8 numeric columns
12:55:39 Using Annoy for neighbor search, n_neighbors = 30
12:55:39 Building Annoy index with metric = cosine, n_trees = 50
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
12:55:39 Writing NN index file to temp file /var/folders/rd/tjq29jm572b7j_j3fg5k_s340000gn/T//RtmpyjyWIo/file14b5172ad81f
12:55:39 Searching Annoy index using 1 thread, search_k = 3000
12:55:39 Annoy recall = 100%
12:55:40 Commencing smooth kNN distance calibration using 1 thread
12:55:42 Initializing from normalized Laplacian + noise
12:55:42 Commencing optimization for 500 epochs, with 40024 positive edges
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
12:55:45 Optimization finished

DimPlot(tryp_subset, reduction = "umap", label = FALSE,
        label.size = 4,
        pt.size = 0.5, group.by = "Phase", cols = mycolours) + UMAP_theme

Error: Insufficient values in manual scale. 5 needed but only 4 provided.
Run `rlang::last_error()` to see where the error occurred.

Trajectory inference with slingshot

lines(SlingshotDataSet(sce), col = "black", lwd = 2)

Error in plot.xy(xy.coords(x, y), type = type, ...) : 
  plot.new has not been called yet

PART THREE

Conduct peudotime analysis with the cycling cells, in my data the slender clusters

plot(rd, pch=16, col = mycolours[as.factor(tryp_subset$Phase)] ) +
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"), panel.background = element_blank(),
        plot.title = element_text(size = 10, face = "bold"), axis.text.x = element_text(size = 8), axis.title.x = element_text(size = 9), axis.title.y = element_text(size = 9), axis.text.y =  element_text(size = 8))

NULL

plot(rd, pch=16, col = mycolours[as.factor(tryp_subset$Phase)] ) + theme(panel.border = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), axis.line = element_line(colour = “black”), panel.background = element_blank(), plot.title = element_text(size = 10, face = “bold”), axis.text.x = element_text(size = 8), axis.title.x = element_text(size = 9), axis.title.y = element_text(size = 9), axis.text.y = element_text(size = 8))

lines(x=pcc\(s[order(pcc\)lambda),1], y=pcc\(s[order(pcc\)lambda),2], col=“black”, lwd=2)

gamList <- fitGAM(counts, pseudotime=pseudoT, cellWeights=cWeights, nknots=5)

  |                                                  | 0 % ~calculating  
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