kieranrcampbell

## If you get the error
## > Error in `.rowNamesDF<-`(x, value = value) : invalid 'row.names' length
## after  singleCellTK::runSeuratPCA(sce)
## then run

sce@metadata$seurat <- NULL

kieranrcampbell

## Going to take non tumour cells as just fibroblast and T/NK
## as these are (i) abundant, and (ii) sufficiently distinct transcriptionally
## from tumour that we're unlikely to confuse them
non_tumour_cells <- c("Fibroblast", "T/NK")

get_baf_df <- function(sce) {
  message(paste0("[Running] Sample ", sce$id[1]))
  colnames(sce) <- paste0(colData(sce)$id, "-", colData(sce)$barcode)
  sce$cell_type <- cell_annots[colnames(sce)]
  

kieranrcampbell

## Can't remember where this comes from unfortunately
def gaussian_kernel(a, b):
    dim1_1, dim1_2 = a.shape[0], b.shape[0]
    depth = a.shape[1]
    a = a.view(dim1_1, 1, depth)
    b = b.view(1, dim1_2, depth)
    a_core = a.expand(dim1_1, dim1_2, depth)
    b_core = b.expand(dim1_1, dim1_2, depth)
    numerator = (a_core - b_core).pow(2).mean(2)/depth
    return torch.exp(-numerator)

kieranrcampbell

def expand_mask_by_one(m):
    """Takes a cell mask np array as input
    and returns with mask expanded by 1
    """
    from skimage.morphology import dilation 
    m2 = m.copy()
    unique_cell_ids = np.sort(np.unique(m.reshape(-1)))
    unique_cell_ids = unique_cell_ids[unique_cell_ids>0]
    
    for cell_id in unique_cell_ids:

kieranrcampbell

Sys.setenv('R_REMOTES_NO_ERRORS_FROM_WARNINGS' = 'true'); devtools::install_github('...')

kieranrcampbell

#' Sort the results of a gsva() call so that the
#' pathway activation always correlates positively
#' on average with the gene set listed
#' @param g Result of call to gsva() (pathway x cell)
#' @param genesets List of genes corresponding to genesets of g
#' @param sce A SingleCellExperiment with a logcounts assay
fix_gsva_direction <- function(g, genesets, sce) {
  stopifnot(nrow(g) == length(genesets))
  
  genesets <- lapply(genesets, intersect, rownames(sce))

kieranrcampbell

seurat_cluster <- function(sce,
                           resolution = 0.8,
                           dims = 1:10,
                           reduction = "mnn",
                           algorithm = 1,
                           return_SCE = TRUE) {

  seu <- as.Seurat(sce, counts = "counts", data = "logcounts")
  seu <- FindNeighbors(seu, dims = dims, reduction = reduction)
  seu <- FindClusters(seu, resolution = resolution, algorithm = algorithm)

kieranrcampbell

javascript:(     function(){         f='http://myaccess.library.utoronto.ca/login?url='+window.location.href;         if(!window.open(f))             location.href=f;     } )()

kieranrcampbell

suppressPackageStartupMessages({
  library(tidyverse)
  library(SingleCellExperiment)
  library(argparser)
})

select <- dplyr::select
mutate <- dplyr::mutate
arrange <- dplyr::arrange
rename <- dplyr::rename

kieranrcampbell

 +
  theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))