Kevin klprint

## app.R
library(shiny)
library(tidyverse)

if(!require(plotly)){
    install.packages("plotly")
}
if(!require(viridis)){
    install.packages("viridis")
}

## hum3d.html
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<style>body{background-color:white;}</style>
<script>(function() {
  // If window.HTMLWidgets is already defined, then use it; otherwise create a
  // new object. This allows preceding code to set options that affect the
  // initialization process (though none currently exist).
  window.HTMLWidgets = window.HTMLWidgets || {};

## sce_helper.R
library(hdf5r)
library(Matrix)
source("https://gist.githubusercontent.com/klprint/1ab4468eb3c54abcf0422dec6223b8fc/raw/b4cc33f5b4da25bcc2e678cf46b692fe67605460/single_cell_functions.R")
library(SingleCellExperiment)
library(tidyverse)
library(liger)

sce.raw.pca <- function(sce, k = 100){
  umi <- assay(sce, "umi")


## sce_functions.R
library(hdf5r)
library(Matrix)
source("https://gist.githubusercontent.com/klprint/1ab4468eb3c54abcf0422dec6223b8fc/raw/b4cc33f5b4da25bcc2e678cf46b692fe67605460/single_cell_functions.R")
library(SingleCellExperiment)
library(tidyverse)

sce.raw.pca <- function(sce, k = 100){
  umi <- assay(sce, "umi")

  cat("Getting informative genes\n")

## keybase.md

      
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                klprint
                / keybase.md
            
            
              Created
              January 31, 2020 09:41
            
          
    Keybase proof

I hereby claim:

I am klprint on github.
I am subfish (https://keybase.io/subfish) on keybase.
I have a public key ASB7mGynrtArFJP7l3XxhFVDHk4Yxr5JqkMl_9mFEjPVMwo

To claim this, I am signing this object:

  
## single_cell_functions.R
# Taken from Simon
# compute variances across column or rows for column-sparse matrices
library(Matrix)
colVars_spm <- function( spm ) {
  stopifnot( is( spm, "dgCMatrix" ) )
  ans <- sapply( seq.int(spm@Dim[2]), function(j) {
    mean <- sum( spm@x[ (spm@p[j]+1):spm@p[j+1] ] ) / spm@Dim[1]
    sum( ( spm@x[ (spm@p[j]+1):spm@p[j+1] ] - mean )^2 ) +
      mean^2 * ( spm@Dim[1] - ( spm@p[j+1] - spm@p[j] ) ) } ) / ( spm@Dim[1] - 1 )
  names(ans) <- spm@Dimnames[[2]]

## explore_seurat.R
library(rlc)
library(matrixStats)
library(biomaRt)
library(Matrix)
library(umap)

#sobj <- readRDS("make_analysis_out/SN010_E115/SN010_E115_normalized.rds")
makeENSMEBLlink <- function(geneID){
  sprintf(
    "<a href='http://www.ensembl.org/Mus_musculus/Gene/Summary?db=core;g=%s' target='_blank'>%s</a>",

## parse_10x_output.sh
#!/bin/bash

# The following script parses the 10x chromoium sparse matrix.
# It replaces the First column with the ENSEMBL gene ID and the second,
# if needed, with the cell barcode (just uncomment the second awk script).

# It needs the three 10x chromium outputs as follows:
# 1. genes.tsv
# 2. matrix.mtx
# 3. barcodes.tsv

## ChangeChmod.txt
# Sets chmod 755 for folder and all subfolders
find /opt/lampp/htdocs -type d -exec chmod 755 {} \;

# Sets chmod 655 for all files in this folder & subfolder
find /opt/lampp/htdocs -type f -exec chmod 644 {} \;

## R_Functions.R
# Analyse data using a sliding window
slideFunct <- function(data, window, step){
  total <- length(data)
  spots <- seq(from=1, to=(total-window), by=step)
  result <- vector(length = length(spots))
  for(i in 1:length(spots)){
    result[i] <- median(data[spots[i]:(spots[i]+window)])
  }
  return(result)
}
	library(shiny)
	library(tidyverse)

	if(!require(plotly)){
	install.packages("plotly")
	}
	if(!require(viridis)){
	install.packages("viridis")
	}
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8" />
	<style>body{background-color:white;}</style>
	<script>(function() {
	// If window.HTMLWidgets is already defined, then use it; otherwise create a
	// new object. This allows preceding code to set options that affect the
	// initialization process (though none currently exist).
	window.HTMLWidgets = window.HTMLWidgets \|\| {};
	library(hdf5r)
	library(Matrix)
	source("https://gist.githubusercontent.com/klprint/1ab4468eb3c54abcf0422dec6223b8fc/raw/b4cc33f5b4da25bcc2e678cf46b692fe67605460/single_cell_functions.R")
	library(SingleCellExperiment)
	library(tidyverse)
	library(liger)

	sce.raw.pca <- function(sce, k = 100){
	umi <- assay(sce, "umi")
	# Taken from Simon
	# compute variances across column or rows for column-sparse matrices
	library(Matrix)
	colVars_spm <- function( spm ) {
	stopifnot( is( spm, "dgCMatrix" ) )
	ans <- sapply( seq.int(spm@Dim[2]), function(j) {
	mean <- sum( spm@x[ (spm@p[j]+1):spm@p[j+1] ] ) / spm@Dim[1]
	sum( ( spm@x[ (spm@p[j]+1):spm@p[j+1] ] - mean )^2 ) +
	mean^2 * ( spm@Dim[1] - ( spm@p[j+1] - spm@p[j] ) ) } ) / ( spm@Dim[1] - 1 )
	names(ans) <- spm@Dimnames[[2]]
	library(rlc)
	library(matrixStats)
	library(biomaRt)
	library(Matrix)
	library(umap)

	#sobj <- readRDS("make_analysis_out/SN010_E115/SN010_E115_normalized.rds")
	makeENSMEBLlink <- function(geneID){
	sprintf(
	"<a href='http://www.ensembl.org/Mus_musculus/Gene/Summary?db=core;g=%s' target='_blank'>%s</a>",
	#!/bin/bash

	# The following script parses the 10x chromoium sparse matrix.
	# It replaces the First column with the ENSEMBL gene ID and the second,
	# if needed, with the cell barcode (just uncomment the second awk script).

	# It needs the three 10x chromium outputs as follows:
	# 1. genes.tsv
	# 2. matrix.mtx
	# 3. barcodes.tsv
	# Sets chmod 755 for folder and all subfolders
	find /opt/lampp/htdocs -type d -exec chmod 755 {} \;

	# Sets chmod 655 for all files in this folder & subfolder
	find /opt/lampp/htdocs -type f -exec chmod 644 {} \;
	# Analyse data using a sliding window
	slideFunct <- function(data, window, step){
	total <- length(data)
	spots <- seq(from=1, to=(total-window), by=step)
	result <- vector(length = length(spots))
	for(i in 1:length(spots)){
	result[i] <- median(data[spots[i]:(spots[i]+window)])
	}
	return(result)
	}