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:
| 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") | |
| 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") |
I hereby claim:
To claim this, I am signing this object:
| # 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 |
| ################################################################# | |
| ######################## TMHMM Parser ########################### | |
| ################################################################# | |
| # Created by: Kevin Leiss | |
| # Last Updated: 14.12.2016 | |
| # | |
| # License: Feel free to use the script, but please refer to me if | |
| # you used it for publication. | |
| # |
| def check_output(file, interval_time, logfile_path): | |
| import os | |
| import time | |
| status = os.path.isfile(file) | |
| while status is not True: | |
| f_log = open(logfile_path, 'a') | |
| f_log.write(time.asctime() + '\t' + 'Still running\n') |