I had a difficult time installing the units R package on the Partners ERIS servers.
I hope this post helps you to figure out how to work around the errors.
#' @param x A sparse matrix from the Matrix package. | |
#' @param file A filename that ends in ".gz". | |
writeMMgz <- function(x, file) { | |
mtype <- "real" | |
if (is(x, "ngCMatrix")) { | |
mtype <- "integer" | |
} | |
writeLines( | |
c( | |
sprintf("%%%%MatrixMarket matrix coordinate %s general", mtype), |
#!/usr/bin/env python | |
""" | |
The Needleman-Wunsch Algorithm | |
============================== | |
This is a dynamic programming algorithm for finding the optimal alignment of | |
two strings. | |
Example | |
------- |
# install.packages(c("Matrix", "rhdf5", "tidyverse")) | |
library(Matrix) | |
library(rhdf5) | |
library(tidyverse) | |
library(glue) | |
my_h5_files <- Sys.glob( | |
"path/to/cellranger-per-channel/output/*/filtered_feature_bc_matrix.h5" | |
) |
<!DOCTYPE html> | |
<body> | |
<!-- Copied directly from http://www.ephys.org/ by Damian J Williams --> | |
<input placeholder="Kamil Slowikowski" name="name"/> | |
<p id="demo"></p> | |
<script> |
/* | |
* The purpose of this script is to automatically click the "Send SMS" | |
* button as soon as the page is loaded, instead of clicking on it manually. | |
* | |
* This is the page with the button: | |
* | |
* https://partnershealthcare.okta.com/signin/verify/okta/sms | |
* | |
*/ |
[ | |
{ | |
"id": "1", | |
"title": "Methods for Identifying Tumor Heterogeneity and Rare Subclones in Single Cell DNA Sequence Data", | |
"text": "Background With the advancements of single cell sequencing technologies it is now possible to interrogate thousands of cells in a single experiment. Single-cell RNA-Seq has been available for several years but high-throughput single-cell DNA analysis is in its infancy. Therefore, it is essential to develop new capabilities for assessing genetic variation present in rare cells and to better understand the role that these cells play in the evolution of tumor progression. To address these challenges and enable the characterization of genetic diversity in cancer cell populations, we developed a novel approach to identify mutation signatures which define subclones present in a tumor population. Methods Here we present a two-step clustering and subclone identification method using data generated on the Tapestri single-cell DNA platform which can generate upto 10000 cells |