arraytools

$ sudo smartctl -a /dev/sdb
smartctl 7.2 2020-12-30 r5155 [x86_64-linux-5.19.0-46-generic] (local build)
Copyright (C) 2002-20, Bruce Allen, Christian Franke, www.smartmontools.org

=== START OF INFORMATION SECTION ===
Device Model:     PNY CS900 1TB SSD
Serial Number:    PNY231123031701048A6
LU WWN Device Id: 5 f8db4c 2311048a6
Firmware Version: CS900LA5
User Capacity:    1,000,204,886,016 bytes [1.00 TB]

arraytools

/* rs-theme-name: Vibrant Ink SB 2 */
/* rs-theme-is-dark: TRUE */
.ace_gutter {
  background: #1a1a1a;
  color: #BEBEBE
}
.ace_print-margin {
  width: 1px;
  background: #444;
}

arraytools

> renv::restore()

Welcome to renv!

It looks like this is your first time using renv. This is a one-time message,
briefly describing some of renv's functionality.

renv maintains a local cache of data on the filesystem, located at:

  - "~/.cache/R/renv"

arraytools

version: '3.3'
services:
    node-exporter:
        image: quay.io/prometheus/node-exporter:latest
        container_name: node_exporter
        command:
            - '--path.rootfs=/host'
        network_mode: host
        pid: host
        restart: unless-stopped

arraytools

---
title: " "
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
library(dplyr)
library(knitr)
library(kableExtra)

arraytools

KRT19	E
AGR2	E
RAB25	E
CDH1	E
ERBB3	E
FXYD3	E
SLC44A4	E
S100P	E
SCNN1A	E
GALNT3	E

arraytools

x <- readxl::read_excel("~/Downloads/EMset.xlsx")
x %>% drop_na() %>% write.table("~/Downloads/EMset.txt", quote=F, row.names = F)
x2 <- read.table("~/Downloads/EMset.txt")
dim(x2) # 218 x 2
epi <- x2[1:170, 2]
mes <- x2[171:218, 2]
x3 <- data.frame(symbol=x2[,2], epimes=c(rep("epi", 170), rep("mes", 48)))
x3[, 1] <- gsub(substr(x3[1,1], 1, 1), "", x3[,1]) # rm "white space'?
write.table(x3, file="~/Downloads/EMgenes_cellline.txt", quote=F, row.names = F, sep="\t")

arraytools

df <-
structure(list(muc6 = c(0.65991920232772827, 12.234284400939941,
7.5393352508544922, 13.921844482421875, 4.8508410453796387, 0,
6.7801151275634766, 5.5127406120300293, 1.030299186706543, 3.5845346450805664,
0.98191821575164795, 0, 0, 1.052558422088623, 0, 0, 2.5294754505157471,
0.59700602293014526, 0, 0, 7.0485143661499023, 0, 0, 0, 1.1008850336074829,
5.777961254119873, 6.1289887428283691, 0, 4.9814505577087402,
0, 5.4703717231750488, 8.0720577239990234, 0), tumortype = c("Carcinoma",
"sarcoma", "Carcinoma", "Carcinoma", "sarcoma", "sarcoma", "Carcinoma",
"Carcinoma", "sarcoma", "sarcoma", "Carcinoma", "Carcinoma",

arraytools

library(glmnet)
x <- dget(url("https://gist.githubusercontent.com/arraytools/238e812555d69cb0213adaf99353c25f/raw/911bd4c6810fff6483521808cd1dfa1833891eb7/glmnet_surv_x"))
y <- dget(url("https://gist.githubusercontent.com/arraytools/238e812555d69cb0213adaf99353c25f/raw/911bd4c6810fff6483521808cd1dfa1833891eb7/glmnet_surv_y"))
lambda <- dget(url("https://gist.githubusercontent.com/arraytools/238e812555d69cb0213adaf99353c25f/raw/911bd4c6810fff6483521808cd1dfa1833891eb7/glmnet_surv_lambda"))

cvfit <- cv.glmnet(x, y, family = "cox", nfolds=10)
fit <- glmnet(x, y, family = "cox", lambda = lambda)
coef.cv <- coef(cvfit, s = lambda)
coef.fit <- coef(fit)
length(coef.cv[coef.cv != 0]) # 31

arraytools

#include <Rembedded.h>
#include <Rdefines.h>

static void doSplinesExample();
int
main(int argc, char *argv[])
{
    Rf_initEmbeddedR(argc, argv);
    doSplinesExample();
    Rf_endEmbeddedR(0);