rmflight

> anova_data <- structure(list(y = c(-72.8380122783358, -42.0699052900013, -13.2570336146187,
+                                    35.5231083258988, - .... [TRUNCATED] 

> # data set:
> #
> # two patients, P1 and P2
> # each patient has samples from two diseases, D1 and D2
> # each of the samples from each patient in e .... [TRUNCATED] 
, , patient = P1

rmflight

{
  "mzML": {
    "schemaLocation": "http://psi.hupo.org/ms/mzml http://psidev.info/files/ms/mzML/xsd/mzML1.1.0.xsd",
    "id": "exampleData",
    "version": "1.1.0"
  },
  "cvList": {
    "cv": [
      {
        "id": "MS",

rmflight

> library(xml2)

> mzml_file <- "test_mzml.mzML"

> doc <- read_xml(mzml_file)

> xml_find_all(doc, "//cvParam")
{xml_nodeset (0)}

> ns <- xml_ns(doc)

rmflight

library(devtools)
# install_github("wesm/feather/R")
library(feather)
library(microbenchmark)

set.seed(3-29-16)

rows <- 100000

x <- data.frame(ints = round(runif(rows, -100, 100)), stringsAsFactors = FALSE)

rmflight

If you want to know how many lines of code are in an Rmd file:

rmarkdown::render("file.Rmd", output_format = "md_document")

cat file.md | grep -c '^ \{4\}'

And then how many lines of code in .R files:

rmflight

# use case is -omics data where some samples have missing data, can
# be coded as NA or 0, but can always set 0 to NA for my use cases
# want the pairwise correlations, where each pairwise comparison
# removes NA in either of the pairs being compared
set.seed(1234)
data_matrix <- matrix(rnorm(200, 0, 1), nrow = 20)

na_locs <- sample(200, 10)

data_matrix[na_locs] <- NA

rmflight

• Download the tarball to a directory on the local hard drive (i.e. in /home)
• In the following, change RDir with the actual directory you want to install R to.

tar -xzf ****.tgz
./configure --prefix=/mlab/data/software/RDir --enable-R-shlib --with-recommended-packages=no --with-tcltk --with-cairo
make
make install

rmflight

---
title: "test document"
---

# test

this is just some simple test text to show what will happen if we ask rstudio to reflow
the text

```{r and_a_code_block}

rmflight

2016-01-05 CompGO: an R package for comparing and visualizing Gene Ontology enrichment differences between DNA binding experiments. interesting take on the problem of comparing two experiments at the annotation level, especially for ways to do it without a cutoff. would be cool to try out some of these methods integrated into categoryCompare, especially wondering if we did PCA on the log odds of subgroups of annotations, or if log odds could be used as a weighting to help find sub groups of annotations.

2016-01-06 Transcriptomic Heterogeneity in Cancer as a Consequence of Dysregulation of the Gene-Gene Interaction Network

rmflight

# function where first calls another function, that in turn calls the first,
# but does so in a way that the second is not called again. I want to test
# how many times f1 and f2 get called under different conditions

f1 <- function(use_f2 = FALSE){
  if (use_f2) {
    f2()
  }
}