lcolladotor

📊 Statistical Computing — Lecture 01 Summary

Main theme: Introduction to statistical computing with R, setting up the programming environment, exploring the R ecosystem, and establishing good coding practices.

The lecture emphasized practical programming, reproducible research, and making statistical computing approachable for students with different backgrounds and levels of experience.

🎓 1. Course introduction and philosophy

• 👋 Welcome to Statistical Computing! The course focuses on practical skills for analyzing, manipulating, and visualizing data using R rather than statistical theory.
• 🧠 Programming can be challenging. Learning R takes practice, and struggling with code is a normal part of developing programming skills.

lcolladotor

---
title: "Tobi Burns"
image: "tobi.jpg"
links:
  - label: LinkedIn
    url: "https://linkedin.com/"
  - label: Twitter
    url: "https://twitter.com/"
  - label: GitHub
    url: "https://github.com/"

lcolladotor

# Bad examples from https://style.tidyverse.org/syntax.html
x[,1]
x[ ,1]
x[ , 1]

# Bad
mean (x, na.rm = TRUE)
mean( x, na.rm = TRUE )

# Bad

lcolladotor

library("tidyverse")
library("here")
chocolate <- readRDS(here("data", "chocolate.RDS"))

## Base R solution
has_sugar <- sapply(
    strsplit(
        gsub(" ", "", gsub(".*-", "", chocolate$ingredients)),
        ","),
    function(x) { any(x == "S") }

lcolladotor

library("tidyverse")
library("here")
chocolate <- readRDS(here("data", "chocolate.RDS"))
glimpse(chocolate)

options(width = 120)
sessioninfo::session_info()

## After copying the above, I ran:
# reprex::reprex(wd = here::here())

lcolladotor

## R 4.3.2 bioc 3.18 test

```R
> library("recount3")
> args(recount3_cache)
function (cache_dir = getOption("recount3_cache", NULL))
NULL
> rse_data <- recount3::create_rse_manual(
+   project = "SRP045225",
+   project_home = "data_sources/sra",

lcolladotor

library("dplyr")
library("sessioninfo")

tuesdata <- tidytuesdayR::tt_load("2020-01-07")
rainfall <- tuesdata$rainfall

rainfall_filtered <- rainfall %>% 
    filter(city_name == "Cuernavaca")

rainfall_filtered

lcolladotor

x <- c("/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-04-19-latin-american-r-bioconductor-developers-workshop-2018.html:44:1",
"/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-06-11-mindfulness.html:27:1",
"/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-07-30-harrassment-diversity-in-science-and-inspiraton-from-my-grandmother.html:24:1",
"/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-09-13-r-gene-regulatory-interaction-formulator-for-inquiring-networks.html:132:1",
"/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-09-17-what-about-a-lawyer-like-app-as-the-mininum-help-for-defandants-in-immigration-cases.html:110:1",
"/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-10-16-ashg18-tweet-summary.html:21:1",
"/Users/leocollado/Dropbox/Code/lcolladotorsource/content/post/2018-09-29-why-i-applied-to-join-sni-the-mexican-national-researchers-registry.html:21:1",
"/Users/leocollado/Dropbox/Code/lcollado

lcolladotor

## Load required libraries
library("googlesheets4")
library("dplyr")
library("ggplot2")
library("plotly")
## For reproducibility
library("sessioninfo")

## Authenticate with Google
googlesheets4::gs4_auth()

lcolladotor

library('SpatialExperiment')
library('ggplot2')
library('gridExtra')
library('ggspavis')

id = 'V10B01-085_A1'
spe_path = '/dcs04/lieber/lcolladotor/spatialHPC_LIBD4035/spatial_hpc/processed-data/pilot_data_checks/spe_basic.Rdata'

################################################################################
#   Function Definitions