talks – Learning with sckinta

R-Ladies Book Club: Chapter 7 move beyond linear

Chapter 7 from ISLR2

2022-09-13 HTML slides

R-Ladies Book Club: Chapter 6 linear model selection and regularization

Chapter 6 from ISLR2

2022-08-18 HTML slides

R-Ladies Book Club: Introduction to Tidymodels

The opening talk at 2022 R-Ladies Philly Book Club

2022-07-14 HTML slides

Network analysis and visualization

R-Ladies Philly workshop on network analyses using R igraph object and visualization with ggraph package.

2019-10-08 PDF slides

All about git

Recently I have actively participated two team projects (PAWS and 2020datahack) which involves multiple team members and a lot of group decisions. For the first time, I…

Buy low sell high on big tech stocks?

I am interested in Big Tech Stock Prices since I personally hold several big Tech stocks and experienced bloody plummeting in the last year. As an amateur investor, I have…

External persistent data I/O using ShinyApp

Shiny App is a fantastic application in Rstudio and makes the data processing more accessible (and fun!). Most easy shiny apps are made to represent data based on a given…

Install multiple versions of R in MacOS

Whenever there is new release of R at CRAN, I am always tempted to install the new version so that I can use the fancy new tools. However, switch to new version of R is…

Interpreting the coefficients of Generalized Linear Model

Linear model is the most popular model used in various of fields, due to its simple execution and interpretation. It can be not only used to predict like all other machine…

ML pipeline with tidymodels vs. caret

As a DS beginner, I first came across ML in R by studying the book Hands-On Machine Learning with R. The book mainly focuses on the package caret with general introductions…

Network Analysis in R - Part 1

Network analysis, also called graph analysis, is to study the complexity of the inter-relationships between actors of all sorts and provides an architectural view of…

Network Analysis in R - Part 2

In last post, I covered the basic components of IGRAPH objects and how to manipulate IGRAPH. You may notice that most of those manipulation do not really require a IGRAPH…

Network visualization - Part 3

In the previous two posts, we discussed about IGRAPH object and how to manipulate, measure and cluster it. In this final post of network analysis series, I will focus on the…

Python Environment Manager - uv

As a computational biologist, I have relied on conda for Python package management for over a decade. This is largely because most bioinformatics packages and software are…

Taking options from command line

Taking in options from command line is an essential step towards generalized usage of scripts. However, it is a chapter I skipped in almost all language textbooks since my…

TidyTuesday: Open Psychometrics 2022Wk33

TidyTuesday 2022-08-16

TidyTuesday: predict chocolate rating with xgboost

Load required libraries

TidyTuesday: predict ultra race time

Load required libraries

Transition from dplyr to data.table

dplyr and tidyr have totally changed the way we code in R. I particularly love the pipe %>% which comes from magrittr package and makes the code easy to read and understand.…

Understanding survival analysis - part 1

I have been performing survival analysis for a while. Although I can create standard survival curves and summarize hypothesis testing tables, I have never really UNDERSTOOD i…

Use API in R and solve common errors

An API (Application Programming Interface) is an intermediary between a large dataset and the applications at user end. It provides an accessible way to request data from a…

bitBites (2026-01-01): LLM shiny, Advert of Agent, FOCUS, Scalable Perturb-seq

Inspired by Stephen Turner¹ ’s weekly recap series, I’m starting a series called bitBites to regularly review what I read and learn. This is part of my New Year’s…

bitBites (2026-01-07): R stats, LLM prompts and update, Virtual cell

R Package Development Advent Calendar 2025 by Athanasia Mo Mowinckel offers a comprehensive journey through R package development. Even with prior experience, I still…

bitBites (2026-01-14): single-cell for drug development and clinical translation, R+Python polyglot, claude code

In this week’s bitBits, I will highlight recent advances in using single-cell transcriptomics for drug prioritization and clinical translation, including frameworks like…

bitBites (2026-01-21): TMLE, Claude skills, Stack

Targeted Maximum Likelihood Estimation (TMLE) is a semiparametric causal inference method for estimating the average treatment effect (ATE). It yield consistent ATE…

bitBites (2026-01-28): Posit Recap, EcoTyper and H&E to proteomics

This week we will recap Posit summary of 2025, Claude-assisted refactoring stories, a few bioinformatics relevant new R packages, and some exciting work predicting spatial…

bitBites (2026-02-04): R AI tool tutorials, single cell research and a spatial signal correction tool

This week’s recap spans new project-based tutorials in the R AI ecosystem, reflections on how coding agents reshape learning, and recent advances in computational biology. I…

bitBites (2026-02-11): Codex demo, AlphaGenome

dplyr column recording: extension of case_when with cleaner coding.