Anaconda (https://www.anaconda.com/) is a distribution of R and Python that can be used to easily install many popular data science, biostats, and other packages. This Hoffman2 Happy Hour will go discus using Anaconda on Hoffman2. This can be applied to using Anaconda on various other HPC resources. We will go over creating conda environments and…
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R
R Graphics: Introduction to ggplot2
This seminar teaches the “grammar” of graphics that underlies the ggplot2 package, allowing the user to build eye-catching, publication-quality graphics layer-by-layer. We cover the basic elements of the grammar of graphics, including aesthetics, geoms, scales, and themes, and we will show you how easy ggplot2 makes it to integrate these elements to make informative and…
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Introduction to Survival Analysis in R
Survival analysis models time-to-event outcomes. This workshop introduces usage of the survival package in R for some of the most commonly used survival methods. Topics include data setup, Kaplan-Meier estimates and curves, log-rank tests, fitting the Cox proportional hazards model, assessing the proportional hazards assumption, and modeling time-varying covariates. Experience in both survival analysis and…
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Hoffman2 Happy Hour: Loading and unloading applications via environmental modules (R, anaconda, etc. examples) + Q&A
The Hoffman2 Happy Hours are designed to showcase one cluster related topic in a short presentation (no more than 20 minutes and generally much less) or lightning talk format, to be followed by 30 to 40 minutes of discussion and user support (office hour style). Each Hoffman2 Happy Hour meeting is 50 minutes long. Bring…
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Using Container on HPC resources
This workshop will go over how to use container on HPC resources. Containers are a great way to run scientific software on various HPC platforms. Users can create a ‘virtual’ OS to easily install any application and transfer it to any system with container software. This workshop will cover how to build and use containers…
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Introduction to Generalized Linear Regression Models in R
Registration: https://ucla.zoom.us/meeting/register/tJUud-6uqTwiGtNZEtt6vy5VApsl6AE8BJVM In this workshop we discuss generalized linear models and why and when we need to use them. We will discuss several generalized linear modes such as logistic, Poisson, and negative binomial and how we run them in R. The seminar briefly reviews regression concepts as necessary, but it is assumed that participants have…
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Running Applications on the Hoffman2 Cluster, Part II
Registration link: https://ucla.zoom.us/meeting/register/tJIvd-igpjMiGNVkod90GFNhBTuT7pwRfj5- The Hoffman2 Cluster is a powerful computational resource for the UCLA research community. This workshop is part of a three-seminar series designed to introduce users to the Hoffman2 Cluster environment and to clarify the process of porting applications or using applications already available on the cluster. It also addresses how to port…
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R Markdown Basics
Registration: https://ucla.zoom.us/meeting/register/tJwpd-uoqDIvG91UKYByaA-7Xcbn4V38rA1k R Markdown files integrate text, Markdown, and R code into dynamic documents that weave together plain text, formatted text, and the output of the R code. The resulting dynamic reports can be produced in many formats, including HTML documents, HTML slideshows, LaTeX pdf, Beamer slideshows, MS Word doc, books, scientific articles, and websites. …
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Generalized Linear Models in R
This workshop is designed to give an overview on generalized linear models. The workshop introduces the basic theory of generalized linear models and their implementation in R. We will talk about a broad range of regression models such as Logistic regression, Poisson regression, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial and how to run…
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Confirmatory Factor Analysis (CFA) in R with lavaan
Zoom registration required: https://ucla.zoom.us/meeting/register/tJwkcuiqrjovGdFdq0u6EebmpiiX_KW00ohH This workshop will cover basic concepts of confirmatory factor analysis by introducing the CFA model and looking at examples of a one-factor, two-factor and second-order CFA. Concepts such as model identification, standardized solutions, and model fit statistics such as the chi-square statistic, CFI, TLI and RMSEA will be covered. The focus…
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