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Search Results for: figures

Total Results Found: 103

Total Results Found: 103

Data Visualization with R: Which package to use?

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Bioinformatics

This is ultimately up to you. In general, patchwork is easier to combine nicely aligned grid style plots. cowplot seems to include greater opportunities for customization, but you could easily customize things like titles using Read More...

R Introductory Series: Complementary packages

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Bioinformatics

There are many complementary R packages related to creating publishable figures using ggplot2. Check out the packages cowplot and ggpubr . Cowplot is particularly great for providing functions that facilitate arranging multiple plots in a grid Read More...

R Introductory Series: Objectives

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Bioinformatics

To learn how to create publishable figures using the ggplot2 package in R. By the end of this lesson, learners should be able to create simple, pretty, and effective figures.

Data Visualization with R: Which package to use?

Web Page

Bioinformatics

This is ultimately up to you. In general, patchwork is easier to combine nicely aligned grid style plots. cowplot seems to include greater opportunities for customization, but you could easily customize things like titles using Read More...

R Introductory Series 2023: Complementary packages

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Bioinformatics

There are many complementary R packages related to creating publishable figures using ggplot2. Check out the packages cowplot and ggpubr . Cowplot is particularly great for providing functions that facilitate arranging multiple plots in a grid Read More...

R Introductory Series: Objectives

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Bioinformatics

Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review general Read More...

R Introductory Series 2023: Objectives

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Bioinformatics

Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review general Read More...

NIH ORS Medical Arts Branch (MAB)
Bethesda, MD

Trans NIH Facility

MAB provides visual communication solutions across all media to the entire NIH community. Our Medical Illustration section provides a complete range of biomedical visualization services, including manuscript/textbook figures, infographics, 3D modeling, animation, technical diagrams, Read More...

Introduction to Data Visualization with R (part 1)

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Bioinformatics

02/08/2024 - This lesson will introduce prominent ways to visualize data with R. The majority of the lesson will be devoted to learning how to create publishable figures using the ggplot2 package. 

Data Wrangling with R: Objectives

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Bioinformatics

Learn the ggplot2 syntax. Build a ggplot2 general template. By the end of the course, students should be able to create simple, pretty, and effective figures.

Data Visualization with R: Load the libraries

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Bioinformatics

There are multiple ways to combine figures using R. In this lesson, we will learn how to combine figures primarily with patchwork . Though, we will also learn some components of cowplot . To get started, load Read More...

Data Visualization with R: Load the libraries

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Bioinformatics

There are multiple ways to combine figures using R. In this lesson, we will learn how to combine figures using two different R packages cowplot and patchwork , beginning with cowplot . To get started, load the Read More...

Data Visualization with R: What is cowplot?

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Bioinformatics

The cowplot package provides various features that help with creating publication-quality figures, such as a set of themes, functions to align plots and arrange them into complex compound figures, and functions that make it easy Read More...

Data Visualization with R: What is cowplot?

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Bioinformatics

The cowplot package provides various features that help with creating publication-quality figures, such as a set of themes, functions to align plots and arrange them into complex compound figures, and functions that make it easy Read More...

Data Visualization with R: Objectives

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Bioinformatics

Learn how to import spreadsheet data. Learn the ggplot2 syntax. Build a ggplot2 general template. By the end of the course, students should be able to create simple, pretty, and effective figures.

Large STARS Submission Instructions

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Large STARS can be used to request supplemental funding exceeding $8,000 to offset experimental costs (e.g., core or vendor services or specialized reagents).  Applications require detailed scientific and budgetary justification and must be proposed in Read More...

R Introductory Series: Data Management

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Bioinformatics

Data organization is extremely important to reproducible science. Consider organizing your project directory in a way that facilitates reproducibility. All inputs and outputs (where possible) should be contained within the project directory, and a consistent Read More...

Microbiome Analysis with QIIME2: What is QIIME 2?

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Bioinformatics

A powerful, extensible, and decentralized microbiome analysis package with a focus on data and analysis transparency. QIIME 2 enables researchers to start an analysis with raw DNA sequence data and finish with publication-quality figures and statistical Read More...

Data Wrangling with R: Why ggplot2?

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Bioinformatics

Outside of base R plotting, one of the most popular packages used to generate graphics in R is ggplot2 , which is associated with a family of packages collectively known as the tidyverse. GGplot2 allows the Read More...

Data Visualization with R: Example journals and their figure limits:

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Bioinformatics

Journal Impact Factor Number of Figures Nature Cancer 60.72 5-8 Science 47.73 6 Cancer Cell 31.74 8 Journal of Clinical Oncology 44.54 6 JAMA Oncology 31.78 5 Cell Host and Microbe 21.02 7 Example Multi-figure panel from Zhang et al.(2022). Longitudinal single-cell RNA-seq analysis reveals stress-promoted Read More...

Data Visualization with R: Multi-figure panel

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Bioinformatics

Objectives Combine multiple plots into a single figure Learn how to use patchwork and cowplot The primary purpose of this lesson is to learn how to combine multiple figures into a single multi-panel figure using Read More...

Data Visualization with R: Objectives

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Bioinformatics

Combine multiple plots into a single figure Learn how to use aspects of cowplot and patchwork The primary purpose of this lesson is to learn how to combine multiple figures into a single multi-panel figure Read More...

Data Visualization with R: Why ggplot2?

Web Page

Bioinformatics

Outside of base R plotting, one of the most popular packages used to generate graphics in R is ggplot2 , which is associated with a family of packages collectively known as the tidyverse. GGplot2 allows the Read More...

Introduction to FlowJo Cytometry

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Bioinformatics

04/28/2021 - Register Description: This webinar offers an introduction to FlowJo, an application designed to help with data archiving, analysis, and reporting. The training begins by showing how to load samples and then outlines the steps Read More...

Software & Techniques

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Confocal

Software Image Acquisition Commercial imaging systems of LRBGE Optical Microscopy Core are controlled by acquisition software specifically designed for the appropriate microscope, such as ZEN (Zeiss confocal microscopes), Nikon Elements (Nikon), Imspector (Abberior). Custom-built HILO Read More...

R Introductory Series: Course Overview

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Bioinformatics

Course Overview Welcome to the R Introductory Series! A series of introductory lessons in R for scientists. This course will include a series of lessons for individuals new to R or with limited R experience . Read More...

R Introductory Series: R base graphics

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Bioinformatics

You do not need to load a package to visually explore data. Rather, you can use base R graphics for plotting (from the graphics package). This plotting is fairly different from ggplot2 , which is based Read More...

R Introductory Series: Introducing ggplot2

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Bioinformatics

ggplot2 is an R graphics package from the tidyverse collection. It allows the user to create informative plots quickly by using a 'grammar of graphics' implementation, which is described as "a coherent system for Read More...

R Introductory Series: The ggplot2 template

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Bioinformatics

The following represents the basic ggplot2 template: ggplot(data = ) + (mapping = aes()) We need three basic components to create a plot: the data we want to plot , geom function(s) , and mapping aesthetics . Notice the + symbol Read More...

Learning R with BTEP

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Bioinformatics

R is both a computational language and open-source environment for statistical computing and graphics. While R programming was ranked 20 th in popularity when compared with other programming languages in December 2023, it remains a favorite among Read More...

Data Wrangling with R: The ggplot2 template

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Bioinformatics

The following represents the basic ggplot2 template. ggplot(data = ) + (mapping = aes()) The only required components to begin plotting are the data we want to plot, geom function(s), and mapping aesthetics. Notice the + symbol following Read More...

Data Visualization with R: The ggplot2 template

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Bioinformatics

The following represents the basic ggplot2 template. ggplot(data = ) + (mapping = aes()) The main components include the data we want to plot, geom function(s), and mapping aesthetics. Notice the + symbol following the ggplot() function. This Read More...

Data Visualization with R: Course Overview

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Bioinformatics

Course Overview Welcome to the Data Visualization with R Series A series of lessons designed to introduce learners to the R package ggplot2 This course will include a series of lessons for scientists with beginner Read More...

Data Visualization with R: Going beyond Excel

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Bioinformatics

Excel is a great program for visualizing and manipulating small data sets. However, it isn't great for working with "big data", and resulting plots are generally not publishable. Learning R and associated Read More...

R Introductory Series 2023: Introducing ggplot2

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Bioinformatics

ggplot2 is a R graphics package from the tidyverse collection. It allows the user to create informative plots quickly by using a 'grammar of graphics' implementation, which is described as "a coherent system for Read More...

R Introductory Series 2023: R base graphics

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Bioinformatics

You do not need to load a package to visually explore data. Rather, you can use base R graphics for plotting (from the graphics package). This plotting is fairly different from ggplot2 , which is based Read More...

R Introductory Series 2023: ggplot2 Continued

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Bioinformatics

Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review Read More...

R Introductory Series 2023: Course Overview

Web Page

Bioinformatics

Course Overview Welcome to the R Introductory Series 2023 A series of introductory lessons in R for scientists. This course will include a series of lessons for individuals new to R or with limited R experience . Read More...

R Introductory Series 2023: The ggplot2 template

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Bioinformatics

The following represents the basic ggplot2 template ggplot(data = ) + (mapping = aes()) We need three basic components to create a plot: the data we want to plot, geom function(s), and mapping aesthetics. Notice the + symbol Read More...

Data Visualization with R

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Bioinformatics

04/05/2022 - Welcome to the Data Visualization with R course series ! Here, we hope to help you establish the foundations for generating publication quality plots in R. We will mostly be using ggplot2 ( https://ggplot2.tidyverse. Read More...

R Introductory Series: Introduction to R and RStudio

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Bioinformatics

Learning Objectives To understand: 1. the difference between R and RStudioIDE. 2. how to work within the RStudio environment including: creating an Rproject and Rscript navigating between directories using functions obtaining help how R can enhance data Read More...

Microbiome Analysis with QIIME2: Metadata and importing

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Bioinformatics

Lesson 2: Getting Started with QIIME2 Lesson Objectives Obtain sequence data and sample metadata Import data and metadata Discuss other useful QIIME2 features including view QIIME2, provenance tracking, and the QIIME2 forum. DNAnexus DNAnexus provides a Read More...