Search Results for: FACS Aria (standard) 3 lasers (405

In support of Intramural Research Program (IRP) scientists, DOHS provides training, consulting, and resources to ensure that laboratory equipment is used and maintained properly and safely. We provide expert safety and health consulting support for Read More...

Biomarker Discovery with Morphological Context:  Changing how tissue specimens are analyzed < https://youtu.be/mVhfZq8ppbc What is Digital Spatial Profiling? GeoMx Digital Spatial Profiler is a novel platform developed by NanoString. Digital Spatial Read More...

The NCI Clinical Research Correlatives Core provides non-CLIA-certified spectral flow cytometric assays to support clinical trials conducted in the CCR. The core specializes in immunophenotyping and immune monitoring assays. Established Technologies Spectral flow cytometry (Cytek), Read More...

The Antibody Characterization Laboratory (ACL) is the laboratory responsible for the development of well-characterized monoclonal antibody reagents. The NCI’s Office of Cancer Clinical Proteomics Research funds ACL as a resource to the entire cancer Read More...

Back Services: Biophysics Facility offers MP as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument training calendar.  Training includes mass distribution analysis of a Read More...

The National Cancer Institute (NCI) is developing a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), patient-derived organoids (PDOrg), and in vitro patient-derived tumor cell cultures (PDCs) and cancer-associated fibroblasts (CAFs). These Read More...

Back Services: We offer a limited sample processing service using standard SEC-MALS and FFF protocols.  This service is intended for the occasional users of this system.  Researchers who expect to use this instrument Read More...

Back Services: We offer a limited sample processing service using standard SEC-MALS and FFF protocols.  This service is intended for the occasional users of this system.  Researchers who expect to use this instrument Read More...

.row { display: flex; justify-content: space-around; align-items: flex-start; margin: 20px; } .column { text-align: center; padding: 10px; width: 30%; } .column img { display: block; margin: 0 auto; width: 150px; height: 150px; } .column strong { display: block; margin-top: 10px; } Background: Intravital microscopy (IVM) Read More...

Back Services: Biophysics Facility offers Octet as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar.  Training includes a full analysis of a Read More...

The NCI Genomic Data Commons (GDC) was established by the NCI Center for Cancer Genomics (CCG) to support the receipt, harmonization, distribution, and analysis of genomic and clinical data from cancer research programs. The GDC Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New CREx User Survey The CREx Team is carrying out a CREx User Survey. If you haven’t Read More...

Back Services: Biophysics Facility offers MST as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar.  Training includes the KD determination of a Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Research Festival The NIH Research Festival highlights the groundbreaking science and the vibrant NIH community driving our Read More...

NCI LASP Animal Research Technology Support (ARTS) provides customized technical support for basic and translational animal-based research to the scientific community. We offer a wide array of services ranging from expert colony management to the Read More...

The centrally funded Statistics team within the Advanced Biomedical Computational Science group at the Frederick National Lab provides statistical consultation and data analysis support for NCI laboratories. We have broad-range expertise in biomedically relevant areas Read More...

Back Services: Biophysics Facility offers fluorometers as open-access instruments.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3226 Description: Some substances reemit light after Read More...

Back Services: This instrument is not user accessible.  We provide both data collection and data analysis services. Location: Building 50, room 3331 Description: An analytical ultracentrifuge is equipped with absorption and interference optical systems that monitor Read More...

The Clinical Image Processing Service (CIPS) offers timely and accurate advanced image processing of diagnostic radiology images for clinical care, research, and training. CIPS’ functions include clinical services and scientific researches. Established Technologies CIPS can Read More...

Back Services: Biophysics Facility offers MDS as an open-access instrument. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Training includes the KD determination of a standard molecular Read More...

Back Services: Biophysics Facility offers ITC calorimeters as open-access instruments.  First-time users must complete a short training session before gaining access to the instrument reservation calendar.  Training includes performing a test experiment and Read More...

Supplemental Technology Award Review System (STARS) Overview STARS Request Form STARS System The Supplemental Technology Award Review System (STARS) is a web-based interface for submission and review of S&S supplement requests by CCR Read More...

Back Services: Biophysics Facility offers DLS as an open-access instrument. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Training includes DLS analysis of small- and large-molecular size Read More...

Services: Biophysics Facility offers CD as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the difference Read More...

Back Services: Biophysics Facility offers CD as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the Read More...

Home About the Biophysics Core Biophysics Core Services [tabby title="Instrumentation"] NHLBI Biophysics Core The Biophysics Core Facility: Overview Core Facilities provide scientific resources, cutting-edge technologies and novel approaches to support DIR scientists. Availability of Read More...

[tabby title="Home"] About NICE-NIH Intramural CryoEM Consortium  NIH Intramural CryoEM Consortium (NICE) serves intramural investigators in all NIH IC’s. NICE provides access to state-of-the-art Titan Krios cryo-electron microscopes for atomic-resolution structure determination of Read More...

Output that you would expect to appear in the terminal (e.g., standard error and standard output) will not in batch mode. Rather, these will be written by default to slurm######.out in the submitting Read More...

05/14/2024 - This presentation will explain the difference between the mean and standard deviation of a set of values and the standard error of the mean. The parameters involved in comparing two normally distributed populations relative Read More...

This tutorial was designed to demonstrate common secondary analysis steps in a scRNA-Seq workflow. We will start with a merged Seurat Object with multiple data layers representing multiple samples. Throughout this tutorial we will Apply Read More...

This tutorial has been designed to demonstrate common secondary analysis steps in a scRNA-Seq workflow. We will start with a merged Seurat Object with multiple data layers representing multiple samples that have already been filtered Read More...

05/01/2024 - This lesson reviews many of the standard steps in a scRNA-Seq workflow: QC filtering, normalization, scaling, and clustering. 

11/13/2024 - The National Library of Medicine (NLM) Division of Intramural Research (DIR) is pleased to welcome Manisha Desai, PhD, Section Chief of Biostatistics and Director of the Quantitative Sciences Unit at Stanford University School of Read More...

06/11/2024 - This talk will cover the basics of statistical resampling methods such as bootstrap, Monte Carlo, and permutations for estimating parameters and testing hypotheses. &nbsp;We will discuss when you might want to use Read More...

Integration is the process of aligning the same cell types across samples, treatments, data sets, batches, etc. Clustering should represent biological differences and not technical artifacts. Integration is not always necessary. You should run through Read More...

If you plan to use RStudio to interactively analyze your data, RStudio Server, a browser-based interface very similar to the standard RStudio desktop environment, is the best option to avoid issues with lag. Each RStudio Read More...

It is next standard to scale and center the features in the data set prior to dimension reduction or visualization via heatmap. Scaling the data will keep highly expressed genes from dominating our analysis. This Read More...

The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . We are going to use the filtlowabund_scaledcounts_airways.txt file Read More...

Lesson 2 Exercise Questions: Part 1 (BaseR subsetting and Factors) The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . We are going Read More...

To apply some function to smaller subsets (groups) within your data, and return a summarized data frame, use group_by() with summarize() . group_by() - group a data frame by a categorical variable so that Read More...

Who says Unix programmers don't have a sense of humor? Let me introduce cat , head , and tail . The cat command (short for "concatenate") is an extremely useful command for creating new files Read More...

Functional enrichment and comparison with R . ClusterProfiler, pathview, and good introductory information Article on the impact of the evolving GO Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges, PLOS Computation Biology, 2012 Pathway enrichment Read More...

As with any language, the learning curve for Unix can be quite steep. However, to get started analyzing data you really need to understand the following: Directory navigation: what the directory tree is, how to Read More...

As with any language, the learning curve for Unix can be quite steap. However, to get started analyzing data you really need to understand the following: Directory navigation: what the directory tree is, how to Read More...

Before jumping into submitting scripts in job files, let's first focus on how to run R from the command line. The primary way to run R from the command line is to call Rscript . Read More...

As with any language, the learning curve for Unix can be quite steep. However, to work on Biowulf you really need to understand the following: Directory navigation: what the directory tree is, how to navigate Read More...

To work on Biowulf you really need to understand the following: Directory navigation: what the directory tree is, how to navigate and move around with cd Absolute and relative paths: how to access files located Read More...

Some use bar plots to illustrate mean plus / minus standard deviation in the data, so let's take a moment to learn how to incorporate error bars in our data. We will learn to do Read More...

Often, we will use bar plots to illustrate mean plus minus standard deviation in our data so we should learn how to incorporate error bars in our plots. We will learn to do this using Read More...

It is common to obtain summary statistics for a dataset to understand parameters like mean, standard deviation, and distribution. In this lesson, we will learn to generate plots that will help with visualization of summary Read More...

In this lesson we will use data obtained from a study that examined the effect that dietary supplements at various doses have on guinea pig tooth length. This data set is built into R, so Read More...

We can use the function prcomp() to run PCA on the first four columns of the iris data. The function takes numeric data. colnames(iris)[1:4] ## [1] "Sepal.Length" "Sepal.Width" "Petal. Read More...

04/16/2025 - Updated Location: ATRF, Frederick MD, Main Auditorium What to bring: &nbsp;Laptop capable of connecting to internet via NIH wifi For questions or to register, please contact Amy Stonelake ( amy.stonelake@nih.gov ) Read More...

04/15/2025 - What to bring: &nbsp;Laptop capable of connecting to internet via NIH&nbsp; wifi Are you looking to expand the reach of your sequencing to enable what long read technologies can provide?& Read More...

01/16/2025 - This two-hour&nbsp; online &nbsp;workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the& Read More...

10/09/2024 - This 1.5 hour  online  workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the  tidyverse  ecosystem. There will be Read More...

08/13/2024 - NCI staff are welcome to register for an upcoming Childhood Cancer Data Initiative (CCDI) webinar titled, "CCDI Federated Data: Enhancing Data Discoverability," where you can learn about one of the newest advancements Read More...

07/11/2024 - Please join us for this special event featuring three speakers on the topic of Single-Cell Spatial Transcriptomics. George Zaki, Ph.D., Director, Applied Scientific Computing, BACS, The Frederick National Lab for Cancer Research, NCI/ Read More...

07/08/2024 - This two-hour&nbsp; in-person &nbsp;workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the& Read More...

The total number of detected transcripts expressed in a cell is dependent on the amount of mRNA in a cell. Cells naturally vary in the total amount of mRNA expressed. However, the chemistry of the Read More...

To look at how these metrics correlate, we can use FeatureScatter() , which can be used to visualize feature-feature relationships and also be applied to other data stored in our Seurat object (e.g., metadata columns, Read More...

05/13/2024 - This in-person workshop will focus on data wrangling using tidy data principles. Tidy data describes a standard way of storing data that facilitates analysis and visualization within the  tidyverse  ecosystem. There will be a Read More...

05/08/2024 - If you&rsquo;re a researcher, clinician, informaticist, commercial partner, or policy maker interested in cancer&nbsp; data science , register to attend this Cancer Data Exchange Summit. You&rsquo;ll have Read More...

The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...

Lesson 2 Exercise Questions: Part 2 (Tidyverse) The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside Read More...

The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . We are going to use the filtlowabund_scaledcounts_airways.txt file Read More...

Lesson 3 Exercise Questions: BaseR dataframe manipulation and factors The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . We are going Read More...

Bioconductor packages are divided into four types: software annotation data experiment data workflows. Software packages themselves can be subdivided into packages that provide infrastructure (i.e., classes) to store and access data, and packages that Read More...

The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...

Lesson 5 Exercise Questions: Tidyverse The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of Read More...

The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of class here . The diffexp_ Read More...

We will use qiime cutadapt trim-paired because we are working with paired-end reads. We will also use more than one thread ( --p-cores ). The region sequenced was V4-V5 with the forward primer, AYTGGGYDTAAAGNG , and the Read More...

What if we want to transform all of our counts spread across multiple columns in acount using scale() , which applies a z-score transformation? In this case we use across() within mutate() , which has replaced the Read More...

There are several functions that you will see repeatedly as you use R more and more. One of those is c() , which is used to combine its arguments to form a vector. Vectors are probably Read More...

This page contains content directly from the Biostar Handbook by Istvan Albert. Always remember to activate your bioinformatics environment. conda activate bioinfo What is a sequence pattern? A sequence pattern is a sequence of bases Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Remember to activate the bioinfo environment. conda activate bioinfo Then create a new directory for files we will be working with today in Read More...

STAR 2-pass mode --sjdbGTFfile is the path to the file with annotated transcripts in standard GTF format, STAR extracts splice junctions from this file, improves accuracy of mapping. Using annotations is highly recommended whenever they Read More...

Let's start our exploration of sequencing read alignment by discussing the reference genome for human chromosome 22. For this, change into our ~/biostar_class/hbr_uhr/refs folder. In Lesson 9, we discussed why we need Read More...

Let's start our exploration of sequencing read alignment by discussing the reference genome for human chromosome 22. For this, change into our ~/biostar_class/hbr_uhr/refs folder. In Lesson 9, we discussed why we need Read More...

Lesson 5: Working on Biowulf Lesson 4 Review Flags and command options Wildcards ( * ) Tab complete Accessing user history with the "up" and "down" arrows cat , head , and tail Working with file content (input, Read More...

08/03/2023 - Identification of evolutionarily related DNA or protein sequences (homologs) is a crucial step in many biology workflows. For example, homologous sequences are used to infer relationships between organisms, understand how sequence changes affect observable Read More...

In this section we will learn how to construct bar plots using data obtained from a study that examined the effect that dietary supplements at various doses have on guinea pig tooth length. This data Read More...

Prior to sending our data into the heatmap generating algorithm, it is a good idea to sacle. There are several reasons for doing this Variables in the data might not have the same units, thus Read More...

Prior to sending our data into the heatmap generating algorithm, it is a good idea to sacle. There are several reasons for doing this Variables in the data might not have the same units, thus Read More...

To plot the first two axes of variation along with species information, we will need to make a data frame with this information. The axes are in pca$x . #Build a data frame pcaData

Scaling is important during cluster analysis because it reduces the influence that variables with high magnitude values will have on distance. (https://medium.com/analytics-vidhya/why-is-scaling-required-in-knn-and-k-means-8129e4d88ed7). A common method for scaling is Read More...

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...

nf-core is a community effort to generate a curated set of standardized, best-practice, reproducible, documented, NGS analysis pipelines. All these workflows are built using the versatile workflow manager, Nextflow , and have been released under the Read More...

Listed below are the video recordings of past BTEP events (classes, seminars, workshops). Videos are hosted on various servers and may play slightly differently. Some videos may be downloaded for local viewing. Recorded Videos of Read More...

Clustering is used to group cells by similar transcriptomic profiles. Seurat uses a graph based clustering method. You can read more about it here . The first step is to compute the nearest neighbors of each Read More...

Learning Objectives This tutorial was designed to demonstrate common secondary analysis steps in a scRNA-Seq workflow. We will start with a merged Seurat Object with multiple data layers representing multiple samples. Throughout this tutorial we Read More...

1. Introduction and Learning Objectives This tutorial has been designed to demonstrate common secondary analysis steps in a scRNA-Seq workflow. We will start with a merged Seurat Object with multiple data layers representing multiple samples that Read More...

This lesson provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat. Learning Objectives Learn about options for analyzing your scRNA-Seq data. Learn about resources for learning R programming. Learn Read More...

Lesson 4 Exercise Questions: Tidyverse The filtlowabund_scaledcounts_airways.txt includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here . You can obtain the data outside of Read More...

Objectives To explore Bioconductor, a repository for R packages related to biological data analysis. To learn about options for report generation with R: RMarkdown and Quarto. Introducing Bioconductor Bioconductor is both an open source project Read More...

Lesson 3: Creating a feature table Lesson Objectives Check for primers Generate an ASV count table and representative sequence file Understand the difference between OTU picking and denoising The two primary files that will be used Read More...

Objectives Review important data wrangling functions Put our wrangling skills to use on a realistic RNA-Seq data set Data Wrangling Review Important functions by topic Importing / Exporting Data Importing and exporting data into the R Read More...

R Crash Course: A few things to know before diving into wrangling Learning the Basics Objectives 1. Learn about R objects 3. Learn how to recognize and use R functions 4. Learn about data types and accessors Console Read More...

dplyr : joining, tranforming, and summarizing data frames Objectives Today we will continue to wrangle data using the tidyverse package, dplyr . We will learn: how to join data frames using dplyr how to transform and create Read More...

More useful Unix Flags and command options - making programs do what they do Use of wildcards Using tab complete for less typing Access your history with the "up" and "down" Read More...

More useful Unix Flags and command options - making programs do what they do Use of wildcards Using tab complete for less typing Access your history with the "up" and "down" Read More...

More useful Unix Flags and command options - making programs do what they do Use of wildcards Using tab complete for less typing Access your history with the "up" and "down" Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Lesson 4: Useful Unix For this lesson, you will need to login to the GOLD environment on DNAnexus. Lesson 3 Review Biowulf is the high performance computing cluster at NIH. When you apply for a Biowulf account Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Prior to differential expression analysis, we need to generate a design.csv file that contains the samples and their corresponding treatment conditions. Note that csv stands for comma separated value so the columns in these Read More...

Lesson 1: Introduction to Unix and the Shell Lesson Objectives Review the course syllabus and general structure of lessons to come. Introduce Unix and describe how it differs from other operating systems. Introduce and get set Read More...

Below, you will find questions and answers brought up in the course polls for the BTEP Bioinformatics for Beginners course series that took place from September 13th, 2022 to December 13th, 2022. Question 1 : Normalization - when to Read More...

BTEP Bioinformatics for Beginners (September 13th, 2022 - December 13th, 2022) Questions and Answers Below, you will find questions and answers brought up in the course polls for the BTEP Bioinformatics for Beginners course series that took Read More...

How to download data from the Sequence Read Archive (NCBI/SRA) to your account on NIH HPC Biowulf You will need: active, unlocked Biowulf account (hpc.nih.gov) active Globus account for transferring files OR Read More...

Gene ontology and pathway analysis Objectives Determine potential next steps following differential expression analysis. Tour geneontology.org and understand the three main ontologies. Learn about different methods and tools related to functional enrichment and pathway Read More...

Lesson 1: Introduction to Unix and the Shell Lesson Objectives Course overview. Introduce Unix and describe how it differs from other operating systems. Introduce and get set up on DNAnexus and the GOLD system. Discuss ways Read More...

Lesson 15: Finding differentially expressed genes Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 14 review In the previous lesson, we learned to visualize RNA sequencing alignment results in the Integrative Read More...

This page contains content taken directly from the Biostar Handbook (Istvan Albert). Always remember to activate the class bioinformatics environment. conda activate bioinfo For this data analysis, we will be using: Two commercially available RNA Read More...

This page contains content taken directly from the Biostar Handbook (Istvan Albert). Always remember to activate the class bioinformatics environment. conda activate bioinfo For this data analysis, we will be using: Two commercially available RNA Read More...

Lesson 13: Aligning raw sequences to reference genome Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 11 Review In Lesson 11 we learned to aggregate multiple FASTQC reports into one using MultiQC, Read More...

Lesson 13: Aligning raw sequences to reference genome Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 11 Review In Lesson 11 we learned to aggregate multiple FASTQC reports into one using MultiQC, Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Obtain RNA-seq test data. The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . Read More...

Lesson 4: Submitting R Scripts via command line Learning Objectives Learn how to use R with less interaction Learn how to deploy sbatch R jobs, and learn about alternatives such as swarm . Learn about R job Read More...

Lesson 1: Introduction to Biowulf, Unix, and R Learning Objectives Learn about why you may want to use R on Biowulf. Refresh Unix and R skills. This lesson will not be hands on. Why use R Read More...

Learning Objectives Understand the components of an HPC system. How does this compare to your local desktop? Learn about Biowulf, the NIH HPC cluster. Learn about the command line interface and resources for learning. What Read More...

Stat Transformations: Bar plots, box plots, and histograms Objectives Review the grammar of graphics template Learn about the statistical transformations inherent to geoms Review data types Create bar plots, box & whisker plots, and histograms. Read More...

/* Whole document: */ body{ font-family: Times; font-size: 16pt; } Stat Transformations: Bar plots, box plots, and histograms Objectives Review the grammar of graphics template Learn about the statistical transformations inherent to geoms Review data types Create bar Read More...

Scatter plots and plot customization Objectives Learn to customize your ggplot with labels, axes, text annotations, and themes. Learn how to make and modify scatter plots to make fairly different overall plot representations. Load a Read More...

Visualizing clusters with heatmaps Objectives Introduce the heatmap and dendrogram as tools for visualizing clusters in data. Learn to construct cluster heatmap using the package pheatmap . Learn how to save a non-ggplot2 plot. Introduce ggplotify Read More...