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Search Results for: MITF Exons 1-13

Total Results Found: 111

Total Results Found: 111

CLIA Molecular Diagnostics Laboratory
Frederick, Maryland

Core Facility

CLIA-Certified Technologies Offered: Fragment Analysis for Micro-satellite Instability Detection, Pharmacoscan Array for Pharmacogenomics, Mutation Detection for PCR and Sanger Sequencing, DNA extraction from whole blood, saliva, FFPE tissues, buccal swabs, nails, hair, PBMCs, buffy coats, Read More...

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Bioinformatics

Love Data Week 2024 is quickly approaching! What is Love Data Week?  Love Data Week is an international week of celebrating all things data related, with an emphasis on data management, sharing, and security. Read More...

Data Wrangling with R: Introducing the SummarizedExperiment

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Bioinformatics

The SummarizedExperiment class and the inherited class RangedSummarizedExperiment are available in the R package SummarizedExperiment . SummarizedExperiment is a matrix-like container where rows represent features of interest (e.g. genes, transcripts, exons, etc.) and columns represent Read More...

Data Wrangling with R: Acknowledgments

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Bioinformatics

Some material from this lesson was either taken directly or adapted from the Intro to R and RStudio for Genomics lesson provided by datacarpentry.org . Additional content was inspired by Chapter 13, Relational Data, from R Read More...

Microbiome Analysis with QIIME2: Practice Lesson 4

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Bioinformatics

This practice lesson is associated with Lesson 4 of the Microbiome Analysis with QIIME 2. In this practice lesson, we will work on filtering our feature table and representative sequences, classify our features, and generate a phylogenetic Read More...

Data Wrangling with R: Challenge data load

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Bioinformatics

Load in a tab delimited file (file_path= "./data/WebexSession_report.txt") using read_delim() . You will need to troubleshoot the error message and modify the function arguments as needed. {{Sdet}} Solution } library ( Read More...

Introducing dplyr and the pipe (part 2)

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Bioinformatics

12/13/2023 - In this lesson, we will continue to wrangle data using dplyr, focusing on functions such as group_by(), arrange(), summarize(), and mutate().

Methods for Connecting to Data Using SAS

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Bioinformatics

09/13/2023 - Sometimes the data you need is not available in a .csv or a SAS7BDAT format, or maybe it is not available on your computer or within your organization at all. This intermediate class Read More...

Visualizing Genomic Data: Preparing Files

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Bioinformatics

03/13/2025 - This session will introduce participants to visualizing alignment results from Next Generation Sequences using the Integrative Genomics Viewer (IGV). This step is important as scientists may want to highlight results from certain genomic locations Read More...

Using SAS/STAT

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Bioinformatics

11/13/2024 - This one-hour online training will cover several easy-to-use tools for analytic situations, including PROC FREQ (chi-square tests, Fisher's exact test), PROC TTEST, and PROC NPAR1WAY. This training covers the basic guidelines for Read More...

2024 BRAIN NeuroAI Workshop

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Bioinformatics

11/12/2024 - Join us at the upcoming hybrid NIH BRAIN NeuroAI Workshop on November 12 and 13, with virtual access to in-person panels and discussions at the NIH Campus in Bethesda, MD. Artificial intelligence (AI) is reshaping technology Read More...

Introduction to R: Part 3 – Data Analysis

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Bioinformatics

09/13/2024 - This course provides an introduction to data analysis using R, focusing on conducting various statistical tests and generating commonly used statistical regression models. Participants will learn how to perform hypothesis testing, calculate descriptive statistics, Read More...

ITCR Webinar: Introduction to the Cancer Proteome Atlas

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Bioinformatics

09/13/2024 - Reverse-phase protein arrays (RPPAs) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and develop novel cancer therapies.   To facilitate community-based investigation of the large-scale protein expression data generated by Read More...

Introduction to linear mixed-effects modeling

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Bioinformatics

08/13/2024 - This session will cover the basics of linear mixed-effects modeling as a method of regression analysis for clustered data. Special emphasis will be on the ideas behind random-intercepts and random-slopes modeling, and the discussion Read More...

Data Wrangling Workshop

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Bioinformatics

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...

Zoom-In Consult for Biowulf Users

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Bioinformatics

03/13/2024 - For inquires send email to staff@hpc.nih.gov Next edition of the NIH HPC monthly Zoom-In Consults! All Biowulf users, and all those interested in using the systems, are invited to stop by Read More...

R Introductory Series: Selecting columns

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Bioinformatics

select() requires the data frame followed by the columns that we want to select or deselect as arguments. #select the gene / transcript, logFC, and FDR corrected p-value #first argument is the df followed by columns Read More...

Data Visualization in ggplot: Customizations

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Bioinformatics

02/13/2024 - This class provides an overview of options for customizing a ggplot graph. This class will focus on methods for creating small multiples, options for customizing a graph, and how to apply ggplot themes.& Read More...

Overview of Statistics Training Resources

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Bioinformatics

02/13/2024 - The first half of the session will briefly review statistics training resources available to the NCI based on feedback from previous Statistics for Lunch sessions. For the second half, we will have an open Read More...

Data Wrangling with R: Practice problems

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Bioinformatics

Which of the following will throw an error and why? 4 _ chr :1:2: unexpected input ## 1: 4_ ## ^ . 4 chr :1:3: unexpected symbol ## 1: .4chr ## ^ {{Edet}} Create the following objects; give each object an appropriate name (your best guess at what name to Read More...

Data Wrangling with R: Lesson 2: Help Session

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Bioinformatics

This is our first coding help session. We have designed some practice problems to get you acquainted with using R before beginning to wrangle in our next lesson. Practice problems Which of the following will Read More...

Data Wrangling with R: Helper functions

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Bioinformatics

We can also include helper functions such as starts_with() and ends_with() select(dexp, transcript, starts_with("log"), FDR) ## # A tibble: 15,926 × 4 ## transcript logFC logCPM FDR ## ## 1 TSPAN6 -0.390 5.06 0.00283 ## 2 DPM1 0.198 4.61 0.0770 ## 3 SCYL3 0.0292 3.48 0.844 ## 4 C1orf112 -0.124 1.47 0.682 ## 5 Read More...

Data Wrangling with R: Excluding columns

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Bioinformatics

We can select all columns, leaving out ones that do not interest us using a - sign. This is helpful if the columns to keep far outweigh those to exclude. We can similarly use the ! Read More...

Data Wrangling with R: Accessors

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Bioinformatics

As you can see from the image, there are several accessor functions to access the data from the object: assays() - access matrix-like experimental data (e.g., count data). Rows are genomic features (e.g., Read More...

Data Wrangling with R: We can reorder using select().

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Bioinformatics

For readability, let's move the transcript column to the front. #you can reorder columns and call a range of columns using select(). ex3 ## 1 TSPAN6 hg38 TRUE -0.390 5.06 32.8 0.000312 0.00283 untrt ## 2 DPM1 hg38 TRUE 0.198 4.61 6.90 0.0281 0.0770 untrt ## 3 SCYL3 hg38 Read More...

Zoom-In Consult for Biowulf Users

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Bioinformatics

12/13/2023 - For inquires send email to staff@hpc.nih.gov Meeting ID: 161 385 0213 Passcode: 179891 Next edition of the NIH HPC monthly Zoom-In Consults! All Biowulf users, and all those interested in using the systems, are invited Read More...

CREx Newsletter Archive

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:root { --primary-action: rgb(0, 0, 0) !important; --primary-action: rgb(0, 0, 0) !important; } .container { width: 1440px; max-width: 100%; } #h2 { font-size: 2.2rem; margin-left: 20px; } /* Lazy Load Styles */ .card-image { display: block; min-height: 20rem; /* layout hack */ background: #fff center center no-repeat; background-size: cover; filter: blur(3 Read More...

NCI CCR Clinical Research Correlatives Core
Bethesda, MD

Collaborative

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...

NIH Clinical Center Positron Emission Tomography (PET)
Bethesda, MD

Core Facility

Trans NIH Facility

The PET Department, CC, functions as a core facility that supports basic, translational, and clinical research using PET. It is a vertically integrated facility, with resources to produce positron-emitting radionuclides, manufacture PET radiopharmaceuticals in a Read More...

July 2021

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CREx News & Updates July 2021   Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGHLIGHTS Learn more about services from the NHLBI Read More...

CCR Collaborative Bioinformatics Resource (CCBR)
Bethesda, MD

Collaborative

The CCR Collaborative Bioinformatics Resource (CCBR) is a centrally funded resource group which provides a mechanism for CCR researchers to obtain many different types of bioinformatics assistance to further their research goals. The group has Read More...

May 2022 Newsletter

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CREx News & Updates May 2022 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Click below to learn how easy it is to navigate the CREx platform. These short videos will Read More...

Class Documents

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Bioinformatics

Most BTEP courses include detailed course materials including lesson content, additional resources, and lesson associated data. These course materials are listed here so that learners can easily return to and review concepts taught in class Read More...

BTEP Video Archive of Past Classes

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Bioinformatics

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...

R Introductory Series: Filtering by row

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Bioinformatics

Now let's filter the rows based on a condition. Let's look at only the treated samples in scaled_counts using the function filter() . filter() requires the df as the first argument followed by 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...

Data Wrangling with R: Unite and separate

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Bioinformatics

There are two additional functions from Tidyr that are very useful for organizing data: unite() and separate() . These are used to split or combine columns. For example, you may have noticed that our feature column Read More...

Data Wrangling with R: Reordering rows

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Bioinformatics

There are many steps that can be taken following subsetting (i.e., filtering by rows and columns); one of which is reordering rows. In the tidyverse, reordering rows is largely done by arrange() . Arrange will Read More...

Data Wrangling with R: Data

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Bioinformatics

Let's load in some data to work with. In this lesson, we will continue to use sample metadata, raw count data, and differential expression results from the airway RNA-Seq project. Load the data: #sample Read More...

Data Wrangling with R: Importing data

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Bioinformatics

For this lesson, we will use sample metadata and differential expression results from the airway RNA-Seq project. Let's begin by importing the data. #sample information smeta ## 1 GSM1275862 N61311 untrt untrt SRR10395… 126 SRX384345 SRS50… SAMN0242… ## 2 Read More...

Data Wrangling with R: Help Session Lesson 5

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Bioinformatics

All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only includes the columns Read More...