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
10/16/2024 - 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...
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Bioinformatics
Lesson 16: RNA sequencing review and classification based analysis Before getting started, remember to be signed on to the DNAnexus GOLD environment. Review In the previous classes, we learned about the steps involved in RNA sequencing Read More...
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Bioinformatics
Lesson 16 Practice Objectives In this lesson, we learned about the classification based approach for RNA sequencing analysis. In this approach, we are aligning our raw sequencing reads to a reference transcriptome rather than a genome. Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Learning objectives: 1. Understand what a sequence alignment is and how different algorithms can effect alignments. 2. Learn how scoring matrices and gap penalties (gap Read More...
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Bioinformatics
Before getting started, remember to be signed on to the DNAnexus GOLD environment.
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Bioinformatics
While we can always download reference genomes and reference transcriptomes from repositories such as NCBI or Ensembl, we will use gffread to create one from the chromosome 22 genome (22.fa) that we have used when analyzing Read More...
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Bioinformatics
In comma separated files the columns are separated by commas and the rows are separated by new lines. To read comma separated files, we can use the specific functions ?read.csv() and ?read_csv() . Let' Read More...
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Bioinformatics
The majority of mRNA derived from eukaryotes is the result of splicing together discontinuous exons, and this creates specific challenges for the alignment of RNASEQ data.
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Bioinformatics
get an interactive node sinteractive --cpus-per-task=12 --mem=30g --gres=lscratch:20 module load STAR mkdir -p bam/rnaseq_STAR GENOME=/fdb/STAR_current/UCSC/mm10/genes-100 and run STAR. STAR --runThreadN 12 --genomeDir $GENOME --sjdbOverhang 100 --readFilesIn filename. Read More...
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Bioinformatics
One of the challenges in analyzing high throughput sequencing is to reconstruct the genome of the unknown by using a knonw (ie. reference). The next step in analysis is to align our sequencing data to Read More...
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Bioinformatics
10/16/2024 - In this webinar, attendees will learn to call MATLAB from Python and to call Python libraries from MATLAB. In addition, they will learn how to use MATLAB’s Python integration to improve the compatibility Read More...
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Bioinformatics
10/16/2024 - The CRDC will celebrate its 10th anniversary with this one-and-a-half-day event highlighting its accomplishments and looking ahead to exciting initiatives. We are planning many informative sessions and report-outs on new work, including our AI Read More...
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Bioinformatics
02/16/2024 - This one-hour training will provide detailed information and demonstrations on how to manage data in Excel. By the end of this course, the participants will recognize how to filter data by text, numbers, and Read More...
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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...
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Bioinformatics
We can access a column of our data frame using [] , [[]] , or using the $ . We can use colnames() and rownames() to access the column names and row names of a data frame. For example: df[[" Read More...
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Bioinformatics
-c -f 4 is counting alignments with the property/condition (-c) that the reads are unmapped (unaligned). Now we can reverse the flag (from -f to -F) and view the number of alignments. samtools view -c Read More...
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Bioinformatics
-c -f 4 is counting alignments with the property/condition (-c) that the reads are unmapped (unaligned). Now we can reverse the flag (from -f to -F) and view the number of alignments. samtools view -c Read More...
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Bioinformatics
One of the things we will be doing quite often is to visualize genomics data using some sort of genome browser. In this course series, we will use a popular one called Integrative Genome Viewer( Read More...
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Bioinformatics
One of the things we will be doing quite often is to visualize genomics data using some sort of genome browser. In this course series, we will use a popular one called Integrative Genome Viewer( Read More...
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Bioinformatics
In this portion of the class, it is very important that you have IGV already opened on your computer. See Figure 1 and Figure 2 on how to load the relevant alignment outputs for HBR_1 and UHR_1 Read More...
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Bioinformatics
Why do we need a reference genome? {{Sdet}} Solution{{Esum}} The reference genome serves as a "known" that guides us in constructing the genome of the unknown from sequencing data. {{Edet}} What file Read More...
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Bioinformatics
For visualizing the HBR and UHR alignment results, we will use the built in Human hg38 genome. To do this, we will just goto the genome selection box and select hg38 (Figure 2). In Figure 3, we Read More...
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Bioinformatics
This lesson will serve as comprehensive review of Module 2. We will spend roughly the first hour reviewing the Module 2 material the second hour answering specific questions from the poll in Lesson 16 and other questions you Read More...
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Bioinformatics
Now that we have downloaded the HBR and UHR dataset and know where analysis tools are, let's start learning about RNA sequencing, by first learning about our reference genome and annotation files. Let's Read More...
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Bioinformatics
Now that we have downloaded the HBR and UHR dataset and know where analysis tools are, let's start learning about RNA sequencing, by first learning about our reference genome and annotation files. Let's Read More...
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Bioinformatics
Let's align an RNA-Seq sample using the "splice aware" aligner hisat2. First we will need to create the indices. Use this format: hisat2-build REFERENCE_GENOME INDEX_PREFIX Like this: hisat2-build Read More...
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Bioinformatics
Let's align an RNA-Seq sample using the "splice aware" aligner hisat2. First we will need to create the indices. Use this format: hisat2-build REFERENCE_GENOME INDEX_PREFIX Like this: hisat2-build Read More...
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Bioinformatics
Let's align an RNA-Seq sample using the "splice aware" aligner hisat2. First we will need to create the indices. Use this format: hisat2-build REFERENCE_GENOME INDEX_PREFIX Like this: hisat2-build Read More...
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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...
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CREx News & Updates June 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...
Frederick, MD
Core Facility
Clinical Support Laboratory – Flow Cytometry Section is a laboratory specializing in providing immunophenotyping support of NCI intramural clinical trials, though assessments may also be performed using cells from Non-human primates and other species. The CSL Read More...
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CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Technology Event Biophysical Methods for Protein Interactions Monday, May 15 – Friday, May 19, 2023 This workshop will review the strategies of Read More...
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...
Frederick, MD
Collaborative
The Biopharmaceutical Development Program (BDP) provides resources for the development of investigational biological agents. The BDP supports feasibility through development and Phase I/II cGMP manufacturing plus regulatory documentation.The BDP was established in 1993. We Read More...
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Bioinformatics
07/16/2025 - All Biowulf users, and all those interested in using the systems, are invited to call in to our Virtual Walk-in Consult to discuss problems and concerns, from scripting problems to node allocation, to strategies Read More...
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Bioinformatics
06/16/2025 - In 2017, Dr. Rol joined the World Health Organization' International Agency for Re earch on Cancer (IARC-WHO), motivated to improve equal acce to high-quality healthcare for everyone. Currently, he lead an IARC team dedicated to Read More...
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Bioinformatics
05/16/2025 - This one-day in-person NIH AI Symposium will bring together researchers from a broad range of disciplines to share their AI-related research, with the goal of disseminating the newest AI research, providing an opportunity to Read More...
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Bioinformatics
04/16/2025 - Please email staff@hpc.nih.gov for the meeting link. All Biowulf users, and all those interested in using the systems, are invited to call in to our Virtual Walk-in Consult to discuss problems Read More...
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Bioinformatics
01/16/2025 - This two-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& Read More...
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Bioinformatics
10/24/2024 - Recent advances in artificial intelligence (AI) have revolutionized the use of hematoxylin and eosin (H&E)-stained tumor slides for precision oncology, enabling data-driven approaches to predict molecular characteristics and therapeutic outcomes. In Read More...
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Bioinformatics
10/16/2024 - Dear Colleagues, Thanks to advances in single-cell genomics, researchers can construct large-scale organ atlases, giving you more accurate ways to study genetic mutations and alterations related to drug responses and disease. These Read More...
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Bioinformatics
09/16/2024 - This 45-minute online training will provide an overview of NanCI by the National Cancer Institute (NCI) , a new mobile application that uses machine learning algorithms to match users’ interests and Read More...
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Bioinformatics
Here, we will start with the data stored in a Seurat object. For instructions on data import and creating the object, see an Introduction to scRNA-Seq with R (Seurat) and Getting Started with Seurat: QC Read More...
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Bioinformatics
Due to limits on computational resources, you may be interested in running your analysis on an HPC. Biowulf is the NIH high performance compute cluster. It has greater than 90k processors, and can easily perform Read More...
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Bioinformatics
05/16/2024 - Qiagen CLC Genomics Workbench is a point-and-click bioinformatics software that runs on a personal computer and enables bulk RNA sequencing, ChIP sequencing, long reads, and variant analysis. NCI scientists can use CLC Genomics Workbench Read More...
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Bioinformatics
05/16/2024 - This course provides detailed information on managing and sharing data from the first data planning stage, through the data life cycle, to data archiving, and finally to selecting an appropriate repository for data preservation. Read More...
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Bioinformatics
04/16/2024 - GitHub is a powerful platform for tracking, sharing, and collaborating on software projects of all kinds. Whether you’re a bioinformatics analyst, a software engineer, or a biologist who sometimes codes, GitHub Read More...
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Bioinformatics
02/16/2024 - Deep sequencing has emerged as the primary tool for transcriptome profiling in cancer research. Like other high-throughput profiling technologies, sequencing is susceptible to systematic non-biological artifacts stemming from inconsistent experimental handling. A critical initial Read More...
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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...
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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...
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Bioinformatics
01/16/2024 - To register to attend, you must log in or create a free SITC Cancer Immunotherapy CONNECT account. It’s your last chance to register and learn about the cutting edge of computational immuno-oncology through Read More...
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Bioinformatics
01/16/2024 - This class focuses on data and project management using R and RStudio. RStudio makes it possible to work on a complete research project in a more efficient, integrated, and organized manner. This course is Read More...
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Bioinformatics
01/16/2024 - About this talk: In this presentation we will go through the rich variety of database types, from traditional relational to cutting-edge NoSQL, uncovering how each 'flavor' adds its unique spice to the world of Read More...
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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...
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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...
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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...
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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...
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Bioinformatics
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...
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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...
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Bioinformatics
Let's grab some data. library ( tidyverse ) acount_smeta % dplyr :: rename ( "Feature" = "...1" ) acount #differential expression results dexp % filter ( ! Feature %in% dexp $ feature ) ## # A tibble: 48,176 × 9 ## Feature SRR1039508 SRR1039509 SRR1039512 SRR1039513 SRR1039516 SRR1039517 ## ## 1 Read More...
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Bioinformatics
Help Session Lesson 6 Let's grab some data. library ( tidyverse ) acount_smeta % dplyr :: rename ( "Feature" = "...1" ) acount #differential expression results dexp % filter ( ! Feature %in% dexp $ feature ) ## # A tibble: 48,176 × 9 ## Feature SRR1039508 SRR1039509 SRR1039512 Read More...
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Bioinformatics
11/16/2023 - This class will provide a demonstration of how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Read More...
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Bioinformatics
10/16/2023 - This class introduces version control and how to use GitHub for project versioning. Participants will have a better understanding of version control, GitHub, and their advantages for managing projects. Upon Read More...
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Bioinformatics
Biowulf is the high performance computing cluster at NIH. When you apply for a Biowulf account you will be issued two primary storage spaces: 1) /home/$User and 2) /data/$USER , with 16 GB and 100 GB of default Read More...
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Bioinformatics
Which reference genome are we using in this IGV session to view the alignment results for samples hcc1395_normal_rep1 and hcc1395_tumor_rep2? On what chromosome are the sequencing data mapping to? {{Sdet}} Solution{{ Read More...
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Bioinformatics
For RNA sequencing studies, we need to use a splice aware aligner to account for reads that map across exons. Bowtie2 is a commonly used aligner for DNA sequencing and is not splice aware. Let' Read More...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
Lessons focus on RNA-Seq analysis including experimental design and best practices, quality control, trimming, alignment based methods, classification based methods, feature counts, and differential expression analysis. Lesson 8: Introduction to RNA-Seq ( Recording ) Lesson 9: Introduction to the Read More...
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Bioinformatics
BBDuk is another tool that can be used for adapter and quality trimming. In addition, BBDuk can be used to filter out contaminations, perform GC filtering, filter for length, etc. (see https://jgi.doe.gov/ Read More...
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Bioinformatics
For RNA sequencing studies, we need to use a splice aware aligner to account for reads that map across exons. Bowtie2 is a commonly used aligner for DNA sequencing and is not splice aware. Let' Read More...
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Bioinformatics
We will download a new tool "csvkit" for working on the comma separated files. This tool is careful to cut only at the columns used as delimiters, and not commas that are part Read More...
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Bioinformatics
Lesson 12: RNA sequencing review 1 Learning objectives Here, we will do a quick review of what we have learned about RNA sequencing in Lessons 8 through 11. Accessing the Biostar handbook The URL for the Biostar handbook is Read More...
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Bioinformatics
Note that we now have differential expression by transcripts and our first column contains the transcript IDs. But what genes do these transcripts map to? We will need to do some data wrangling to find Read More...
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Bioinformatics
Lesson 14 Practice Objectives Here, we will practice using the Integrative Genome Viewer (IGV) to visualize the hcc1395 RNA sequencing alignment results. About the data and launching IGV We were introduced to the hcc1395 RNA sequencing Read More...
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Bioinformatics
Lesson 14: Visualizing alignment results Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 13 Review Previously, we used the application HISAT2 to align the raw sequencing data from the Human Brain Read More...
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Bioinformatics
Lesson 9: Reference genomes and genome annotations used in RNA sequencing Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 8 Review In Lesson 8, we learned about the basics of RNA sequencing, Read More...
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Bioinformatics
Lesson 9: Reference genomes and genome annotations used in RNA sequencing Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 8 Review In Lesson 8, we learned about the basics of RNA sequencing, Read More...
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Bioinformatics
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...
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Bioinformatics
Lesson 14: Visualizing alignment results Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 13 Review Previously, we used the application HISAT2 to align the raw sequencing data from the Human Brain Read More...
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Bioinformatics
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...
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Bioinformatics
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...
Bethesda, MD
Collaborative
As a multi-user facility, the different instruments provide a wide range of imaging modes for EIB scientists, from standard immunohistochemistry, through brightfield and wide-field epifluorescence imaging, to highly complex live cell confocal microscopy and super-resolution Read More...
Frederick, MD
Core Facility
The CCR-Frederick Flow Cytometry Core Facility provides research support to the Frederick-CCR community, including cytometry analysis and sorting services, instrument maintenance, new user training, and technical consultation. Typical Assays Performed by Core Instruments Immunophenotyping of Read More...
Rockville, MD
Core Facility
Trans NIH Facility
The Functional Genomics Laboratory (formerly, the RNAi Screening Facility) of the National Center for Advancing Translational Sciences (NCATS) assist investigators with all stages of project planning and execution, beginning with assay development through genome-wide siRNA Read More...
Bethesda, MD
Trans NIH Facility
The Neurorehabilitation and Biomechanics Research Section (also referred to as the NAB LAB) is a multidisciplinary group of highly qualified scientists, clinical and technical staff, and trainees with diverse backgrounds including medical, physical therapy, neuroscience Read More...
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CREx News & Updates September 2021 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGLIGHTS Learn more about services from the CCR Read More...
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CREx News & Updates December 2021 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Site Spotlight FACILITY HIGLIGHTS Learn more about services from the STRIDES Initiative. VIEW STRIDES INITIATIVE NIH Cores Read More...
Rockville, MD
Trans NIH Facility
NISC’s role within NHGRI, and more broadly across NIH, aims to advance genome sequencing and its many applications, with a goal not simply to produce sequence data, but to produce the infrastructure required to Read More...
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Bioinformatics
04/16/2025 - Updated Location: ATRF, Frederick MD, Main Auditorium What to bring: Laptop capable of connecting to internet via NIH wifi For questions or to register, please contact Amy Stonelake ( amy.stonelake@nih.gov ) Read More...
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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...
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Bioinformatics
The Seurat Object is a data container for single cell RNA-Seq and related data. It is an S4 object, which is a type of data structure that stores complex information (e.g., scRNA-Seq count matrix, Read More...
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Bioinformatics
Some tools have been described in the previous session (see here ). Today, we will be focusing on the SingleR tool, which also requires the celldex package . In short, SingleR operates by comparing your current dataset Read More...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
This lesson will introduce data wrangling with R. Attendees will learn to filter data using base R and tidyverse (dplyr) functionality. Learning Objectives Understand the concept of tidy data. Become familiar with the tidyverse packages. Read More...
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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...
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Bioinformatics
Help Session Lesson 3 Loading data Import data from the sheet "iris_data_long" from the excel workbook (file_path = "./data/iris_data.xlsx"). Make sure the column names are unique and Read More...
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Bioinformatics
Objectives To explore Bioconductor, a repository for R packages related to biological data analysis. To better understand S4 objects as they relate to the Bioconductor core infrastructure. To learn more about a popular Bioconductor S4 Read More...
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Bioinformatics
Data import and reshape Objectives 1. Learn to import multiple data types 2. Data reshape with tidyr : pivot_longer() , pivot_wider() , separate() , and unite() Installing and loading packages So far we have only worked with objects that Read More...
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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...
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Bioinformatics
Help Session Lesson 5 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 Read More...
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Bioinformatics
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...
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Bioinformatics
Introduction to dplyr and the %>% Objectives Today we will begin to wrangle data using the tidyverse package, dplyr . To this end, you will learn: how to filter data frames using dplyr how to employ Read More...
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Bioinformatics
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...
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Bioinformatics
This page uses content directly from the Biostars Handbook by Istvan Albert (https://www.biostarhandbook.com). Always remember to load the bioinformatics environment. conda activate bioinfo SAM files SAM format is TAB-delimited, line-oriented, human-readable text Read More...
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Bioinformatics
This page uses content directly from the Biostars Handbook by Istvan Albert (https://www.biostarhandbook.com). Always remember to load the bioinformatics environment. conda activate bioinfo SAM files SAM format is TAB-delimited, line-oriented, human-readable text Read More...
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Bioinformatics
Let's go back to the biostar_class directory and create a folder called practice_trimming for this exercise. How do we do this? {{Sdet}} Solution{{Esum}} This depends on where you are currently (ie. Read More...
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Bioinformatics
By using the metacharacter asterisk "*" we can run feature counts on all the HBR and UHR samples in one command line. featureCounts -a refs/ERCC92.gtf -g gene_name -o counts.txt bam/ Read More...
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Bioinformatics
By using the metacharacter asterisk "*" we can run feature counts on all the HBR and UHR samples in one command line. featureCounts -a refs/ERCC92.gtf -g gene_name -o counts.txt bam/ Read More...
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Bioinformatics
By using the metacharacter asterisk "*" we can run feature counts on all the HBR and UHR samples in one command line. featureCounts -a refs/ERCC92.gtf -g gene_name -o counts.txt bam/ Read More...
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Bioinformatics
Alignment RNASeq Mapping Challenges The majority of mRNA derived from eukaryotes is the result of splicing together discontinuous exons, and this creates specific challenges for the alignment of RNASEQ data. Mapping Challenges Reads not perfect Read More...