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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...

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...

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...

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...

-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...

-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...

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...

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 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...

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...

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...

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...

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 Mouse Modeling Core assists NIH investigators by generating and preserving genetically-engineered mouse strains. Services include scientific consultation, gene-targeting in mouse embryonic stem cells, micro-injection of nucleic acids, proteins, or ES cells into mouse embryos, Read More...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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 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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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 protein, macromolecular complexes, membrane receptors, cellular organelles, and Read More...

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...

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...

The Biological Products Core provides the AIDS research community with high-quality purified preparations of various strains of Human Immunodeficiency Virus (HIV) and Simian Immunodeficiency Virus (SIV), economically prepared by leveraging the economy of scale. Materials Read More...

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...

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...

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...

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...

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...

[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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

This page uses content directly from the Biostar Handbook by Istvan Albert. Learn * What are sequence adapters? * Do we need to trim them before alignment? * How can I trim with a new adapter sequence? Be Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Learn * What are sequence adapters? * Do we need to trim them before alignment? * How can I trim with a new adapter sequence? Be Read More...

Bioinformatics for Beginners: RNA-Seq Course Description: This course was designed to teach the basic skills needed for bioinformatics, including working on the Unix command line. This course primarily focuses on RNA-Seq analysis. All steps of Read More...

When analyzing high throughput sequencing data, we will need to trim away adapters. Adapters help anchor the unknown sequencing template to the Illumina flow cell and can interfere with alignment. We may also want to Read More...

The SRA (Sequence Read Archive) at NCBI is a large, public database of DNA sequencing data. The repository holds "short reads" generated by high-throughput next-generation sequencing, usually less than 1,000 bp. We will download Read More...

Let's now take a look at our final differential analysis results table (results_with_gene_names_labeled.txt), using the SLC2A11 gene as an example and below we use the column command to Read More...

Lesson 11 Practice Objectives In this lesson, we learned to merge multiple FASTQC reports into one perform data cleanup (quality and adapter trimming) to prepare our sequencing reads for downstream analysis. Here, we will put what Read More...

fastq-dump and fasterq-dump can be used to download FASTQ-formatted data. Both download the data in SRA format and convert it to FASTQ format. fastq-dump SRR1553607 creates the file: SRR1553607.fastq Check the file to make Read More...

fastq-dump and fasterq-dump can be used to download FASTQ-formatted data. Both download the data in SRA format and convert it to FASTQ format. fastq-dump SRR1553607 creates the file: SRR1553607.fastq Check the file to make 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 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...

This page uses content directly from the Biostar Handbook by Istvan Albert. Review: * cd * mkdir * curl * tar * cat * grep * wc * outputting data * piping data from one command to another * cut Learn: * du * pip * csvkit * datamash 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...

This page contains content directly from The Biostar Handbook . Always remember to start the bioinformatics environment. conda activate bioinfo Pseudoalignment-based methods identify locations in the genome using patterns rather than via alignment type algorithms. It Read More...

This page contains content directly from The Biostar Handbook . Always remember to start the bioinformatics environment. conda activate bioinfo Pseudoalignment-based methods identify locations in the genome using patterns rather than via alignment type algorithms. It Read More...

Lesson 11: Merging FASTQ quality reports and data cleanup Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 10 Review In the previous lesson, we learned about the structure of the FASTQ 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...

We previously stored FASTQC results for the HBR and UHR raw sequencing data in the ~/biostar_class/hbr_uhr/QC directory (recall that ~ denotes home directory). So before getting started, change into this folder. cd ~/ Read More...

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...

The bowtie2-build indexer builds a Bowtie index from a set of DNA sequences ([ref]. "bowtie2-build" builds a Bowtie index from a set of DNA sequences. "bowtie2-build" outputs a 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...

In lesson 9, we learned that reference genomes came in the form of FASTA files, which essentially store nucleotide sequences. In this lesson, we will learn about the FASTQ file, which is the file format that Read More...