Search Results for: Ad 5/3 Delta-24

06/24/2025 - Thi year the Frederick Re earch Compute Environment (FRCE) i expanding it outreach. Our fir t new feature i a web-ba ed tool that will allow you to ea ily run graphical application on Read More...

04/24/2025 - This class will introduce beginners or those looking for a refresher to Jupyter Lab, a platform used to organize code and analysis steps in one place. Jupyter Lab can be easily installed or run Read More...

03/24/2025 - AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be Read More...

02/24/2025 - AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be Read More...

Welcome to Getting Started with scRNA-Seq This is a mini seminar series designed to help attendees learn more about single cell RNA-Seq, from applicable technologies to data analysis. Seminar Schedule April 3, 2024 - The CCR Single Read More...

04/24/2024 - This seminar provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat.  In this seminar, attendees will learn about options for analyzing scRNA-Seq data, resources for learning R, how Read More...

04/24/2024 - Please join us on Wednesday, April 24, 2024, when Dr. Abhishek Jha, co-founder and CEO of Elucidata, will present " Data Quality for LLMs: Building a Reliable Data Foundation." The presentation starts at 11:00 a.m. Read More...

To participate in this class you will need your government-issued computer and a reliable internet connection. You do not need to download or install any software to participate in the class. However, at the end Read More...

01/24/2024 - This 90-minute course equips participants with essential knowledge and skills for effective interactions with Large Language Models (LLMs), such as ChatGPT. Explore the intricacies of prompt engineering and its pivotal role in optimizing the Read More...

01/24/2024 - Documenting your data analysis is a crucial step toward making your research reproducible. In this session of the BTEP Coding Club, we will learn how to get started using Quarto with RStudio for report Read More...

01/24/2024 - Dear colleagues,   Please join us on Wed., Jan. 24 when Dr. Avi Ma’ayan from the Icahn School of Medicine at Mount Sinai will demonstrate how to use these tools to access hundreds of thousands Read More...

01/24/2024 - Dear Colleague,   Helen Shearman, Ph.D., Senior Field Application Scientist, will be presenting a one-hour overview demonstration on SnapGene. SnapGene offers a fast and easy way to plan, visualize, and document your Read More...

Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodrí Read More...

References This course series primarily used information from QIIME2.org and the QIIME2 forum . Specifically, this course series focused on data and code from the QIIME2 Cancer Microbiome Intervention Tutorial . Special thanks goes to the Read More...

06/29/2023 - Please join us for a special presentation about the Fred Hutchinson’s data journal to the cloud, including an innovative cloud platform (Cirro:  https://cirro.bio/ ) to streamline data collection, Read More...

01/24/2023 - Welcome to BTEP’s Introduction to Unix on Biowulf course series. We will meet on Tuesdays and Thursdays from 1 pm to 2 pm (starting January 24, 2023) to learn how to work in the Unix command line Read More...

06/24/2022 - RStudio Team is a data science platform that allows data scientists to develop and share data science pipelines with collaborators. In this presentation, RStudio will highlight the basic functionalities of the platform to provide 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...

Bruker AVANCE 400 and 500 MHz NMR instruments. Helium Cryoprobe technology on the 500 MHz machine for added sensitivity, especially for Carbon-13 spectra. Access to a second 500 MHz instrument with Prodigy Liquid Nitrogen-cooled cryoprobe. User Accounts can be Read More...

07/24/2025 - NIDDK Bio tat eminar erie : From Re earch tudy De ign to Collecting, Managing, and Analyzing Data. Learning Objective : 1.          To delineate feature of REDCap to upport project management for re earch tudie . 2.          To outline Read More...

07/24/2025 - The "Data Vi ualization in R" erie focu e on u ing ggplot and the broader tidyver e eco y tem to create in ightful and cu tomizable vi ualization . It cover Read More...

06/24/2025 - Tran late gene li t into biological in ight u ing pathway enrichment tool . Thi training will provide an overview the current tatu of pathway tool , with focu on oftware available to NIH community.  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...

09/24/2024 - This class will introduce beginners or those looking for a refresher to Jupyter Lab, a platform used to organize code and analysis steps in one place. Jupyter Lab can be easily installed or run Read More...

07/24/2024 - As a cancer researcher, did you know that  data sharing  is now required by many funding agencies and journals? Join NCI CBIIT’s  Dr. Jill Barnholtz-Sloan & Read More...

07/24/2024 - Knowledge of Unix command line is advantageous for scientists who are new to bioinformatics, as many tools are designed to run on Unix-like systems. High performance computing systems (e.g., NIH Biowulf) also require Read More...

07/24/2024 - Partek Flow enables scientists to construct analysis workflows for multi-omics sequencing data including DNA, bulk and single cell RNA, spatial transcriptomics, ATAC and ChIP. It is hosted on Biowulf, the NIH high performance computing Read More...

07/24/2024 - This hour and half in-person training will explore the topics of perception and cognition, and how these apply to data visualization. There will also be a discussion on “pre-attentive” properties Read More...

Much like pseudobulk differential expression, the RNA expression can be collapsed into pre-defined components, such as the clusters, if it is believed that cell-to-cell variation is inducing too much confusion in the labeling. This collapsing Read More...

April 3, 2024 - The CCR Single Cell Analysis Facility (SCAF): An Overview (Mike Kelly, SCAF) ( Recording ) April 10, 2024 - Introduction to single cell RNA-Seq (Charlie Seibert, Saeed Yadranji Aghdam, SCAF) ( Recording ) April 17, 2024 - SCAF: Overview of Cell 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...

There is an approach to data analysis known as "split-apply-combine", in which the data is split into smaller components, some type of analysis is applied to each component, and the results are combined. Read More...

There is an approach to data analysis known as "split-apply-combine", in which the data is split into smaller components, some type of analysis is applied to each component, and the results are combined. Read More...

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

01/24/2024 - This is the second lesson of the Introduction to Unix on Biowulf, January 2024 series. After this lesson, participants will  Know how to get help with Unix commands Know how to transfer data from local Read More...

For the following plots, let's use the diamonds data ( ?diamonds ). The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and cut of each diamond. --- R4 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...

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...

10/24/2023 - In this session, we will provide an overview of the Next-Generation Sequencing (NGS) capabilities and applications. We will present the workflows and analyses for Illumina short-read, PacBio, and Oxford Nanopore long-read sequencing on Frederick Read More...

09/28/2023 - Attend the Bridge2AI-Skills & Workforce Development (SWD) Lecture Series for 2023-24 on the Large Language Model (LLM) Module Dr. Xia “Ben” Hu is an Associate Professor at Rice University in the Department of Read More...

Most alignment algorithms rely on the construction of auxiliary data structures, called indices, which are made for the sequence reads, the reference genome sequence, or both. Mapping algorithms can largely be grouped into two categories Read More...

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...

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...

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...

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...

08/24/2023 - Attend this virtual junior investigator session and hear Oak Ridge National Lab’s Dr. Adam Spannaus and Stanford’s Dr. Chenchen Zhu describe how they use analyses and AI models Read More...

07/24/2023 - In partnership with the NIH Clinical Center's Biostatistics and Clinical Epidemiology Service (BCES), the NIH Library is offering classes geared to cover general concepts behind statistics and epidemiology. This four-part lecture series will Read More...

Let's check out the structure of the data. {{Sdet}} Possible Solution{{Esum}} str(mtcars) ## 'data.frame': 32 obs. of 11 variables: ## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ... ## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ... ## $ disp: num 160 160 108 258 360 ... ## $ hp : num 110 110 93 110 175 105 245 62 95 123 ... ## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ... ## $ wt : num 2.62 2.88 2.32 3.21 3.44 ... ## $ qsec: num 16.5 17 18.6 19.4 17 ... ## $ vs : Read More...

08/24/2022 - Register for the  August Cancer Genomics Cloud  (CGC) webinar to learn more about FragPipe, a one-stop proteomics  data analysis  suite, and how it runs on the CGC using publicly available data. Dr. Fengchao Yu Read More...

08/24/2022 - Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m875b987cd37fafd4c24a84b7296aadb0 This webinar will demonstrate new features for creating publication ready RNA-Seq Graphs using the easy Point-and-Click Read More...

08/24/2022 - Precision oncology has made significant advances, mainly by targeting actionable mutations and fusion events involving cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun to explore the utility of tumor transcriptome Read More...

05/24/2022 - Python is one of the preferred programming languages for scientists to solve a wide variety of biological problems. We find that many scientists who come to Software Carpentry workshops use Python and want to Read More...

05/10/2022 - Overview Python is one of the preferred programming languages for scientists to solve a wide variety of biological problems. We find that many scientists who come to Software Carpentry workshops use Python and want 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...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New CREx Program Manager The CREx Team is happy to announce Deepika Velampati as the new CREx Program Read More...

The COP evaluates novel therapies in pet dogs with cancer to improve outcomes for human patients and established the Comparative Oncology Trial Consortium (COTC), a collaborative effort of NCI and extramural comparative oncology centers at 24 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...

Molecular Cytogenetics Core Facility facilitates the assessment of structural and numerical genomic changes in pre-cancer and cancer research models. This core provides comprehensive support for the cytogenetic analysis of cells from human and research animal Read More...

The CCR Building 41 Flow Cytometry Core is a full-service facility within the Center for Cancer Research that supports over 150 users representing 26 laboratories. The Core Facility provides instrument and software training, technical expertise, assay development, and Read More...

CREx News & Updates February 2022 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Site Spotlight ORS Division of Veterinary Resources (DVR) DVR is the central NIH lab animal support program Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Spotlight The NIH Lab Managers Working Group have developed a new NIH-wide database of cold 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...

The Flow Cytometry Core (LGI) offers established technologies to support studies using flow cytometry and cell sorting. Established Technologies Applications that run on FACS Caliburs include: Immunophenotyping (up to 4-color), Intracellular markers, including cytokines and Read More...

CREx News & Updates March 2022 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Site Spotlight NIA Nonhuman Primate Core The NIA Nonhuman Primate Core supports multi-disciplinary translational aging projects for Read More...

The AgingResearchBiobank was officially launched in January 2019 with a mission to provide a state-of-the-art inventory system for the storage, maintenance, and distribution of de-identified biospecimens and associated phenotypic, clinical, and imaging data from numerous NIA-funded Read More...

In order to meet increasing demands from both NIH intramural and extramural communities for access to a small angle X-ray scattering (SAXS) resource, the Center for Cancer Research (CCR) under the leadership of Drs. Jeffrey Read More...

The OSTR offers cutting-edge technology platforms to the CCR scientific community through centralized facilities. The videos accessed through this page are designed to introduce the various scientific methodologies OSTR makes available through the cores on Read More...

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...

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...

10/24/2024 - NIH Text Mining and Natural Language Processing SIG is pleased to welcome you to this special event featuring two extraordinary speakers focused on the applications of Deep Learning in Computational Biology.  & 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...

In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...

In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...

Help Session Lesson 4 Plotting with ggplot2 For the following plots, let's use the diamonds data ( ?diamonds ). The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and Read More...

Why did we focus so heavily on the tidyverse if it can't be used to manipulate Bioconductor objects? Well, for one, regardless of whether you are a user of Bioconductor packages, you will often 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...

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...

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...

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...

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...

Let's use the tool Trimmomatic to clean up the adapters and the poor quality reads for SRR1553606. For help with Trimmomatic type trimmomatic --help at the command line. Before getting started with using trimmomatic, 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 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...

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...

We will build a database out of all features of the 2014 Ebola genome under accession number KM233118. This data will go into a new directory named "db_2014". mkdir -p db_2014 # Get the 2014 Ebola Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Review: * downloading data from SRA * decompressing tar files * e-utilities * fastq-dump Learn: * sra-stat * XML format * automating SRA downloads * working with comma-separated values (csv) format * Read More...

“Gene set enrichment analysis” refers to the process of discovering the common characteristics potentially present in a list of genes. When these characteristics are GO terms, the process is called “functional enrichment.” Warning Overall GO 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...

Lesson 6: sra-tools, e-utilities, and parallel This page uses some content directly from the Biostar Handbook by Istvan Albert. Lesson 5 Review: The majority of computational tasks on Biowulf should be submitted as jobs: sbatch or swarm Read More...

Lesson 6: Downloading data from the SRA For this lesson, you will need to login to the GOLD environment on DNAnexus. Lesson 5 Review: The majority of computational tasks on Biowulf should be submitted as jobs: sbatch 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 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...

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 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...

This page uses content directly from the Biostar Handbook by Istvan Albert. Remember to activate the bioinformatics environment and create a directory for today's work. conda activate bioinfo mkdir blast cd blast What is Read More...

Load the data For these exercises, you will explore the titanic data from kaggle.com , which was downloaded from here . You will need to download the data and load into R. As this is a Read More...

There is an approach to data analysis known as "split-apply-combine", in which the data is split into smaller components, some type of analysis is applied to each component, and the results are combined. Read More...

Introduction to Data Wrangling with the Tidyverse Objectives Wrangle data using tidyverse functionality (i.e., dplyr ). To this end, you should understand: 1. how to use common dplyr functions (e.g., select() , group_by() , arrange() , mutate() , Read More...