Search Results for: exercise physiology

Putting what we have learned to the test: The following questions synthesize several of the skills you have learned thus far. It may not be immediately apparent how you would go about answering these questions. Read More...

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

What geoms would you use to draw each of the following named plots? a. Scatterplot b. Line chart c. Histogram d. Bar chart e. Pie chart (Question taken from https://ggplot2-book.org/individual-geoms.html .) {{ Read More...

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

Q1. What is the value of each object? Run the code and print the values. mass <- 47.5 # mass? age <- 122 # age? mass <- mass * 2.0 # mass? age <- Read More...

Q1. Let's use some functions. a. Use sum() to add the numbers from 1 to 10. Q1a: Solution sum(1:10) ## [1] 55 b. Compute the base 10 logarithm of the elements in the following vector and save to an Read More...

Let's use some functions. a. Use sum() to add the numbers from 1 to 10. {{Sdet}} Solution{{Esum}} sum ( 1 : 10 ) {{Edet}} b. Compute the base 10 logarithm of the elements in the following vector and save to an Read More...

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

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

Let's use some functions. a. Use sum() to add the numbers from 1 to 10. {{Sdet}} Solution{{Esum}} sum ( 1 : 10 ) {{Edet}} b. Compute the base 10 logarithm of the elements in the following vector and save to an Read More...

07/09/2024 - Galaxy is a scientific workflow, data integration, data analysis, and publishing platform that makes computational biology accessible to research scientists that do not have computer programming experience. This workshop will cover exome sequencing data Read More...

07/14/2023 - Galaxy is a scientific workflow, data integration, data analysis, and publishing platform that makes computational biology accessible to research scientists that do not have computer programming experience. This workshop will cover exome sequencing data Read More...

What is the distribution of fuel efficiency (mpg)? Use 7 bins for this exercise. {{Sdet}} Solution{{Esum}} ggplot ( mtcars , aes ( x = mpg )) + geom_histogram ( fill = "orange" , bins = 7 ) {{Edet}}

09/22/2022 - The avalanche of easy-to-create genomics data has impacted almost all areas of medicine and science, from cancer patients and microbial diagnostics to molecular monitoring for astronauts in space. In this lecture, new discoveries from Read More...

01/27/2025 - NCI CCR Liver Cancer Program Seminar Series Dr. Sethupathy is professor of physiological genomics and chair of the Department of Biomedical Sciences at Cornell University. He leads a research lab focused on genome-scale and Read More...

To access the NIH Partek Flow server, go to https://partekflow.cit.nih.gov/flow and enter the user's NIH username and then password. Note User may have selected a password different than that Read More...

Those researchers who used the NCI CCR Sequencing Facility to get sequencing done will receive a link to their data. This data can be transferred to the "PartekFlow" folder on Biowulf using Globus. Read More...

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

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...

09/22/2022 - The avalanche of easy-to-create genomics data has impacted almost all areas of medicine and science, from cancer patients and microbial diagnostics to molecular monitoring for astronauts in space. In this lecture, new discoveries from Read More...

09/15/2022 - In partnership with the National Cancer Institute (NCI) Cancer Moonshot SM , the Society for Immunotherapy of Cancer (SITC) and the  Big Data and Data Sharing Committee  are excited to announce our second " SITC-NCI Read More...

08/03/2022 - This training will provide an introduction to ChIP sequencing data analysis followed by a tutorial showing ChIP-seq analysis workflow and preparing participants to independently run basic ChIP-seq analysis for peak calling using a " Read More...

07/13/2022 - This training will provide an introduction to exome sequencing data analysis followed by tutorials showing the use of exome analysis workflow and preparing participants to independently run basic exome analysis for variant detection using Read More...

05/25/2022 - This training will provide an introduction to RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The Read More...

05/04/2022 - Presenter: Thomas Gonatopoulos-Pournatzis, Ph.D. Stadtman Investigator NIH Distinguished Scholar Head Functional Transcriptomics Section RNA Biology Laboratory NCI-Frederick Dr. Gonatopoulos-Pournatzis studies the regulatory pathways and functional roles of alternative splicing and other pre-mRNA processing Read More...

08/16/2021 - This training will provide an introduction to ChIP sequencing data analysis followed by a tutorial showing ChIP-seq analysis workflow and preparing participants to independently run basic ChIP-seq analysis for peak calling using a " Read More...

06/28/2021 - This training will provide an introduction to exome sequencing data analysis followed by tutorials showing the use of exome analysis workflow and preparing participants to independently run basic exome analysis for variant detection using Read More...

05/18/2021 - Register Session Description This training will provide an introduction to RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for Read More...

03/08/2021 - Zoom Registration Description NHGRI will host a new seminar series this year on the “Bold Predictions for Human Genomics by 2030” that are described in NHGRI’s “ Strategic Vision for Improving Human Health at the Read More...

06/26/2020 - This training will provide an introduction to exome sequencing data analysis followed by tutorials showing the use of exome analysis workflow and preparing participants to independently run basic exome analysis for variant detection using Read More...

06/23/2020 - This training will provide an introduction to exome sequencing data analysis followed by tutorials showing the use of exome analysis workflow and preparing participants to independently run basic exome analysis for variant detection using Read More...

06/12/2020 - This training will provide an introduction to ChIP sequencing data analysis followed by a tutorial showing ChIP-seq analysis workflow and preparing participants to independently run basic ChIP-seq analysis for peak calling using a " Read More...

06/09/2020 - "This training will provide an introduction to ChIP sequencing data analysis followed by a tutorial showing the use of ChIPseq analysis workflow and preparing participants to independently run basic ChIPseq analysis for peak Read More...

05/18/2020 - This training will provide an introduction to RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The Read More...

The Metabolic Clinical Research Unit (MCRU) opened in 2007 as a key component of the Strategic Plan for NIH Obesity Research . The NIDDK worked closely with the Clinical Center to design the Unit, which houses state-of-the-art Read More...

The NIA Nonhuman Primate (NHP) Core Facility maintains a colony of rhesus macaques at the National Institutes of Health Animal Center. Established in 2012, the Core's mission is to offer research services supporting multi-disciplinary translational aging Read More...

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...

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...

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

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

Accessing Partek Flow at NIH and tips for data transfer Learning objectives Instructions for accessing Partek Flow NCI researchers can find instructions for accessing Partek Flow at https://bioinformatics.ccr.cancer.gov/btep/partek-flow-bulk-and-single-cell-rna-seq-data-analysis/ . But Read More...

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

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

Lesson 5 Exercise Questions: ggplot2 What geoms would you use to draw each of the following named plots? a. Scatterplot b. Line chart c. Histogram d. Bar chart e. Pie chart (Question taken from https://ggplot2 Read More...

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

Lesson 2 Exercise Questions: Base R syntax, objects, and data types Let's use some functions. a. Use sum() to add the numbers from 1 to 10. {{Sdet}} Solution{{Esum}} sum ( 1 : 10 ) {{Edet}} b. Compute the base 10 logarithm of Read More...

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

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

Lesson 6 Exercise Questions: ggplot2 Putting what we have learned to the test: The following questions synthesize several of the skills you have learned thus far. It may not be immediately apparent how you would go Read More...

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...

Practice Lesson 4 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 Read More...

We were introduced to the hcc1395 RNA sequencing data in Lesson 12 practice session . This study compared the transcriptome of hcc1395 normal and cancer cell lines so it's a normal versus tumor comparison. This dataset Read More...

For this exercise, go back to the ~/biostar_class/hcc1395 folder and create a new directory called trimmed_data. {{Sdet}} Solution{{Esum}} cd ~/biostar_class/hcc1395 mkdir trimmed_data cd trimmed_data {{Edet}} The adapters Read More...

Can we combine just the fold change columns in the alignment based and classification based differential analysis results to compare the two? Hint: first copy the results.csv file from the alignment based method in 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...

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...

This exercise will use Seaborn's clustermap function to construct a gene expression heatmap of top differentially expressed genes in the HBR and UHR study. Heatmaps are another common visualization in RNA sequencing and allow Read More...

The following questions will have you explore the mtcars dataset through creating plots that were presented in Lesson 4. At the end of these exercises, you should be more comfortable creating plots that convey statistical summary Read More...

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

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

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

Lesson 5 Exercise Questions: ggplot2 What geoms would you use to draw each of the following named plots? a. Scatterplot b. Line chart c. Histogram d. Bar chart e. Pie chart (Question taken from https://ggplot2 Read More...

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

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

Lesson 2 Exercise Questions: Base R syntax, objects, and data types Let's use some functions. a. Use sum() to add the numbers from 1 to 10. {{Sdet}} Solution{{Esum}} sum ( 1 : 10 ) {{Edet}} b. Compute the base 10 logarithm of Read More...

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

Lesson 6 Exercise Questions: ggplot2 Putting what we have learned to the test: The following questions synthesize several of the skills you have learned thus far. It may not be immediately apparent how you would go Read More...

12/09/2022 - PhysioNet is a data sharing platform that began as an outreach component for an NIH research project in 1999. Rebuilt in 2019 following FAIR principles (Findable, Accessible, Interoperable, Reusable), the platform has grown rapidly. It now Read More...

10/03/2016 - The maximum number of registrations (25) allowed has been reached for this workshop. You will be put on the waitlist and informed if any cancellations do occur. You are welcome to come on the morning Read More...

01/07/2016 - REGISTRATION IS FULL FOR THIS WORKSHOP (25 ATTENDEES; 6 WAITLIST) The Cancer Genome Atlas (TCGA) is a large-scale study that has cataloged genomic data accumulated for many different types of cancers, and includes mutations, copy number Read More...

06/02/2015 - This workshop will cover some basic concepts involved in the integration of different types of NGS data in order to obtain a better overall picture of the underlying biology. Specifically, the course will examine Read More...

Accessing Partek Flow at NIH and tips for data transfer Learning objectives After consulting this guide, participants will Know how to access Partek Flow at NIH. Be able to transfer data from NCI CCR Sequencing Read More...

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...

Lesson 12 Practice Objectives In this practice session, we will work with something new, which is a dataset from the Griffith lab RNA sequencing tutorial. Here, we will have a chance to practice what we have 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...

Lesson 10: Introducing the FASTQ file and assessing sequencing data quality Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 9 Review In the previous lesson, we explored the reference genomes and Read More...

Managing Bioinformatics Projects with Jupyter Lab Learning Objectives After this class, participants will have obtained the foundation needed to start using Jupyter Lab as an all-in-one place to maintain code, output, and other description of 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...

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

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

12/19/2016 - iPathwayGuide is a gene and protein expression analysis tool that uses a systems biology approach to identify significantly impacted pathways, gene ontology terms, diseases, and predicted microRNAs based on the given gene or protein Read More...

09/01/2016 - This 2-day workshop, including a BYOD (Bring Your Own Data) exercise, will provide an introduction and hands-on training for Cytoscape, which is an open source software platform for visualizing  networks and integrating these networks Read More...

06/06/2016 - The 'NCBI Resources for CCR Scientists' workshop, on June 6 and June 8, 2016, will focus on teaching a wide range of resources developed within NCBI that are relevant for CCR scientists. It will include both hands-on Read More...

09/22/2015 - Learn the basics of microarray gene expression analysis using Partek Genomics Suite and Open Source Tools. As we walk though hands-on analysis of a cancer dataset, you will learn the principles of experimental design, Read More...