Bethesda, MD
Trans NIH Facility
The NIH Biowulf Cluster provides researchers with a world-class system to assist in solving complex biomedical problems as diverse as gene variation in worldwide human populations, deep learning to model protein structures, and PET brain Read More...
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Back Services: Biophysics Facility offers ITC calorimeters as open-access instruments. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Training includes performing a test experiment and Read More...
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Bioinformatics
Logistic regression is a machine learning algorithm used for classification, predicting the probability of a binary outcome (like Yes/No, 0/1, Spam/Not Spam) based on input variables, fitting an S-shaped curve (sigmoid or logistic) to Read More...
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Bioinformatics
The primary reason not to use R is that it has a rather steep learning curve. The best way to learn R is to use R, but to use R, you need to learn a Read More...
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Bioinformatics
Rarefaction is the process of subsampling reads without replacement to a defined sequencing depth, thereby creating a standardized library size across samples. Any sample with a total read count less than the defined sequencing depth Read More...
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Bioinformatics
As with any language, the learning curve for Unix can be quite steep. However, to work on Biowulf you really need to understand the following: Directory navigation: what the directory tree is, how to navigate Read More...
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Bioinformatics
02/12/2020 - The Role of Generalist and Institutional Repositories to Enhance Data Discoverability and Reuse The primary goals of the workshop are to: Learn how generalist repositories see themselves in the larger biomedical data repository landscape. Read More...
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Bioinformatics
02/11/2020 - The Role of Generalist and Institutional Repositories to Enhance Data Discoverability and Reuse The primary goals of the workshop are to: Learn how generalist repositories see themselves in the larger biomedical data repository landscape. Read More...
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Bioinformatics
ROC (Receiver Operating Characteristic) Curve tells us about how good the model can distinguish between two things (e.g If a patient has a disease or no). Better models can accurately distinguish between the two. Read More...
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Bioinformatics
ROC (Receiver Operating Characteristic) Curve tells us about how good the model can distinguish between two things (e.g If a patient has a disease or no). Better models can accurately distinguish between the two. Read More...
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Bioinformatics
The script deg.R in b4b_script will be used perform differential expression analysis on the hcc1395 data. This script will use DESeq2 and takes the following as input. Filtered gene expression table, which Read More...
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Bioinformatics
R is freely available and can be used via command line, through an integrated development environment (RStudio), and online (RStudio Server). Using R effectively can make scientific data analysis more reproducible. Data reports can be Read More...
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Bioinformatics
12/02/2026 - Partek Flow is a point-and-click platform for building analysis workflows for Next Generation Sequences (NGS), including DNA, bulk and single-cell RNA, spatial transcriptomics, ATAC, and ChIP, helping scientists avoid the steep learning curve of Read More...
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Bioinformatics
10/14/2026 - Partek Flow is a point-and-click platform for building analysis workflows for Next Generation Sequences (NGS), including DNA, bulk and single-cell RNA, spatial transcriptomics, ATAC, and ChIP, helping scientists avoid the steep learning curve of Read More...
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Bioinformatics
08/19/2026 - Partek Flow is a point-and-click platform for building analysis workflows for Next Generation Sequences (NGS), including DNA, bulk and single-cell RNA, spatial transcriptomics, ATAC, and ChIP, helping scientists avoid the steep learning curve of Read More...
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Bioinformatics
06/18/2026 - Partek Flow is a point-and-click platform for building analysis workflows for Next Generation Sequences (NGS), including DNA, bulk and single-cell RNA, spatial transcriptomics, ATAC, and ChIP, helping scientists avoid the steep learning curve of Read More...
Web Page
Bioinformatics
02/18/2026 - Partek Flow is a point-and-click platform for building analysis workflows for Next Generation Sequences (NGS), including DNA, bulk and single-cell RNA, spatial transcriptomics, ATAC, and ChIP, helping scientists avoid the steep learning curve of Read More...
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Bioinformatics
12/10/2025 - 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 a point-and-click software suitable for those who wish Read More...
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Bioinformatics
Data frames hold tabular data comprised of rows and columns; they can be created using data.frame() . To understand more about the structure of an object and data frame, consider the following functions: str() displays Read More...
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Bioinformatics
Partek Flow is a start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing sequencing Read More...
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Bioinformatics
A rarefaction curve plot[s] the number of counts sampled (rarefaction depth) vs. the expected value of species diversity. --- Weiss et al. 2017 Let's take a look at an alpha rarefaction curve . Demo plot Read More...
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Bioinformatics
Using a small subset of data: Imported raw fastq files using qiime tools import . Data was paired-end CASAVA format. Checked for primers using qiime cutadapt trim-paired . Denoised with qiime dada2 denoise-paired and generated summaries of Read More...
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Bioinformatics
As with any language, the learning curve for Unix can be quite steep. However, to get started analyzing data you really need to understand the following: Directory navigation: what the directory tree is, how to Read More...
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Bioinformatics
As with any language, the learning curve for Unix can be quite steap. However, to get started analyzing data you really need to understand the following: Directory navigation: what the directory tree is, how to Read More...
Web Page
Bioinformatics
Data frames hold tabular data comprised of rows and columns; they can be created using data.frame() . To understand more about the structure of an object and data frame, consider the following functions: str() displays Read More...
Web Page
Bioinformatics
06/14/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
05/03/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
To plot the first two axes of variation along with species information, we will need to make a data frame with this information. The axes are in pca$x . #Build a data frame pcaData
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Bioinformatics
04/12/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
The Unix command syntax is composed of The command Option(s) that will alter how a command functions Argument(s), what you want the command to operate on command options argument For instance, to make Read More...
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Bioinformatics
The Unix command syntax is composed of The command Option(s) that will alter how a command functions Argument(s), what you want the command to operate on command options argument For instance, to make Read More...
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Bioinformatics
First, split the data into labels and 2D arrays for training and testing as is the standard approach in ML. train_test_split function from the sklearn.model_selection module is commonly used to divide Read More...
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Bioinformatics
First, split the data into labels and 2D arrays for training and testing as is the standard approach in ML. train_test_split function from the sklearn.model_selection module is commonly used to divide Read More...
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Bioinformatics
Partek Flow is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing sequencing data through command line and/or code. It enables the analysis of Read More...
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Bioinformatics
As with any language, the learning curve for Unix can be quite steep. However, to work on Biowulf you really need to understand the following: Navigating the File System: Understanding the hierarchical structure of directories, Read More...
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Bioinformatics
As with any language, the learning curve for Unix can be quite steep. However, to work on Biowulf you really need to understand the following: Navigating the File System: Understanding the hierarchical structure of directories, Read More...
Web Page
Bioinformatics
09/13/2024 - Reverse-phase protein arrays (RPPAs) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and develop novel cancer therapies. To facilitate community-based investigation of the large-scale protein expression data generated by Read More...
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Bioinformatics
Partek Flow enables scientists to build comprehensive workflows for analyzing multi-omics high throughput sequencing data including DNA and variant calling, bulk and single cell modalities for RNA, ChIP, and ATAC, spatial transcriptomics, CITE, and immune Read More...
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Bioinformatics
Differential expression analysis is the process of identifying genes that have a significant difference in expression between two or more groups. For many sequencing experiments, regardless of methodology, differential analysis lays the foundation of the Read More...
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Bioinformatics
Course Overview Partek Flow is a start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with Read More...
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Bioinformatics
Lesson 5: Microbial diversity, alpha rarefaction, alpha diversity Learning Objectives Understand the difference between alpha and beta diversity Introduce several alpha diversity metrics Understand what rarefaction is and why it is important Introduce the debate regarding Read More...
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Bioinformatics
10/25/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
10/11/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
09/27/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
09/13/2023 - Partek Flow is your start-to-finish solution for analyzing high dimensional multi-omics sequencing data. It is a point-and-click software and is suitable for those who wish to avoid the steep learning curve associated with analyzing Read More...
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Bioinformatics
After the merged expression counts table has been created, we can proceed with differential expression analysis. Let's use DESeq2 again for this. But first, let's move counts.csv (the merged salmon expression table) Read More...
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Bioinformatics
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...
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Bioinformatics
Bioinformatics Training and Education Program 15 January – 15 February 2023 BTEP Bulletin Contact us at ncibtep@nih.gov FEATURED BIOINFORMATICS EVENTS Data Management Sharing: Part 1 and Part 2 DOE-NCI Collaboration: MOSSAIC for Advancing Computational Models for Cancer Research Variation Read More...
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Bioinformatics
06/06/2022 - Join the June NCI Imaging and Informatics Community Webinar for a discussion on the recent contributions from Dr. Mirabela Rusu’s Personalized Integrative Medicine Laboratory (PIMed) at Stanford University. Recent laboratory contributions include: registering Read More...
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Bioinformatics
To plot the first two axes of variation along with species information, we will need to make a data frame with this information. The axes are in pca$x. #Build a data frame pcaData & Read More...
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Bioinformatics
Definition "The goal of GSEA is to determine whether members of a gene set S tend to occur toward the top (or bottom) of the list L, in which case the gene set is Read More...
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Bioinformatics
Lesson 1: Introduction to Biowulf, Unix, and R Learning Objectives Learn about why you may want to use R on Biowulf. Refresh Unix and R skills. This lesson will not be hands on. Why use R 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
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
Lesson 7: Course Wrap-Up Learning Objectives Introduce the QIIME2 microbiome workflow for Biowulf Review key concepts Showcase additional plugins QIIME 2 on Biowulf As mentioned previously, QIIME 2 is installed on Biowulf. To see available versions use module Read More...
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Bioinformatics
Lesson 1: Introduction to Unix and the Shell Lesson Objectives Review the course syllabus and general structure of lessons to come. Introduce Unix and describe how it differs from other operating systems. Introduce and get set Read More...
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Bioinformatics
Lesson 1: Introduction to Unix and the Shell Lesson Objectives Course overview. Introduce Unix and describe how it differs from other operating systems. Introduce and get set up on DNAnexus and the GOLD system. Discuss ways Read More...
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Bioinformatics
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...
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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
Scatter plots and plot customization Objectives Learn to customize your ggplot with labels, axes, text annotations, and themes. Learn how to make and modify scatter plots to make fairly different overall plot representations. Load a Read More...
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Bioinformatics
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...
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Bioinformatics
Intro_scikit-learn_part2 In [130]: ## Please uncomment the folloing line and run pip install to install scikit-plot for visualization for first run of the notebook. # Once it is installed, you can comment it out again for Read More...
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Bioinformatics
Intro_scikit-learn In [1]: ## Please uncomment the folloing line and run pip install to install scikit-plot for visualization for first run of the notebook. # Once it is installed, you can comment it out again for subsequent Read More...