Search Results for: differential scanning fluorimetry (DSF)

The primary means of running differential expression in Seurat is through the FindMarkers function. The main usage for this function is as follows: FindMarkers(object,ident.1= ..., ident.2=..., test.use="wilcox", min.pct = 0.01, logfc. Read More...

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...

Differential abundance testing examines which taxa are significantly different in abundance between conditions. However, challenges such as sparsity, compositionality, and library size differences make this challenging to determine.

09/20/2023 - This session of the BTEP Coding Club will focus on the tool rMATS for differential alternative splicing event detection from RNA-Seq data. This 1-hour demo will provide a detailed overview of rMATS including why Read More...

Next, how do we generate the differential expression results? {{Sdet}} Solution{{Esum}} Rscript $CODE/deseq2.r {{Edet}}

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...

Differential expression involves the comparison of normalized expression counts of different samples and the application of statistical measures to identify quantitative changes in gene expression between the different samples.

The Biophysics Core’s mission is to provide support in the study of macromolecular interactions, dynamics, and stability by offering consultations, training, professional collaborations, and instrument access. General Services: Multi-technique molecular interaction studies, Kinetic and Read More...

03/11/2025 - In this class, participants will get hands-on experience with generating and interpreting differential gene expression analysis results from bulk RNA sequencing. In addition, participants will learn to generate common plots used to visualize bulk Read More...

03/06/2025 - This class introduces participants to the first steps to differential expression analysis in bulk RNA sequencing which involves filtering out noise from (ie. genes without expression across samples) and performing QC on the gene Read More...

One particular critique of differential expression in single cell RNASeq analysis is p-value "inflation," where the p-values get so small that there are far too many genes exist with p-values below 0.05, even after 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...

From the paper where this data was obtained, the following (incomplete) list of gene markers was obtained: Mmp3: preadipocytes Mki67: proliferating cells Fabp4: differentiating beige adipocytes and differentiated beige adipocytes Scd1: differentiated beige adipocytes Ucp1: Read More...

In Seurat (since version 4), differential analysis requires a preprocessing step to appropriately scale the normalized SCTransform assay across samples: adp = PrepSCTFindMarkers(adp) Found 8 SCT models. Recorrecting SCT counts using minimum median counts: 8146 As covered earlier, Read More...

Electron Microscopy Laboratory (EML) The EML offers investigators access to unique expertise and EM technologies that allow our partners to explore new avenues of research to enhance the knowledge of biological systems. To assist our Read More...

This page contains content taken directly from the Biostar Handbook by Istvan Albert. Always remember to start the bioinformatics environment. conda activate bioinfo We will be analyzing differential expression of genes on Chr22 from the Read More...

This page contains content taken directly from the Biostar Handbook by Istvan Albert. Always remember to start the bioinformatics environment. conda activate bioinfo We will be analyzing differential expression of genes on Chr22 from the Read More...

01/22/2025 - This three hour online training covers QIAGEN’s CLC Genomics Workbench enables researchers to analyze NGS data without the use of command line and is a powerful tool for determining differential expression. Read More...

Single cell RNASeq is a remarkably powerful tool for analyzing populations of cells that can be recovered from various experiments. Clustering and cell type annotation can be used to distinguish different populations with a level Read More...

library(tidyverse) # dplyr and ggplot2; CRAN library(Seurat) # Seurat toolkit; CRAN library(hdf5r) # for data import; CRAN library(patchwork) # for plotting; CRAN library(presto) # for differential expression; Github library(glmGamPoi) # for sctransform; Bioconductor library( Read More...

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 have already been filtered 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...

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...

The NCI Research Flow Facility provides cell sorting and benchtop flow cytometry services to NCI investigators. Services are program-specific and are not available to all NCI or NIH investigators. Please inquire as to availability. Established Read More...

CCR VOLUME Electron Microscopy (CVEM) aims to develop new techniques in volume electron microscopy (vEM) and, in collaboration with CCR Investigators, apply these techniques to research cell biological questions well-suited for study by high-resolution 3D Read More...

The EML offers investigators access to unique expertise and EM technologies that allow CCR Investigators to explore new avenues of research in order to enhance the knowledge of biological systems. To assist our customers, we Read More...

The LCBG Microscopy Core offers imaging technologies and training. The Core has established instrumentation for for 2D and 3D imaging of both fixed and living specimens.

OMAL focuses its research and development activities to quantitatively understand the molecular basis of three-dimensional (3D) cell organization, motility, invasion, and differentiation using fixed samples and live, 3D tissue culture models (i.e., translational models). Read More...

LCMB Microscopy Core offers live cell imaging technologies as well as super-resolution, fluorescence lifetime and confocal imaging systems for immunofluorescence. Our confocal instruments are a Leica SP8 laser scanning confocal microscope and a Nikon spinning Read More...

MAB provides visual communication solutions across all media to the entire NIH community. Our Medical Illustration section provides a complete range of biomedical visualization services, including manuscript/textbook figures, infographics, 3D modeling, animation, technical diagrams, Read More...

Home About the Biophysics Core Biophysics Core Services [tabby title="Instrumentation"] NHLBI Biophysics Core The Biophysics Core Facility: Overview Core Facilities provide scientific resources, cutting-edge technologies and novel approaches to support DIR scientists. Availability of Read More...

The Biomedical Engineering and Physical Science (BEPS) shared resource supports NIH’s intramural basic and clinical scientists on applications of engineering, physics, imaging, measurement, and analysis. BEPS is centrally located on the main NIH campus 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...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More. New Resources on CREx NIMH Human Brain Collection Core (HBCC) The HBCC obtains human brain tissue, hair, and blood Read More...

06/18/2025 - Gene et enrichment analy i (G EA) i a popular tool for evaluating functional enrichment, e pecially following differential expre ion analy i . Thi e ion of the BTEP Coding Club will how attendee Read More...

05/21/2025 - The programming language R i ideal for biomedical re earcher a it ha package that facilitate Next Generation equencing (NG ) data analy i . For example, bulk RNA equencing differential expre ion analy i can Read More...

04/08/2025 - Reactome is a free, open-source, curated and peer-reviewed pathway database that includes bioinformatics tools for the visualization, interpretation and analysis of pathway knowledge. This lesson will showcase the capabilities of Reactome in garnering biological Read More...

03/20/2025 - Please note: Registration is required to get the Meeting Link for this event. Please pre-register. BTEP and the Single Cell and Spatial Transcriptomics Interest Group jointly present: Quantifying spatiotemporal dynamics during embryogenesis is crucial Read More...

03/13/2025 - UCSC Xena showcases seminal cancer genomics datasets from The Cancer Genome Atlas (TCGA) and the Pan-Cancer Atlas, as well as the Genomic Data Commons, Pan-cancer Atlas of Whole Genomes, and the International Cancer Genome Read More...

12/12/2024 - This class will introduce bulk RNA sequencing analysis using Qiagen software. Participants will learn how to process FASTQ files and obtain differential expression using CLC Genomics Workbench as well as extract biological insight using Read More...

What is bioinformatics? Bioinformatics integrates biology, statistics, and computer science to develop and apply theory, methods, and tools for the collection, storage, and analysis of biological and related data. Bioinformatics plays a critical role in Read More...

11/08/2024 - Learn microbiome analysis basics in R with phyloseq. This workshop will cover different types of analysis frequently used in microbiome studies, including sample diversity, community composition, and differential taxa. The techniques we learn will Read More...

10/09/2024 - This session will give an overview of the NCI Cancer Research Data Commons and the variety of available cancer data such as RNA expression and protein abundance. These data are hosted in openly accessible Read More...

06/13/2024 - The schedule for this week consists of one presentation: Lorenz Adlung, UMC Hamburg-Eppendorf, will discuss: scMod: Marrying machine learning and deterministic modelling of longitudinal single-cell data Single-cell-based methods such as flow cytometry or single-cell Read More...

library(tidyverse) # dplyr and ggplot2 library(Seurat) # Seurat toolkit library(hdf5r) # for data import library(patchwork) # for plotting library(presto) # for differential expression library(glmGamPoi) # for sctransform Warning: package 'glmGamPoi' was built under R 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...

Now, that we have clusters, we can use differential expression analysis to uncover markers that define our clusters. These markers can be used to assign cell types to our clusters. First, because we are working 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...

05/08/2024 - Qlucore Omics Explorer is a point-and-click software that enables analysis of RNA sequencing (bulk and single cell), proteomics and metabolomics data. It’s machine learning capabilities also allow for classification of cell types. This 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...

03/20/2024 - Our series of talks continues with two 20-minute presentations.  There will be light refreshments (coffee and donuts) provided, so please consider attending in person! We encourage attendees to stay and chat with Read More...

03/13/2024 - Dear Colleagues,    UCSC Xena is a web-based visual integration and exploration tool for multi-omic data and associated clinical and phenotypic annotations.   Xena showcases seminal cancer genomics datasets from Read More...

After this class, participants will Become familiar analyzing single cell RNA sequencing data using Partek Flow including Importing of data into a Partek Flow project QA/QC, filtering, and normalizing of single cell RNA data 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...

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...

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...

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...

Let's create a column in our original differential expression data frame denoting significant transcripts (those with an FDR corrected p-value less than 0.05 and a log fold change greater than or equal to 2). dexp_sigtrnsc Read More...

Let's create a column in our original differential expression data frame denoting significant transcripts (those with an FDR corrected p-value less than 0.05 and a log fold change greater than or equal to 2). ::: {.cell} dexp_ 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...

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...

There are data sets available in R to practice with or showcase different packages. For today's lesson and the remainder of this course, we will use data from the Bioconductor package airway to showcase Read More...

There are some immediate problems with the data. The column names begin with numbers, which are not syntactic with R. The gene names are hybrids of Ensembl ID and gene symbols and will match neither Read More...

First, we will want to fix the three immediate problems discussed above. Once those have been fixed, we are going to create a bar plot, using ggplot2 to plot the total gene counts per sample. Read More...

To subset by column, we use the function select() . We can include and exclude columns, reorder columns, and rename columns using select() . Select a few columns from our differential expression results ( dexp ). We can select Read More...

mutate() adds new variables and preserves existing ones; transmute() adds new variables and drops existing ones. New variables overwrite existing variables of the same name. --- dplyr.tidyverse.org Let's create a column in 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...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Resources Advance your research with the NIH Mouse Imaging Facility (MIF) The NIH Mouse Imaging Read More...

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...

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...

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 Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Resources Derive Greater Insights and Accelerate your Research Using Bioinformatic Tools! CREx is an NIH Read More...

Services: Biophysics Facility offers CD as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the difference Read More...

Back Services: Biophysics Facility offers CD as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the Read More...

Back Services: We offer a limited sample processing service using standard SEC-MALS and FFF protocols.  This service is intended for the occasional users of this system.  Researchers who expect to use this instrument Read More...

Back Services: We offer a limited sample processing service using standard SEC-MALS and FFF protocols.  This service is intended for the occasional users of this system.  Researchers who expect to use this instrument 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...

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...

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...

Anaconda ( https://www.anaconda.com/ ) is a package manager and distributor for a wide array of data science software. Package managers are ideal for scientists who conduct analysis on a personal computer as they eliminate 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...

Register now for an upcoming seminar on January 22, 2025 , “Revealing Tumor-Promoting Signals in Breast Cancer Subtypes: A NIDAP Analysis of Single-Cell Data” . This one-hour talk will feature guest speaker and NIDAP developer, Josh Meyer, who will Read More...

12/05/2024 - This one and a half hour online training 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 Read More...

11/19/2024 - 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 a point-and-click software hosted on Biowulf, the NIH Read More...

06/12/2024 - Join us for an engaging training session where we will examine the similarities and differences between machine learning and statistical differential gene expression (DGE) analysis using Qlucore Omics Explorer. Qlucore Omics Explorer is a Read More...

Many experiments look to compare to distinct populations, and scRNASeq is no exception. The two populations being compared can vary wildly from experiment to experiment; some look to draw comparisons based on the experimental condition, Read More...

As we can see above, the glimpse command shows the metadata that can be used to classify the cells. Within Seurat, the metadata is used to define the "identity" of the dataset. This 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...

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...

The FindAllMarkers function is particularly useful in identifying the differentially expressed genes that distinguish several groups, such as seen here in the clusters. What makes this unique is that none of the identities are initially Read More...

Learning Objectives This tutorial was 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. Throughout this tutorial we 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...

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...

These steps can be used to create a publish worthy figure. For example, let's create a volcano plot of our differential expression results. A volcano plot is a type of scatterplot that shows statistical Read More...

To explore tidyverse functionality, let's read in some data and take a look. #let's use our differential expression results dexp "ENSG00000000003", "ENSG00000000419", "ENSG00000000457", "E… $ albut untrt, Read More...

Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review 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...

Learning Objectives Learn about data structures including factors, lists, data frames, and matrices. Load, explore, and access data in a tabular format (data frames) Learn to write out (export) data from the R environment Data 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...

01/19/2024 - Trey Ideker, Ph.D., is a professor of medicine, bioengineering, and computer science, and former chief of genetics at the University of California San Diego (UCSD). Additionally, he is director or co-director of the Read More...

Work through DNAnexus? Find a nice cancer data set for 16S and shotgun Divide into two workshops or courses? Course structure or workshop structure? Amplicon processing and analysis (5 week course) (4 weeks) 1. Talk by Greg Caparaso? 1. Read More...

Microbiome Course Course Outline Work through DNAnexus? Find a nice cancer data set for 16S and shotgun Divide into two workshops or courses? Course structure or workshop structure? Amplicon processing and analysis (5 week course) (4 weeks) 1. Read More...

Let's load in some data to work with. In this lesson, we will continue to use sample metadata, raw count data, and differential expression results from the airway RNA-Seq project. Load the data: #sample Read More...

For this lesson, we will use sample metadata and differential expression results from the airway RNA-Seq project. Let's begin by importing the data. #sample information smeta ## 1 GSM1275862 N61311 untrt untrt SRR10395… 126 SRX384345 SRS50… SAMN0242… ## 2 Read More...

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...

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...

Objectives Review important data wrangling functions Put our wrangling skills to use on a realistic RNA-Seq data set Data Wrangling Review Important functions by topic Importing / Exporting Data Importing and exporting data into the R 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...

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...

NCI scientists have many choices available to them for bioinformatic analyses of Next Generation Sequencing (NGS) data. While some require expertise in programming, others provide a more user-friendly, point-and-click interface. These options include programs for Read More...

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...