Search Results for: 2E8 Cells

Back Services: Biophysics Facility offers DSC as an open-access instrument. First-time users must complete training before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: The differential scanning calorimeter measures the constant pressure Read More...

Back Services: Biophysics Facility offers fluorometers as open-access instruments.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3226 Description: Some substances reemit light after Read More...

Back Services: This instrument is not user accessible.  We provide both data collection and data analysis services. Location: Building 50, room 3331 Description: An analytical ultracentrifuge is equipped with absorption and interference optical systems that monitor Read More...

The CCR Microscopy Core provides NCI investigators access to state-of-the-art imaging tools and techniques, including light sheet fluorescence, high-resolution confocal, multi-photon, and super-resolution microscopy. The mission of the CCR Microscopy Core Facility is to support Read More...

The National Clinical Trials Network Biospecimen Banks (NCTN) receive, store, and distribute human cancer biospecimens collected on NCTN clinical trials . NCTN Biobanks provide cancer researchers with quality, well-annotated biospecimens and associated clinical information. The NCTN 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...

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 NIH Tetramer Core Facility (TCF) provides custom synthesis and distribution of soluble major histocompatibility complex (MHC)-peptide tetramer reagents that can be used to detect antigen-specific T cells. Approved investigators pay all shipping and Read More...

The Spatial Imaging Technology Resource (formerly the Nanoscale Protein Analysis Section of the Collaborative Protein Technology Resource or CPTR) provides expertise and service in state-of-the-art protein analysis technologies to advance CCR research in basic discovery Read More...

The CCR-Frederick Flow Cytometry Core Facility provides research support to the Frederick-CCR community, including cytometry analysis and sorting services, instrument maintenance, new user training, and technical consultation. Typical Assays Performed by Core Instruments Immunophenotyping of Read More...

The facilities at AIM are available for use by the entire NIH intramural research community. While we welcome users with any size imaging project, AIM specializes in large, yearlong (or longer), collaborative research efforts with Read More...

The NCI High-Throughput Imaging Facility (HiTIF) works in a collaborative fashion with NCI/NIH Investigators by providing them with the necessary expertise, instrumentation, and software to develop and execute advanced High-Throughput Imaging (HTI) assays. These 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...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Intramural Core Resources NHGRI Flow Cytometry Core The Core performs high quality single cell analysis through the Read More...

[embed]https://youtu.be/yTl1Q0D7aZ0[/embed] 10x Genomics' supports multiple cancer research areas from single nucleotide and structural variant detection to single cell whole transcriptome gene expression analysis of thousands of individual Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New CREx User Survey The CREx Team is carrying out a CREx User Survey. We would greatly appreciate Read More...

Many established and emerging technologies are available to CCR scientists.  This technology-rich environment makes the CCR a unique place to conduct scientific research.  Through the OSTR, the CCR continues to find 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...

NCI LASP Genome Modification Core (GMC) is a CCR-dedicated facility that provides advice, training, and reagents to NCI scientists seeking to utilize CRISPR and other nucleases to generate genome modifications in primary cells, cell lines, Read More...

Mass Spectrometry Section of the Collaborative Protein Technology Resource (Bldg. 37) Core Capabilities: Identification of proteins in complexes, organelles, subcellular fractions, or fluids. Global relative protein quantitation. Quantitation by isotopic labeling of cells in culture (SILAC) Read More...

The NCI Clinical Research Correlatives Core provides non-CLIA-certified spectral flow cytometric assays to support clinical trials conducted in the CCR. The core specializes in immunophenotyping and immune monitoring assays. Established Technologies Spectral flow cytometry (Cytek), Read More...

The Mass Cytometry Core (MCC) provides access to cutting-edge platforms and expert technical support for high-dimensional single-cell analysis and spatial proteomic profiling. A central expertise of the core is Imaging Mass Cytometry (IMC), which allows Read More...

The Blood Processing Core monitors viral load in patients with HIV and performs sequential studies using samples obtained from patients with cancer, AIDS, chronic granulomatous disease, or other diseases associated with immunologic dysfunction. The core Read More...

September 8, 2022 crex.nih.gov CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Science & Technology Seminars and Training Events Upcoming Seminars and Educational Opportunities The following Read More...

CCR VOLUME Electron Microscopy Core (CVEMC),  formerly known as volume Electron Microscopy (vEM), aims to develop new techniques in volume electron microscopy (vEM) and, in collaboration with CCR Investigators, apply these techniques to research cell Read More...

The Specimen Resource Locator (SRL) is a biospecimen resource database designed to help researchers locate resources that may have the samples needed for their investigational use. This publicly searchable database includes information about biospecimen banks Read More...

The CCR Genomics Core is located in Building 41 on the NIH Bethesda campus. The primary goal of the Core is to provide investigators from CCR/NCI and other NIH Institutes access to genomic technologies and 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...

What is Xenium? Xenium is a high-resolution, imaging-based in situ spatial profiling technology from 10x Genomics that allows for simultaneous expression analysis of RNA targets (currently in range of 100’s) within the same tissue section. Read More...

CREx News & Updates July 2021   Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGHLIGHTS Learn more about services from the NHLBI 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 News & Updates June 2022 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Click below to learn how easy it is to navigate the CREx platform. These short videos will Read More...

CREx News & Updates May 2022 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More Click below to learn how easy it is to navigate the CREx platform. These short videos will Read More...

The NIH Center for Human Immunology, Inflammation, and Autoimmunity (CHI) is a trans-NIH resource whose mission is to provide a collaborative hub of advanced translational immunology for NIH clinical and pre-clinical studies. This uniquely structured Read More...

The Genomics and Pharmacology Facility is part of the NCI's Center for Cancer Research (CCR), within the Developmental Therapeutics Branch. Its mission is to manage and assess molecular interaction data obtained through multiple platforms, increase Read More...

Protein and Metabolite Characterization Core (PMCC), formerly known as the Protein Characterization Lab (PCL),  offers various technologies to CCR investigators to characterize proteins and metabolites. The core develops and applies state-of-the-art analytical technologies, primarily mass Read More...

Our operational objectives are to provide state-of-the-art OMICS technologies in support of the Genetics Branch (GB) investigators and collaborators. Research Services Wet Lab Single cell isolation from fresh, frozen, and FFPE tissue, DNA/RNA extractions 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...

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 Chemistry and Synthesis Center (CSC) of the National Heart, Lung, and Blood Institute (NHLBI) provides IRP scientists with targeted imaging probes and chemical tools that help accelerate cell-based assays, in vivo imaging studies, and Read More...

10/21/2022 - Single cell chromatin accessibility, measured by ATAC-seq, and single cell gene expression, measured by RNA-seq provide two views on a cell’s state. From chromatin accessibility it is possible to infer information about the 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...

The goal of quality control is to keep only high quality cells (i.e., remove low quality cells (dead or dying cells), cell-free RNA, or doublets). Low quality cells will impact downstream analyses. Take care Read More...

In this tutorial, we will continue to use data from Nanduri et al. 2022, Epigenetic regulation of white adipose tissue plasticity and energy metabolism by nucleosome binding HMGN proteins , published in Nature Communications . As a reminder, Read More...

In this tutorial, we will continue to use data from Nanduri et al. 2022, Epigenetic regulation of white adipose tissue plasticity and energy metabolism by nucleosome binding HMGN proteins , published in Nature Communications . As a reminder, Read More...

06/22/2023 - The Bhattacharya Lab at the UCSF Parnassus Campus is focused on the functional role of monocyte-derived macrophages in the onset and persistence of fibrosis in the lung. We are addressing the following major questions, Read More...

04/16/2026 - The ability to measure gene expression levels for individual cells (vs. pools of cells) and with spatial resolution is crucial to address many important biological and medical questions, such as the study of stem Read More...

04/10/2025 - TumorDecon is a computational tool at an early stage of contributing to the intersection of bioinformatics and oncology. The goal of TumorDecon is to estimate the percentages of various immune cells from gene expression Read More...

There are several metrics that can be used to assess overall quality. The base workflow from Seurat suggests the following: nCount_RNA - the absolute number of RNA molecules (UMIs) per cell (i.e., count Read More...

The Seurat v5 object doesn’t require all assays have the same cells. In this case, Cells() can be used to return the cell names of the default assay while colnames() can be used to Read More...

There are a number of ways to explore the PCA results. Two of the more useful visualizations include the DimHeatmap() and ElbowPlot() . DimHeatmap() allows us to visualize the top genes contributing to each PC. Both Read More...

Now, we can either use our filtering parameters directly with subset() or provide a cells argument. # use different parameters; established above adp_filt 350 & nCount_RNA >650 & percent.mt

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...

The total number of detected transcripts expressed in a cell is dependent on the amount of mRNA in a cell. Cells naturally vary in the total amount of mRNA expressed. However, the chemistry of the Read More...

01/03/2024 - on Wednesday, January 3rd at noon in Building 41, Conference Room C507/C509 and online. In-person attendance is encouraged.  Dr. Larson's research is focused on understanding gene expression in eukaryotic Read More...

05/25/2023 - Single-cell technologies, such as single-cell RNA sequencing (scRNA-seq), have increased the resolution achieved in the study of cellular phenotypes, allowing measurements of thousands of different genes in thousands of individual cells. This has created Read More...

01/19/2023 - The National Cancer Institute (NCI) has launched a new virtual seminar series titled NCI Rising Scholars: Cancer Research Seminar Series. This monthly seminar series is an opportunity to highlight the research and the important Read More...

11/05/2025 - This talk delves into the innovative utilization of generative AI in propelling biomedical research forward. By harnessing single-cell sequencing data, we developed scGPT, a foundational model that extracts biological insights from an extensive dataset Read More...

Once we have read in the matrices, the next step is to create a Seurat object. The Seurat object will be used to store the raw count matrices, sample information, and processed data (normalized counts, Read More...

In this tutorial, we are using data from Nanduri et al. 2022, Epigenetic regulation of white adipose tissue plasticity and energy metabolism by nucleosome binding HMGN proteins , published in Nature Communications . The raw count matrices are Read More...

When using SingleR, the 3 primary parameters are the experimental dataset, the reference dataset, and the labels being used. Continuing with the main labels of the MouseRNASeq dataset on the full dataset looks like this: annot = Read More...

The general experimental design was as follows: WT vs DKO mice at two time points, 0 and 6 days. At day 0, cells were in a preadipocyte state, while at day 6 they had differentiated into adipocytes. Each time Read More...

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...

The role of cell clustering is to identify cells with similar transcriptomic profiles by computing Euclidean distances across genes . However, scRNA-Seq experiments include highly dimensional data, with each cell associated with the expression of thousands Read More...

Integration is the process of aligning the same cell types across samples, treatments, data sets, batches, etc. Clustering should represent biological differences and not technical artifacts. Integration is not always necessary. You should run through Read More...

Following normalization, the next step is to find variable features. In most scRNA-seq experiments only a small proportion of the genes will be informative and biologically variable. A subset of cells with high cell to Read More...

The quality of the cells should be assessed considering the above metrics jointly and not simply in isolation. QC can be applied manually by subjectively choosing and applying thresholds, which can be quite arbitrary. Alternatively, 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...

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...

It is next standard to scale and center the features in the data set prior to dimension reduction or visualization via heatmap. Scaling the data will keep highly expressed genes from dominating our analysis. This 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...

04/19/2024 - Dear Colleagues,    This webinar will introduce TumorDecon, a computational tool that's at an early stage of contributing to the intersection of bioinformatics and oncology.   TumorDecon aims to 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...

09/14/2023 - While there is a positive correlation between cancer and aging, the mechanisms underlying this relationship remain unclear. Clonal hematopoiesis, a benign condition that is both associated with aging and predisposes to increased risk of Read More...

02/26/2026 - Scientific discovery is increasingly limited not by data availability, but by our ability to integrate evidence, generate hypotheses, and iteratively test them at scale. Recent advances in foundation models and large language models suggest Read More...

12/16/2025 - Abstract: Spatial transcriptomics (ST) is evolving rapidly as a pivotal technology in studying the biology of tumors and their associated tumor microenvironments (TME). However, where/how it can impact research remain unclear. In this Read More...

10/29/2025 - The Buenrostro lab is broadly dedicated to advancing our knowledge of gene regulation and the downstream consequences on cell fate decisions. To do this, the Buenrostro lab develops new technologies utilizing molecular biology, microscopy Read More...

05/29/2025 - Prostate cancer exhibits significant intratumoral heterogeneity, driving a spectrum of phenotypes ranging from indolent disease to aggressive metastasis, challenging risk stratification and treatment. A key feature of this heterogeneity is clonal diversity, encompassing both Read More...

05/20/2025 - In this talk, Dr. Hwang will discuss three examples of applying single-cell and spatial oncology approaches to the study of pancreatic cancer. First, he will explain how they utilized single-nucleus RNA-sequencing to uncover an Read More...

04/10/2025 - This one hour online training introduces participants to the tools and techniques for analyzing and quantifying microscopy images using MATLAB’s low-code algorithms. Participants will learn how to preprocess images, segment regions Read More...

03/27/2025 - Please note: Registration is required to get the Meeting Link for this event. Please pre-register. Aviv Regev is head of Genentech Research and Early Development. Formerly, Regev was Chair of the Faculty and Core 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...

01/21/2025 - About the Speaker: Hari completed his PhD in Cell Biology at the University of Toronto, where he used single-molecule imaging techniques to reveal how multimolecular interactions govern early signaling events in individual immune cells. 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...

11/06/2024 - Join Our Training on Spatial Omics Data Analysis with MAWA (Multiplex Analysis Web Apps).   Want to learn how to process and analyze your spatial proteomics/transcriptomics data? Join us for four virtual hour-long sessions Read More...

10/29/2024 - Join Our Training on Spatial Omics Data Analysis with MAWA (Multiplex Analysis Web Apps).   Want to learn how to process and analyze your spatial proteomics/transcriptomics data? Join us for four virtual hour-long sessions Read More...

10/22/2024 - Join Our Training on Spatial Omics Data Analysis with MAWA (Multiplex Analysis Web Apps).   Want to learn how to process and analyze your spatial proteomics/transcriptomics data? Join us for four virtual hour-long sessions Read More...

10/15/2024 - Join Our Training on Spatial Omics Data Analysis with MAWA (Multiplex Analysis Web Apps).   Want to learn how to process and analyze your spatial proteomics/transcriptomics data? Join us for four virtual hour-long sessions Read More...

07/11/2024 - Please join us for this special event featuring three speakers on the topic of Single-Cell Spatial Transcriptomics. George Zaki, Ph.D., Director, Applied Scientific Computing, BACS, The Frederick National Lab for Cancer Research, NCI/ Read More...

06/10/2024 - Please join us for the next talk in our single cell and spatial interest group series.    Dr. Jasmine Plummer is a faculty member and the Director of St. Jude Children' Read More...

Now that we have loaded the package, we can import our data. Generally, in R programming, functions that involve data import begin with "read / Read". Seurat includes a number of read functions for Read More...

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 will Apply 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...

The metadata in the Seurat object is located in adp@metadata and contains the information associated with each cell. We can access the metadata using: head(adp@meta.data) #using head to return only the 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...

Clustering is used to group cells by similar transcriptomic profiles. Seurat uses a graph based clustering method. You can read more about it here . The first step is to compute the nearest neighbors of each 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...

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...

To look at how these metrics correlate, we can use FeatureScatter() , which can be used to visualize feature-feature relationships and also be applied to other data stored in our Seurat object (e.g., metadata columns, Read More...

03/05/2024 - This in-person workshop will show participants how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Cell Read More...

The geom functions require a mapping argument. The mapping argument includes the aes() function, which "describes how variables in the data are mapped to visual properties (aesthetics) of geoms" (ggplot2 R Documentation). If Read More...

01/10/2024 - Our series of talks continues next month with two 20-minute presentations focused on single cell genomics studies in the model organism zebrafish.  There will be light refreshments and we encourage attendees to Read More...

For any next generation sequencing experiment, you will need sample information (sample metadata) to make sense of your data. The key to a good study is to collect good metadata. You should minimally have all Read More...

The geom functions require a mapping argument. The mapping argument includes the aes() function, which "describes how variables in the data are mapped to visual properties (aesthetics) of geoms" (ggplot2 R Documentation). If Read More...

11/16/2023 - This class will provide a demonstration of how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Read More...

10/04/2023 - Our series of talks continues this month with two 20-minute presentations.  There will be light refreshments and we encourage attendees to stay and chat with colleagues after the presentations.   & Read More...

09/29/2023 - Dr. Peng Jiang started his research program at NCI in July 2019. His lab focuses on developing big data and artificial intelligence frameworks to identify biomarkers and new therapeutic approaches for cancer immunotherapies in solid 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...

09/08/2023 - Hybrid Seminar Friday, September 8, 2023 • 9:00-10:00 a.m. Building 549 Auditorium (In-person attendance encouraged)   Speaker: Brian Kelsall, M.D. Senior Investigator, Mucosal Immunobiology Section Laboratory of Molecular Immunology National Institutes of Allergy Read More...

There are many databases devoted to relating genes and gene products to pathways, processes, and other phenomenon. Again, the following is not meant to be a comprehensive list. Kyoto Encyclopedia of Genes and Genomes (KEGG) Read More...

Let's submit a batch job. We are going to download data from the Sequence Read Archive (SRA) , a public repository of high throughput, short read sequencing data. We will discuss the SRA a bit Read More...

The geom functions require a mapping argument. The mapping argument includes the aes() function, which "describes how variables in the data are mapped to visual properties (aesthetics) of geoms" (ggplot2 R Documentation). If Read More...

04/26/2023 - In this month’s Cancer Genomics Cloud (CGC) webinar, Dr. Tolga Can of the Colorado School of Mines will share how he and members of the Erson-Bensan Lab are using publicly available Read More...

04/13/2023 - In this hands-on virtual lab, the participants will familiarize themselves with Deep Learning concepts and techniques, using MATLAB Online to train deep neural networks on GPUs in the cloud, create Read More...

04/06/2023 - Az imuth is a web application that uses an annotated reference dataset to  automate the processing, analysis, and interpretation of a new single-cell RNA-seq experiment . Azimuth leverages a  'reference-based mapping' pipeline that inputs a Read More...

The identification of cell types in single cell genomics data (cell type annotation) can provide new insights into cellular identities, heterogeneity, and functional roles. Cell type annotation is challenging Read More...

The geom functions require a mapping argument. The mapping argument includes the aes() function, which "describes how variables in the data are mapped to visual properties (aesthetics) of geoms" (ggplot2 R Documentation). If Read More...

11/17/2022 - In this hands-on virtual lab, the participants will familiarize themselves with Deep Learning concepts and techniques, using MATLAB Online to train deep neural networks on GPUs in the cloud, create deep learning models from Read More...

11/16/2022 - Join Drs. Jennifer E. Beane-Ebel and Vijaya B. Kolachalama of Boston University as they discuss their studies of pathological and molecular alterations associated with lesion severity and progression. Topics include deep learning methods for Read More...

10/26/2022 - In partnership with NCI’s Cancer Moonshot SM  Initiative, the Society for Immunotherapy of Cancer (SITC) and the  Big Data  and  Data Sharing  Committee are hosting the eighth of nine webinars that make up Read More...

10/19/2022 - Speaker: Ron Germain, M.D., Ph.D. NIH Distinguished Investigator NIAID, NIH Dr. Germain received his Sc.B. and Sc.M. from Brown University in 1970 and his M.D. and Ph.D. from Harvard 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...

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...

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...

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...

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...

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...

Data visualization with ggplot2 Objectives To learn how to create publishable figures using the ggplot2 package in R. By the end of this lesson, learners should be able to create simple, pretty, and effective figures. 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...

Lesson 2: Getting Started with QIIME2 Lesson Objectives Obtain sequence data and sample metadata Import data and metadata Discuss other useful QIIME2 features including view QIIME2, provenance tracking, and the QIIME2 forum. DNAnexus DNAnexus provides a Read More...

Introduction to ggplot2 Objectives Learn the ggplot2 syntax. Build a ggplot2 general template. By the end of the course, students should be able to create simple, pretty, and effective figures. Data Visualization in the tidyverse 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...

Below, you will find questions and answers brought up in the course polls for the BTEP Bioinformatics for Beginners course series that took place from September 13th, 2022 to December 13th, 2022. Question 1 : Normalization - when to Read More...

BTEP Bioinformatics for Beginners (September 13th, 2022 - December 13th, 2022) Questions and Answers Below, you will find questions and answers brought up in the course polls for the BTEP Bioinformatics for Beginners course series that took Read More...

Lesson 5: Working on Biowulf Lesson 4 Review Flags and command options Wildcards ( * ) Tab complete Accessing user history with the "up" and "down" arrows cat , head , and tail Working with file content (input, Read More...

Gene ontology and pathway analysis Objectives Determine potential next steps following differential expression analysis. Tour geneontology.org and understand the three main ontologies. Learn about different methods and tools related to functional enrichment and pathway Read More...

High resolution single cell profiling assays have provided an unprecedented view of many biological systems and processes, but the spatial context in which this biology is occurring is often crucial. Spatial profiling, including spatial transcriptomic Read More...

Introduction to ggplot2 Objectives Learn how to import spreadsheet data. Learn the ggplot2 syntax. Build a ggplot2 general template. By the end of the course, students should be able to create simple, pretty, and effective Read More...

Data visualization with ggplot2 Objectives To learn how to create publishable figures using the ggplot2 package in R. By the end of this lesson, learners should be able to create simple, pretty, and effective figures. Read More...