Bethesda, MD
Core Facility
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...
Frederick, MD
Core Facility
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...
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Discover expert help with analysis, processing applications, and licensed software packages.
Bethesda, MD
Collaborative
The Mass Spectrometry Unit of the Collaborative Protein Technology Resource uses mass spectrometry for the study of proteins. We perform collaborative experiments with CCR researchers in areas such as: interactomes, quantitative global proteome analyses, and Read More...
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Cores & Facilities From centralized laboratories to collaborative resources and technologies available to CCR Investigators. NCI Cores Centralized laboratories providing broad access to cutting-edge technologies and specialized expertise. Browse NCI Cores Collaborative Resources are technologies and Read More...
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Bioinformatics
DAVID works best with gene lists comprised of <= 3000 genes, and the Functional Annotation Clustering and Gene Functional Classification tools have a 3000 gene limit.
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Bioinformatics
"The goal of DAVID's design is to be able to efficiently upload and analyze a list consisting of
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Bioinformatics
"The goal of DAVID's design is to be able to efficiently upload and analyze a list consisting of
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
Database for Annotation, Visualization and Integrated Discovery (DAVID) - an overview Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 17 review In the previous class, we got an overview of Read More...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
Database for Annotation, Visualization and Integrated Discovery (DAVID) - an overview Lesson 17 review In the previous class, we got an overview of functional and pathway analysis, which help to put RNA sequencing results into biological 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
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...
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Bioinformatics
This page contains content taken directly from the Biostar Handbook (Istvan Albert). Always remember to activate the class bioinformatics environment. conda activate bioinfo For this data analysis, we will be using: Two commercially available RNA Read More...
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Bioinformatics
This page contains content taken directly from the Biostar Handbook (Istvan Albert). Always remember to activate the class bioinformatics environment. conda activate bioinfo For this data analysis, we will be using: Two commercially available RNA Read More...
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Bioinformatics
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...