Search Results for: negative staining

05/19/2021 - Register Kinase inhibitors have been intensively studied and used effectively for cancer treatment for decades. Yet, despite our progress in understanding kinases in oncology, more needs to be known to better predict how and Read More...

These sets of exercises will create the following plots from the hbr_uhr_deg_chr22 and hbr_uhr_top_deg_normalized_counts data tables. Volcano plot for hbr_uhr_deg_chr22 using Python's Seaborn Read More...

These sets of exercises will create the following plots from the hbr_uhr_deg_chr22 and hbr_uhr_top_deg_normalized_counts data tables. Volcano plot for hbr_uhr_deg_chr22 using Python's Seaborn Read More...

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...

Imported using R and Python Contains RNA sequencing differential expression analysis results. The columns are: name: contains gene names log2FoldChange: gene expression change between two experimental conditions on the log2 scale PAdj: adjusted p-value Read More...

Imported using R and Python Contains RNA sequencing differential expression analysis results. The columns are: name: contains gene names log2FoldChange: gene expression change between two experimental conditions on the log2 scale PAdj: adjusted p-value Read More...

Enrichment Score and normalized enrichment score. Enrichment Score - represents the degree to which a set is over-represented at the top or bottom of the ranked list. normalized enrichment score (NES) - allows comparability across Read More...

[tabby title="Home"] About NICE-NIH Intramural CryoEM Consortium  NIH Intramural CryoEM Consortium (NICE) serves intramural investigators in all NIH IC’s. NICE provides access to state-of-the-art Titan Krios cryo-electron microscopes for atomic-resolution structure determination of Read More...

The Mid-Atlantic CHTN is one of six participating divisions of the Cooperative Human Tissue Network (CHTN) and is based in the Pathology Department at the University of Virginia. While primarily a resource for cancer researchers, 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...

Clinical Support Laboratory – Flow Cytometry Section is a laboratory specializing in providing immunophenotyping support of NCI intramural clinical trials, though assessments may also be performed using cells from Non-human primates and other species. The CSL Read More...

2024 Coutinho, L. L., Femino, E. L., Gonzalez, A. L., Moffat, R. L., Heinz, W. F., Cheng, R. Y. S., Lockett, S. J., Rangel, M. C., Ridnour, L. A. & Wink, D. A. NOS2 and 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...

In lesson 3, we learned how to read and save excel spreadsheet data to a R object using the tidyverse package readxl . Today we will use some example data from an excel spreadsheet to learn the Read More...

In tab delimited files, data columns are separated by tabs. To import tab-delimited files there are several options. There are base R functions such as read.delim() and read.table() as well as the readr Read More...

Differential Expression 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. Normalization and Statistical Significance Read More...

Plots condense complex and busy tabular data into a form that is easier to interpret. An expression heatmap is a common visualization used in RNA sequencing analysis. A heatmap shows numerical data on a color 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...

Let's draw an image on here, just to show that we can add one. There are two options. We can add an image as if it was another figure or we can simply draw Read More...

Excel is a great program for visualizing and manipulating small data sets. However, it isn't great for working with "big data", and resulting plots are generally not publishable. Learning R and associated Read More...

05/19/2022 - THIS EVENT HAS BEEN CANCELLED Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood and are subdivided into three major histomorphologic subtypes: alveolar (ARMS), embryonal (ERMS), or spindle/sclerosing (SSRMS).  Patients with Read More...

05/19/2021 - Register/Join Kinase inhibitors have been intensively studied and used effectively for cancer treatment for decades. Yet, despite our progress in understanding kinases in oncology, more needs to be known to better predict how Read More...

03/17/2021 - Presenter: Himel Mallick, PhD Senior Scientist, Biostatistics Merck Research Laboratories Abstract Identifying clinically actionable features that display differential abundance and expression patterns across experimental conditions is an important first step toward characterizing the multi-omics Read More...

09/04/2020 - Speakers: Dave Clements, Galaxy Community Manager, Johns Hopkins University, Steven Weaver, Senior Programmer Analyst, Temple University Galaxy is an open web-based platform for data integration and analysis in the life sciences. Galaxy makes sophisticated Read More...

The example data we will use for plotting are from a bulk RNA-Seq experiment described by Himes et al. (2014) and available in the Bioconductor package airway. In this experiment, the authors were comparing transcriptomic differences Read More...

Here we will use bulk RNA-Seq data available in the R package airway, which is from an experiment published by Himes et al. (2014). These data, which are available in R as a RangedSummarizedExperiment object, are Read More...

These example data are from a bulk RNA-Seq experiment described by Himes et al. (2014) and available in the Bioconductor package airway. ::: {.cell} #data import from excel exdata<-readxl::read_xlsx("./data/RNASeq_ Read More...

Users will be working with data tables during analyses. These can be imported into the a Jupyter Notebook although the approach for doing so will be language dependent. The example below will use a Python Read More...

Users will be working with data tables during analyses. These can be imported into the a Jupyter Notebook although the approach for doing so will be language dependent. The example below will use a Python Read More...

This exercise will use the differential gene expression analysis table from the hbr and uhr study. hbr_uhr_deg_chr22=pandas.read_csv("./hbr_uhr_deg_chr22.csv") The info() attribute will retrieve Read More...

For this exercise, stay in the /data/username/pies_2023 folder, which should be the present working directory (use pwd to check). If not in the /data/username/pies_2023 folder, change into it. Copy the hbr_ Read More...

Plots condense complex and busy tabular data into a form that is easier to interpret. An expression heatmap is a common visualization used in RNA sequencing analysis. A heatmap shows numerical data on a color Read More...

For today's lesson, we will use data derived from the Bioconductor package airway. The airway data is from Himes et al. (2014). These data, which are contained within a RangedSummarizedExperiment, object are from a bulk Read More...

Step 1: Import the data my_file <- paste0(data_path,"/","airway_deg_results.csv") airway_deg <- read.csv(my_file,check.names=FALSE,row.names=1) EnhancedVolcano Read More...

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The CLIA Molecular Diagnostics Laboratory (CMDL) provides an array of services for groups at the NIH Clinical Center, Fort Detrick, and Hood College, among others. They support cancer- and disease-related research by making 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 Biological Products Core provides the AIDS research community with high-quality purified preparations of various strains of Human Immunodeficiency Virus (HIV) and Simian Immunodeficiency Virus (SIV), economically prepared by leveraging the economy of scale. Materials Read More...

CLIA-Certified Technologies Offered: Fragment Analysis for Micro-satellite Instability Detection, Pharmacoscan Array for Pharmacogenomics, Mutation Detection for PCR and Sanger Sequencing, DNA extraction from whole blood, saliva, FFPE tissues, buccal swabs, nails, hair, PBMCs, buffy coats, Read More...

The Clinical Support Laboratory offers processing, tracking, and testing of a broad range of clinical samples. Support can begin at the early stages of clinical trial development to aid in developing a comprehensive strategy for 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...

Protein Characterization Laboratory (PCL) offers various technologies to CCR investigators to characterize proteins and metabolites. The laboratory develops and applies state-of-the-art analytical technologies, primarily mass spectrometry, liquid chromatography, and Surface Plasmon Resonance (SPR), to advance Read More...

Protein Characterization Laboratory (PCL) offers various technologies to CCR investigators to characterize proteins and metabolites. The laboratory develops and applies state-of-the-art analytical technologies, primarily mass spectrometry, liquid chromatography, and Surface Plasmon Resonance (SPR), to advance Read More...

2024 Date: Tuesday, October 15, 2024 Time and Location: 11 am EST, ZOOM (INVITATION BY LMIG LIST SERVER) Speaker: Dr. Diego Presman (U Buenos Aires) Title: “Insights on Glucocorticoid Receptor Activity Through Live Cell Imaging” Summary: Eucaryotic transcription factors ( 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...

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...

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...

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...

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...

Data import and reshape Objectives 1. Learn to import multiple data types 2. Data reshape with tidyr : pivot_longer() , pivot_wider() , separate() , and unite() Installing and loading packages So far we have only worked with objects that Read More...

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...

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...

Multi-figure panel Objectives Combine multiple plots into a single figure Learn how to use patchwork and cowplot The primary purpose of this lesson is to learn how to combine multiple figures into a single multi-panel 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 frames Objectives To be able to load, explore, and access data in a tabular format. To this end, students should understand the following: 1. how to import and export data 2. how to create, summarize, and Read More...

Tasks to do at the Analysis Wizard: Provide an input gene list (either copy paste or upload as a text file) Specify the gene identifier type. Gene identifiers can be gene symbol, Ensembl IDs, Entrez Read More...

The next exercise is to practice creating a scatter plot on a biologically relevant dataset. Namely, the differential expression results from the hbr and uhr RNA sequencing study will be used to create a scatter Read More...

In tab delimited files, data columns are separated by tabs. To import tab-delimited files there are several options. There are base R functions such as read.delim() and read.table() as well as the readr Read More...

The next exercise is to practice creating a scatter plot on a biologically relevant dataset. Namely, the differential expression results from the hbr and uhr RNA sequencing study will be used to create a scatter Read More...

To start learning how to track changes using Git, a text file called mars will be created in the directory /Users/tillodc/teaching/planets. This file will contain notes about the planet mars. Note that Read More...

The resulting object eh is a gseaResult object. This object contains the results (eh@result) and other information that went into the analysis, for example, @organism type, @setType, the @geneSets used, the genes in our @ Read More...