Bethesda, MD
Collaborative
The COP evaluates novel therapies in pet dogs with cancer to improve outcomes for human patients and established the Comparative Oncology Trial Consortium (COTC), a collaborative effort of NCI and extramural comparative oncology centers at 24 Read More...
Frederick, MD
Collaborative
The Biopharmaceutical Development Program (BDP) provides resources for the development of investigational biological agents. The BDP supports feasibility through development and Phase I/II cGMP manufacturing plus regulatory documentation. The BDP was established in 1993. We Read More...
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CREx News & Updates September 2021 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGLIGHTS Learn more about services from the CCR Read More...
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[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...
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Bioinformatics
class(a1$dose) ## [1] "numeric" As it turns out, dose is really an experimental factor, so if we specify factor(dose) it will be interpreted as a categorical or discrete. Before fixing the x Read More...
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Bioinformatics
class ( a1 $ dose ) ## [1] "numeric" As it turns out, dose is really an experimental factor, so if we specify factor(dose) it will be interpreted as categorical or discrete. Before fixing the x axis Read More...
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Bioinformatics
Above, we learned about the number of tooth length measurements taken at each dose and supplement combination using the default stat="count" transformation of geom_bar . But what if we want to specify Read More...
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Bioinformatics
Let's take a look at a bar plot constructed using the default stat="count" transformation. Below, we plot the number of tooth length measurements taken at each dose. Setting color="black& Read More...
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Bioinformatics
GSEA can be performed using GO (gseGO), KEGG pathways (gseKEGG), KEGG modules (gseMKEGG), and WikiPathways (gseWP). With the DOSE package, you can use DisGeNET (DOSE::gseDGN), Disease Ontology (DOSE::gseDO), and Network of Cancer Genes Read More...
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Bioinformatics
Above, we learned the number of tooth length measurements taken at each dose and supplement combination using the default stat_count transformation of geom_bar, but what if we want to specify and plot exactly Read More...
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Bioinformatics
geom_bar() uses stat_count() by default: it counts the number of cases at each x position. --- ggplot2 documentation stat_count() requires mapping for either an x OR a y variable but not both. Read More...
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Bioinformatics
A barplot is used to display the relationship between a numeric and a categorical variable. --- R Graph Gallery The tooth growth data can be visualized via a bar plot using geom_bar() , as dose Read More...
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Bioinformatics
Until this point we have been plotting raw data with geom_point() , but now we will be introducing geoms that transform and plot new values from your data. Many graphs, like scatterplots, plot the raw Read More...
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Bioinformatics
Until this point we have been plotting raw data with geom_point() , but now we will be introducing geoms that transform and plot new values from your data. Many graphs, like scatterplots, plot the raw Read More...
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Bioinformatics
A barplot is used to display the relationship between a numeric and a categorical variable. --- R Graph Gallery The tooth growth data can also be visualized via bar plot using geom_bar . However, if Read More...
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Bioinformatics
If you are interested in ggpubr, you are likely familiar with ggplot2. As a reminder, ggplot2 is a popular R graphics package associated with a family of packages known as the tidyverse. Tidyverse packages work Read More...
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Bioinformatics
Box and whisker plots also show data distribution. Unlike a histogram, we can readily see summary statistics such as median, 25th and 75th percentile, and maximum and minimum. The default statistical tranformation of a box Read More...
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Bioinformatics
In this section we will learn how to construct bar plots using data obtained from a study that examined the effect that dietary supplements at various doses have on guinea pig tooth length. This data Read More...
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Bioinformatics
In this lesson we will use data obtained from a study that examined the effect that dietary supplements at various doses have on guinea pig tooth length. This data set is built into R, so Read More...
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Bioinformatics
clusterProfiler, along with complementary packages, can easily be used to generate functional enrichment results using over-representation analysis from the following databases: GO, KEGG, DOSE, REACTOME, Wikipathways, DisGeNET, network of cancer genes.
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Bioinformatics
Box and whisker plots also show data distribution. Unlike a histogram, we can readily see summary statistics such as median, 25th and 75th percentile, and maximum and minimum. The default statistical tranformation of a box Read More...
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Bioinformatics
Often, we will use bar plots to illustrate mean plus minus standard deviation in our data so we should learn how to incorporate error bars in our plots. We will learn to do this using Read More...
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Bioinformatics
09/23/2021 - Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m5fa0e43ae167ed5ea3a77fb25d339a82 TOPIC: AI for Multimodal Data, presented by members of the Strategic Data Science Initiative, Read More...
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Bioinformatics
library(clusterProfiler) library(org.Hs.eg.db) library(tidyverse) library(DOSE) library(ReactomePA) library(enrichplot)
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Bioinformatics
The strength of ggplot2 is also its weakness. Using a layered approach means that it can often take quite a bit of code to reach a publishable state, even for routine plots. For new users, Read More...
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Bioinformatics
Some use bar plots to illustrate mean plus / minus standard deviation in the data, so let's take a moment to learn how to incorporate error bars in our data. We will learn to do Read More...
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Bioinformatics
Before diving into the construction of bar plot, box & whisker plot, and histogram, we should do a quick review of the types of variables that we commonly work with in data analysis. Categorical variables Read More...
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Bioinformatics
Stat Transformations: Bar plots, box plots, and histograms Objectives Review the grammar of graphics template Learn about the statistical transformations inherent to geoms Review data types Create bar plots, box & whisker plots, and histograms. Read More...
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Bioinformatics
/* Whole document: */ body{ font-family: Times; font-size: 16pt; } Stat Transformations: Bar plots, box plots, and histograms Objectives Review the grammar of graphics template Learn about the statistical transformations inherent to geoms Review data types Create bar Read More...
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Bioinformatics
09/23/2021 - Registration: https://btep.ccr.cancer.gov/classes/ai_four/ Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m5fa0e43ae167ed5ea3a77fb25d339a82 Description: In this talk, we Read More...
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Bioinformatics
01/07/2021 - Presenter: Gary Patti, Ph.D. Departments of Chemistry, Genetics, and Medicine Washington University in St. Louis It is well established that the metabolism of cancer cells is reprogrammed to support the demands of rapid Read More...
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Bioinformatics
This document contains practice questions on plot customization using ggplot2. All questions use datasets available in base R or in ggplot2. Suggested workflow for students: Attempt each question in your own script or console. Only Read More...
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Bioinformatics
ORA and GSEA support Functionality for multiple ontology and pathway databases Allows user defined databases and annotations, which is particularly useful for non-model organisms Easily compare functional profiles between treatments integrates the tidy philosophy complementary Read More...
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Bioinformatics
Create a script called git_in_rstudio1.R and add the following. Save, stage, commit, and add to GitHub. data("ToothGrowth") library(tidyverse) ggplot(ToothGrowth, aes(x=as.factor(dose), y=len, color= Read More...
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Bioinformatics
Using clusterProfiler you can conduct ORA with GO, KEGG, MKEGG (KEGG modules), and WikiPathways. Using complementary packages (i.e., DOSE, ReactomePA), ORA can also be conducted with Disease Ontology (DO), Reactome, network of cancer genes, Read More...
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Bioinformatics
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...
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Bioinformatics
Required arguments: geneList - the ordered ranked gene list. TERM2GENE - a data frame including the terms and genes (the custom gene sets, which in this case were from MSigDB). Optional arguments: minGSSize - Read More...
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Bioinformatics
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...