NATIONAL CANCER INSTITUTE - CANCER.GOV

Search Results for: Msh6 null

Total Results Found: 46

Total Results Found: 46

NCI LASP Mouse Modeling & Cryopreservation (MMC)
Frederick, MD

Core Facility

Repositories

The Mouse Modeling Core assists NIH investigators by generating and preserving genetically-engineered mouse strains. Services include scientific consultation, gene-targeting in mouse embryonic stem cells, micro-injection of nucleic acids, proteins, or ES cells into mouse embryos, Read More...

R Introductory Series: Mutate

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Bioinformatics

Another useful data manipulation function from dplyr is mutate() . mutate() allows you to create a new variable from existing variables. Perhaps you want to know the ratio of two columns or convert the units of Read More...

R Introductory Series: Mutate

Web Page

Bioinformatics

Another useful data manipulation function from dplyr is mutate() . mutate() allows you to create a new variable from existing variables. Perhaps you want to know the ratio of two columns or convert the units of Read More...

BTEP Coding Club: Indexing errors

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Bioinformatics

Indices in R start with 1. Incorrect usage of indexing in data structures such as vectors or data frames will not necessarily result in an error, but will often lead to unexpected results. A general subscript Read More...

BTEP Coding Club: Indexing errors

Web Page

Bioinformatics

Indices in R start with 1. Incorrect usage of indexing in data structures such as vectors or data frames will not necessarily result in an error, but will often lead to unexpected results. A general subscript Read More...

R Introductory Series: Object data types

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Bioinformatics

The data type of an R object affects how that object can be used or will behave. Examples of base R data types include numeric, integer, complex, character, and logical. R objects can also have Read More...

R Introductory Series: Getting help

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Bioinformatics

Now we know a bit about using functions, but what if I had no idea what the function round() was used for or what arguments to provide? Getting help in R is fairly easy. In Read More...

Microbiome Analysis with QIIME2: Methods in QIIME 2

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Bioinformatics

ANCOM (Analysis of Composition of Microbiomes) additive log ratio approach assumes that less than 25 % of features change between groups q2-composition plugin Need to filter rare taxa w-statistic - the number of null hypotheses rejected Read More...

R Introductory Series 2023: Object data types

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Bioinformatics

R objects have certain attributes, and these attributes will be important for how they can interact with certain methods / functions. Understanding the mode (storage type) or the class of an object will be important for Read More...

BTEP Coding Club: Lollipop plot

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Bioinformatics

These are the same results exhibited differently. Notice the seamless integration with tidyverse functionality. clusterProfiler extends ggplot2 functionality to accept enrichment results directly. s_ego %>% filter(p.adjust < 0.03) %>% ggplot( Read More...

BTEP Coding Club: Using clusterProfiler dplyr verb extensions

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Bioinformatics

We can use clusterProfiler extensions of dplyr verbs (mutate(),filter(),select(),summarize(),slice(),group_by(),arrange()) for easy manipulation of enrichResult, gseaResult, and compareClusterResult objects. mutate() can be particularly powerful and allow us to use Read More...

R Introductory Series: Base R and data frames

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Bioinformatics

Lesson 3 Exercise Questions: BaseR dataframe manipulation and factors 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 . We are going Read More...

Data Visualization with R: Perform PCA

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Bioinformatics

We can use the function prcomp() to run PCA on the first four columns of the iris data. The function takes numeric data. colnames(iris)[1:4] ## [1] "Sepal.Length" "Sepal.Width" "Petal. Read More...

Data Visualization with R: Save as an R object

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Bioinformatics

Below, we assign the heatmap to the R object hm_ph. hm_ph {"x":{"data":[{"x":[4.875,2.875,null,2.875,2.875,null,2.875,1.75,null,1.75,1.75,null,1.75,1,null,1,1,null,1.75,2.5,null,2.5,2.5,null,2.5,2,null,2,2,null,2.5,3,null,3,3,null,2.875,4,null,4,4, Read More...

R Introductory Series 2023: Base R and data frames

Web Page

Bioinformatics

Lesson 3 Exercise Questions: BaseR dataframe manipulation and factors 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 . We are going Read More...

BTEP Coding Club: Configuration

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Bioinformatics

The plugin has several configuration options: boardmarkerWidth: an integer, the drawing width of the boardmarker; larger values draw thicker lines. chalkWidth: an integer, the drawing width of the chalk; larger values draw thicker lines. chalkEffect: Read More...

Introductory R for Novices: Exercise 4: Lesson 5

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Bioinformatics

For this exercise we will use filtlowabund_scaledcounts_airways.txt, which includes normalized and non-normalized transcript count data from an RNAseq experiment. You can read more about the experiment here. To obtain this file, click Read More...

R Introductory Series: Basics of R Programming

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Bioinformatics

Objectives To understand some of the most basic features of the R language including: Creating R objects and understanding object types Using mathematical operations Using comparison operators Creating, subsetting, and modifying vectors By the end Read More...

R Introductory Series: Introduction to R and RStudio

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Bioinformatics

Learning Objectives To understand: 1. the difference between R and RStudioIDE. 2. how to work within the RStudio environment including: creating an Rproject and Rscript navigating between directories using functions obtaining help how R can enhance data Read More...

Microbiome Analysis with QIIME2: Course Wrap-Up

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Bioinformatics

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...

Data Visualization with R: Lesson5

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Bioinformatics

Visualizing clusters with heatmaps Objectives Introduce the heatmap and dendrogram as tools for visualizing clusters in data. Learn how to work with the package pheatmap . Learn how to save a non-ggplot2 plot. Introduce ggplotify to Read More...

R Introductory Series 2023: R Basics

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Bioinformatics

R basics Objectives : To understand some of the most basic features of the R language including: Creating R objects and understanding object types Using mathematical operations Using comparison operators Creating, subsetting, and modifying vectors By Read More...

R Introductory Series 2023: Introduction to R and RStudio

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Bioinformatics

Introduction to R and RStudio IDE Objectives To understand: 1. the difference between R and RStudioIDE. 2. how to work within the RStudio environment including: creating an Rproject and Rscript navigating between directories using functions obtaining help 3. Read More...