Search Results for: 7G7 Anti-IL-2 alpha R

Let's combine our PCA and volcano plots. pca + volcano ## Warning: Using alpha for a discrete variable is not advised. The last plot included in patchwork statements is considered the active plot, to which we 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...

These steps can be used to create a publish worthy figure. For example, let's create a volcano plot of our differential expression results. A volcano plot is a type of scatterplot that shows statistical Read More...

A rarefaction curve plot[s] the number of counts sampled (rarefaction depth) vs. the expected value of species diversity. --- Weiss et al. 2017 Let's take a look at an alpha rarefaction curve . Demo plot Read More...

We will produce a number of core diversity metrics (alpha and beta) using a QIIME 2 pipeline, qiime diversity core-metrics-phylogenetic . The parameters we need to know include the path to our rooted tree ( --i-phylogeny ), the path Read More...

To change the y axis scale, we will need a specific function. These functions generally start with scale_y... . In our case we want to reverse our axis so that increasingly negative is going in Read More...

We can modify many aspects of the figure legend using the function guide() . Let's see how that works and go ahead and customize some theme arguments. Notice that the legend position is specified in Read More...

These steps can be used to create a publish worthy figure. For example, let's create a volcano plot of our differential expression results. A volcano plot is a type of scatterplot that shows statistical 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...

To change the y axis scale, we will need a specific function. These functions generally start with scale_y.... In our case we want to reverse our axis so that increasingly negative is going in Read More...

We can modify many aspects of the figure legend using the function guide(). Let's see how that works and go ahead and customize some theme arguments. Notice that the legend position is specified in Read More...

Look at the distribution of nCount_RNA with a Violin plot: # set colors cnames% ggplot(aes(color=orig.ident, x=nCount_RNA, fill= orig.ident)) + geom_density(alpha = 0.2) + theme_classic() + scale_x_log10() + geom_vline( Read More...

Now, let's take a look at the number of detected features. VlnPlot(adp, features = "nFeature_RNA", group.by="orig.ident") + scale_fill_manual(values=cnames) Warning: Default search for " 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...

In addition to the Heatmap and the FeaturePlot shown previously, two other options easily accessible through Seurat are the Dot Plot and Violin Plot. The dot plot can visualize relative expression level and expression fraction. Read More...

VlnPlot(adp, features = "percent.mt", group.by="orig.ident") + scale_fill_manual(values=cnames) + geom_hline(yintercept=10,color="red") Warning: Default search for "data" layer in " 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...

In addition to clasifying our organisms, we also want to reconstruct their phylogenetic relationships by generating a phylogenetic tree. We often assume that phylogenetic closeness can elucidate commonalities in phenotypic properties / functions, so it is Read More...

Rarefaction is the process of subsampling reads without replacement to a defined sequencing depth, thereby creating a standardized library size across samples. Any sample with a total read count less than the defined sequencing depth Read More...

Using a small subset of data: Imported raw fastq files using qiime tools import . Data was paired-end CASAVA format. Checked for primers using qiime cutadapt trim-paired . Denoised with qiime dada2 denoise-paired and generated summaries of Read More...

This course was designed to teach the basics of targeted amplicon data processing and analysis using the QIIME2 platform. Attendees will learn how to format data and metadata, import data, demultiplex sequences, trim sequences, denoise Read More...

Course Overview This course was designed to teach the basics of targeted amplicon data processing and analysis using the QIIME2 platform. Attendees will learn how to format data and metadata, import data, demultiplex sequences, trim 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...

Essentially named storage that can be manipulated. Rules for R variables: Avoid spaces or special characters EXCEPT '_' and '.' No numbers or underscores at the beginning of an object name. Avoid common names with special meanings ( Read More...

Essentially named storage that can be manipulated. Rules for R variables: Avoid spaces or special characters EXCEPT '_' and '.' No numbers or underscores at the beginning of an object name. Avoid common names with special meanings ( 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...

Let's change various aspects of the plot labels. plot_grid(pca,volcano,hmap,sc, labels=LETTERS[1:4],label_size = 14, label_fontface = "bold.italic", label_colour ="blue", label_fontfamily ="Times New Read More...

In scatter plots, the raw data is the focus of the plot, but for many other plots, this is not the case. We will discuss statistical transformation more in lesson 4 and how they apply. However, Read More...

The main function to combine figures using cowplot is plot_grid() . Let's check out the help documentation using ?plot_grid() . The first and most important parameter is the list of plots we want to Read More...

There are quite a few parameters to adjust figure labels. To re-position labels, see label_x , label_y , hjust , and vjust . These each take either a single value to move all labels or a vector Read More...

Let's start combining plots using the R package cowplot . cowplot is available on CRAN and can be installed using install.packages("cowplot") . The main function to combine figures using cowplot is plot_ Read More...

This is the sixth lesson in our Data Visualization with R Series. At this point, we have created quite a few plots. For this lesson, we will focus on the RNA-Seq plots that we created Read More...

This is the sixth lesson in our Data Visualization with R Series. At this point, we have created quite a few plots. For this lesson, we will focus on the RNA-Seq plots that we created Read More...

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10/19/2022 - Welcome to the Microbiome Analysis with QIIME 2 course series!                   This course series was designed to teach the basics of targeted amplicon data processing and analysis using the QIIME 2 platform. Attendees will learn how to Read More...

01/25/2021 - Presenter: Dr. Arjun Raj from the Perelman School of Medicine, UPenn. Abstract:Anti-cancer therapies can often kill the vast majority of tumor cells but a few rare cells remain and grow despite treatment. Non-genetic Read More...

Mapping aesthetics include some of the following: the x and y data arguments shapes color fill size linetype alpha :::{.notes} This is not an all encompassing list of mapping aesthetics. :::

There are many defaults when generating a plot with ggplot2, but almost everything you see can be customized. Here we can see: Assigned colors A legend axis titles a plot background tick marks The assignment 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...

There are many defaults when generating a plot with ggplot2, but almost everything you see can be customized. :::: {.columns} ::: {.column width="30%"} Here we can see: Assigned colors A legend axis titles a plot Read More...

Colors are assigned to the fill and color aesthetics in aes(). We can change the default colors by providing an additional layer to our figure. To change the color, we use the scale_color functions: Read More...

Let's reshape the data. I will rely heavily on dplyr functions to perform these tasks. First, I want to isolate the alpha chain and beta chain data. #isolate alpha and beta dfTRA< Read More...

Back Services: Biophysics Facility offers Octet as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar.  Training includes a full analysis of a Read More...

The Medicinal Chemistry Accelerator (MCA) is a collaborative CCR resource that supports investigators in developing small molecule inhibitors for anticancer drug candidates. While CCR and NCATS have infrastructure to identify initial “hits” through high-throughput screening, Read More...

NCI LASP Animal Research Technology Support (ARTS) provides customized technical support for basic and translational animal-based research to the scientific community. We offer a wide array of services ranging from expert colony management to the 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...

Work through DNAnexus? Find a nice cancer data set for 16S and shotgun Divide into two workshops or courses? Course structure or workshop structure? Amplicon processing and analysis (5 week course) (4 weeks) 1. Talk by Greg Caparaso? 1. Read More...

Microbiome Course Course Outline Work through DNAnexus? Find a nice cancer data set for 16S and shotgun Divide into two workshops or courses? Course structure or workshop structure? Amplicon processing and analysis (5 week course) (4 weeks) 1. Read More...

A search may take place in nucleotide space, protein space or translated spaces where nucleotides are translated into proteins. Searches may implement search “strategies”: optimizations to a specific task. Different search strategies will produce different Read More...

We can change the alignment of the plots by using the align argument. bc

We now know enough to put our new skills to use to make a volcano plot from RNASeq data. A volcano plot is a type of scatterplot that shows statistical significance (P value) versus magnitude Read More...

The plot above is looking pretty good, but there are many more features that can be customized to make this publishable or fit a desired style. Changing non-data elements (related to axes, titles subtitles, gridlines, 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...

When you have a lot of colors and you want to keep these colors consistent, you can use the following convenient functions to set a name attribute for a vector of colors. Let's do Read More...

Objectives Combine multiple plots into a single figure Learn how to use aspects of cowplot and patchwork The primary purpose of this lesson is to learn how to combine multiple figures into a single multi-panel 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...

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...

06/24/2020 - Join us for a webinar:  How to Analyze Single Cell RNA-Seq Data: Point, Click, Done Register:  https://www.partek.com/webinar/how-to-analyze-single-cell-rna-seq-data-point-click-done/ Single cell mRNA sequencing allows for the identification of different cell subtypes Read More...

Aesthetics that are not mapped to our variables are placed outside of the aes() function. These aesthetics are manually assigned and do not undergo the same scaling process as those within aes(). For example, we Read More...

Aesthetics that are not mapped to our variables are placed outside of the aes() function. These aesthetics are manually assigned and do not undergo the same scaling process as those within aes(). ::: {.cell output-location='slide'} # Read More...

In scatter plots, the raw data is the focus of the plot, but for many other plots, this is not the case. You may wish to overlay a stat on your PCA. For example, ellipses Read More...

To create a publication quality plot, you will need to make several modifications to your basic PCA biplot code. We have already seen how to modify the default coordinate system, how to add additional statistics ( Read More...

Now that we know how to create a PCA biplot, let's use what we have learned to also make a volcano plot. A volcano plot is a type of scatterplot that shows statistical significance ( Read More...

The next step is to either create or upload existing files. Click on the "uploading an existing file" link to upload a file named this_is_a_r_script.R from local computer. Read More...

These questions can be answered in excel. However, the data would need to be reshaped. To see what I mean, let's take a brief look at the data in Excel. Notice that there are Read More...

Without installing any other packages we can use the base R function merge, which will "merge two data frames by common columns or row names, or do other versions of database join operations." Read More...

In this case, we are going to use a left_join in order to retain all rows in our differential expression results. If we only wanted to include matching values, we could instead use an Read More...

The Laboratory Animal Sciences Program (LASP) of the Frederick National Laboratory operates a Gnotobiotics Facility (GF) to support research focused on the role of microbiota in cancer inflammation, pathogenesis, and treatment response. The GF can Read More...

The Pan-Microbial Serology Facility (PMSF) is part of the Center for Cancer Research (CCR) at the National Cancer Institute (NCI). The PMSF focuses on determining individualized pan-microbial immune profiles associated with human diseases including immunological Read More...

In order to meet increasing demands from both NIH intramural and extramural communities for access to a small angle X-ray scattering (SAXS) resource, the Center for Cancer Research (CCR) under the leadership of Drs. Jeffrey Read More...

Most BTEP courses include detailed course materials including lesson content, additional resources, and lesson associated data. These course materials are listed here so that learners can easily return to and review concepts taught in class Read More...

Listed below are the video recordings of past BTEP events (classes, seminars, workshops). Videos are hosted on various servers and may play slightly differently. Some videos may be downloaded for local viewing. Recorded Videos of 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...

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...

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...

Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review Read More...

Lesson 4: Feature table filtering, taxonomic classification, and phylogeny Learning objectives learn how to apply different types of filtering to your ASV table and representative sequence data. classify your ASVs. Generate a phylogenetic tree. Now that 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...

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...

This page uses content directly from the Biostar Handbook by Istvan Albert. Remember to activate the bioinformatics environment and create a directory for today's work. conda activate bioinfo mkdir blast cd blast What is Read More...

Learning Objectives Learn about popular programming languagues in bioinformatics Compare advantages and disadvantages of Python and R Discuss what you will need to learn to use these languages Discuss learning resources Choosing a programming language Read More...

Learning Objectives Learn about popular programming languagues in bioinformatics Compare advantages and disadvantages of Python and R Discuss what you will need to learn to use these languages Discuss learning resources Choosing a programming language 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...

Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review Read More...

Changes to a coding project (including scripts, data, and other content) should be saved periodically, similar to clicking on the "save" button to periodically save changes when constructing a word document. This is Read More...