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Bioinformatics
The Principal Components plot below graphs the sample along the PC1 and PC2 axes, which account for the highest and second highest variances in the data, respectively. PC1 explains 67.5% of variance while PC2 explains 8.7%. It Read More...
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Bioinformatics
Bioconductor packages are divided into four types: software annotation data experiment data workflows. Software packages themselves can be subdivided into packages that provide infrastructure (i.e., classes) to store and access data, and packages that Read More...
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Bioinformatics
Some typical statitstical tests applied to beta diversity metrics include the following: Adonis (PERMANOVA) Similar to a MANOVA, but is permutational and non-parametric. Sensitive to group dispersion, so it is worth running alongside a beta-dispersion Read More...
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Bioinformatics
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...
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Bioinformatics
Understanding data distribution can help us decide appropriate downstream steps in analysis such as which statistical test to use. A histogram is a good way to visualize distribution. It divides the data into bins or Read More...
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Bioinformatics
Understanding data distribution can help us decide appropriate downstream steps in analysis such as which statistical test to use. A histogram is a good way to visualize distribution. It divides the data into bins or Read More...
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Bioinformatics
Bioconductor packages are divided into four types: software annotation data experiment data workflows. Software packages themselves can be subdivided into packages that provide infrastructure (i.e., classes) to store and access data, and packages that Read More...
Web Page
Bioinformatics
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...
Frederick, MD
Core Facility
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...
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Back Services: We offer a limited sample processing service using standard SEC-MALS and FFF protocols. This service is intended for the occasional users of this system. Researchers who expect to use this instrument Read More...
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Back Services: We offer a limited sample processing service using standard SEC-MALS and FFF protocols. This service is intended for the occasional users of this system. Researchers who expect to use this instrument Read More...
Frederick, MD
Core Facility
The CCR-Frederick Flow Cytometry Core Facility provides research support to the Frederick-CCR community, including cytometry analysis and sorting services, instrument maintenance, new user training, and technical consultation. Typical Assays Performed by Core Instruments Immunophenotyping of Read More...
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Confocal
2025 Sebastian R, Sun EG, Fedkenheuer M, Fu H, Jung S, Thakur BL, Redon CE, Pegoraro G, Tran AD, Gross JM, Mosavarpour S, Kusi NA, Ray A, Dhall A, Pongor LS, Casellas R, Aladjem MI. Mechanism Read More...
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Confocal
Nikon SoRa Spinning Disk Capabilities: Inverted microscope Photo-metrics BSI sCMOS camera Yokogawa SoRa CSU-W1 spinning disk unit Super-resolution, confocal and wide-field imaging modes 4x, 10x, 20x and 60x objective lenses Mad City Labs 500 mm piezo Read More...
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Confocal
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...
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Bioinformatics
Functional annotation clustering works to cluster annotations that share similar genes. If we click on Functional Annotation Clustering in the Annotation Summary Results page then we can see the functional annotation clusters that our input Read More...
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Bioinformatics
Prior to sending our data into the heatmap generating algorithm, it is a good idea to sacle. There are several reasons for doing this Variables in the data might not have the same units, thus Read More...
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Bioinformatics
Prior to sending our data into the heatmap generating algorithm, it is a good idea to sacle. There are several reasons for doing this Variables in the data might not have the same units, thus Read More...
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Bioinformatics
Principal Components Analysis (PCA) transforms high dimensional data such as those derived from RNA sequencing so that researchers can see how study variables cluster together. The result of PCA is that the original data is Read More...
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Bioinformatics
The Functional Annotation Clustering tool groups similar annotations together to reduce the redundancy seen in the Functional Annotation Chart results. This eases the interpretation of the findings. The Functional Annotation Clustering integrates the same techniques Read More...
Bethesda, MD
Collaborative
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...
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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...
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Home About the Biophysics Core Biophysics Core Services [tabby title="Instrumentation"] NHLBI Biophysics Core The Biophysics Core Facility: Overview Core Facilities provide scientific resources, cutting-edge technologies and novel approaches to support DIR scientists. Availability of Read More...
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Confocal
2024 Mizunuma M, Redon CE, Saha LK, Tran AD, Dhall A, Sebastian R, Taniyama D, Kruhlak MJ, Reinhold WC, Takebe N, Pommier Y. Acetalax (Oxyphenisatin Acetate, NSC 59687) and Bisacodyl Cause Oncosis in Triple-Negative Breast Read More...
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Bioinformatics
Objectives To explore Bioconductor, a repository for R packages related to biological data analysis. To learn about options for report generation with R: RMarkdown and Quarto. Introducing Bioconductor Bioconductor is both an open source project Read More...
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Bioinformatics
Lesson 6 . Learning Objectives Introduce several beta diversity metrics Discover different ordination methods Learn about statistical methods that are applicable Beta diversity Beta diversity is between sample diversity. This is useful for answering the question, how Read More...
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Bioinformatics
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...
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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
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
Visualizing clusters with heatmaps Objectives Introduce the heatmap and dendrogram as tools for visualizing clusters in data. Learn to construct cluster heatmap using the package pheatmap . Learn how to save a non-ggplot2 plot. Introduce ggplotify Read More...
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Bioinformatics
Visualizing clusters with heatmaps Objectives Introduce the heatmap and dendrogram as tools for visualizing clusters in data. Learn to construct cluster heatmap using the package pheatmap . Learn how to save a non-ggplot2 plot. Introduce ggplotify Read More...
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Bioinformatics
Objectives To explore Bioconductor, a repository for R packages related to biological data analysis. To generate high quality data reports using R Markdown to make data analysis more reproducible. Reminder: Uploading files from RStudio Server Read More...