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Bioinformatics
Differential abundance testing examines which taxa are significantly different in abundance between conditions. However, challenges such as sparsity, compositionality, and library size differences make this challenging to determine.
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Bioinformatics
featureCounts -a refs/22.gtf -g gene_name -o 22counts.txt bam/HBR*.bam bam/UHR*.bam Let's check the results file. less 22counts.txt We can remove some of the columns so we just Read More...
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Bioinformatics
featureCounts -a refs/22.gtf -g gene_name -o 22counts.txt bam/HBR*.bam bam/UHR*.bam Let's check the results file. less 22counts.txt We can remove some of the columns so we just Read More...
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Bioinformatics
featureCounts -a refs/22.gtf -g gene_name -o 22counts.txt bam/HBR*.bam bam/UHR*.bam Let's check the results file. less 22counts.txt We can remove some of the columns so we just Read More...
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Bioinformatics
By using the metacharacter asterisk "*" we can run feature counts on all the HBR and UHR samples in one command line. featureCounts -a refs/ERCC92.gtf -g gene_name -o counts.txt bam/ Read More...
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Bioinformatics
By using the metacharacter asterisk "*" we can run feature counts on all the HBR and UHR samples in one command line. featureCounts -a refs/ERCC92.gtf -g gene_name -o counts.txt bam/ Read More...
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Bioinformatics
By using the metacharacter asterisk "*" we can run feature counts on all the HBR and UHR samples in one command line. featureCounts -a refs/ERCC92.gtf -g gene_name -o counts.txt bam/ Read More...
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Bioinformatics
Let's use our practice data set to run ANCOM. Step 1: Filter out low abundance / low prevalent ASVs. Note: this will shift the composition of the samples, and thus could bias results. mkdir ancom qiime Read More...
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Bioinformatics
There are other reasons you may be interested in using pivot_wider or pivot_longer . In my experience, most uses revolve around plotting criteria. For example, you may want to plot two different but related Read More...
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Bioinformatics
There are other reasons you may be interested in using pivot_wider or pivot_longer . In my experience, most uses revolve around plotting criteria. For example, you may want to plot two different but related Read More...
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Bioinformatics
RNASEQ looks at steady state mRNA levels which is the sum of transcription and degradation Protein levels are assumed to be driven by mRNA levels RNASEQ can measure relative abundance not absolute abundance RNASEQ is 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
There are a number of specific solutions that have been devised to address the issues created by attempting to map mRNA to DNA genomes. Each of these has its advantages and disadvantages. Align against the Read More...
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Bioinformatics
06/16/2025 - In 2017, Dr. Rol joined the World Health Organization' International Agency for Re earch on Cancer (IARC-WHO), motivated to improve equal acce to high-quality healthcare for everyone. Currently, he lead an IARC team dedicated to Read More...
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Bioinformatics
There are several metrics that can be used to assess overall quality. The base workflow from Seurat suggests the following: nCount_RNA - the absolute number of RNA molecules (UMIs) per cell (i.e., count Read More...
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Bioinformatics
Purpose of RNA sequencing and what biological questions can RNA sequencing answer Experimental considerations Sample preparation Replicates Technical noise Read depth More depth for low expression genes More depth for low expression differences between samples Read More...
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Bioinformatics
Purpose of RNA sequencing and what biological questions can RNA sequencing answer Experimental considerations Sample preparation Replicates Technical noise Read depth More depth for low expression genes More depth for low fold differences Read length Read More...
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Bioinformatics
Purpose of RNA sequencing and what biological questions can RNA sequencing answer Experimental considerations Sample preparation Replicates Technical noise Read depth More depth for low expression genes More depth for low fold differences Read length Read More...
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Bioinformatics
The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . The UHR is total RNA isolated from a diverse set of 10 cancer cell lines. The HBR Read More...
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Bioinformatics
The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . The UHR is total RNA isolated from a diverse set of 10 cancer cell lines. The HBR Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Obtain RNA-seq test data. The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Obtain RNA-seq test data. The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . Read More...
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Bioinformatics
The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . The UHR is total RNA isolated from a diverse set of 10 cancer cell lines. The HBR Read More...
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Bioinformatics
The goal of quality control is to keep only high quality cells (i.e., remove low quality cells (dead or dying cells), cell-free RNA, or doublets). Low quality cells will impact downstream analyses. Take care Read More...
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Bioinformatics
Frequency based filtering, contingency based filtering, metadata based filtering qiime feature-table filter-samples Filter samples based on total number of sequences (e.g., --p-min-frequency 1000 ) Filter samples with a minimal number of features (e.g., --p-min-features 10 ) Metadata Read More...
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Bioinformatics
This page contains content directly from The Biostar Handbook . Always remember to start the bioinformatics environment. conda activate bioinfo Pseudoalignment-based methods identify locations in the genome using patterns rather than via alignment type algorithms. It Read More...
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Bioinformatics
This page contains content directly from The Biostar Handbook . Always remember to start the bioinformatics environment. conda activate bioinfo Pseudoalignment-based methods identify locations in the genome using patterns rather than via alignment type algorithms. It Read More...
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Biomarker Discovery with Morphological Context: Changing how tissue specimens are analyzed < https://youtu.be/mVhfZq8ppbc What is Digital Spatial Profiling? GeoMx Digital Spatial Profiler is a novel platform developed by NanoString. Digital Spatial Read More...
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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...
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Bioinformatics
RNA-SEQ Overview What is RNASEQ ? RNA-Seq (RNA sequencing), uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample at a given moment. (Wikipedia) Strictly speaking this could be any Read More...
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Bioinformatics
10/09/2024 - This session will give an overview of the NCI Cancer Research Data Commons and the variety of available cancer data such as RNA expression and protein abundance. These data are hosted in openly accessible Read More...
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Bioinformatics
The total number of detected transcripts expressed in a cell is dependent on the amount of mRNA in a cell. Cells naturally vary in the total amount of mRNA expressed. However, the chemistry of the Read More...
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Bioinformatics
A way to add variables to a plot beyond mapping them to an aesthetic is to use facets or subplots. There are two primary functions to add facets, facet_wrap() and facet_grid() . If faceting Read More...
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Bioinformatics
A way to add variables to a plot beyond mapping them to an aesthetic is to use facets or subplots. There are two primary functions to add facets, facet_wrap() and facet_grid() . If faceting Read More...
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Bioinformatics
To rarefy or not to rarefy? Feature tables are composed of sparse and compositional data. Measuring microbial diversity using 16S rRNA sequencing is dependent on sequencing depth. By chance, a sample that is more deeply Read More...
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Bioinformatics
Technical Replicates It’s generally accepted that they are not necessary because of the low technical variation in RNASeq experiments Biological Replicates (Always useful) Not strictly needed for the identification of novel transcripts and transcriptome Read More...
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Bioinformatics
Most RNASEQ techniques deal with count data. The reads are mapped to a reference and the number of reads mapped to each gene/transcript is counted Read counts are roughly proportional to gene-length and abundance Read More...
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Bioinformatics
Lesson 12: RNA sequencing review 1 Learning objectives Here, we will do a quick review of what we have learned about RNA sequencing in Lessons 8 through 11. Accessing the Biostar handbook The URL for the Biostar handbook is Read More...
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Bioinformatics
For any NGS experiment you will have to make choices about the following sequencing options. Unfortunately, there is and inverse relationship between accuracy and cost. Read Depth More depth needed for lowly expressed genes Detecting Read More...
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Bioinformatics
“Gene set enrichment analysis” refers to the process of discovering the common characteristics potentially present in a list of genes. When these characteristics are GO terms, the process is called “functional enrichment.” Warning Overall GO Read More...
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Bioinformatics
Two commercially available RNA samples. Universal Human Reference (UHR) is total RNA isolated from a diverse set of 10 cancer cell lines. Human Brain Reference (HBR) is total RNA isolated from the brains of 23 Caucasians, male Read More...
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Bioinformatics
Two commercially available RNA samples. Universal Human Reference (UHR) is total RNA isolated from a diverse set of 10 cancer cell lines. Human Brain Reference (HBR) is total RNA isolated from the brains of 23 Caucasians, male Read More...
Web Page
Bioinformatics
Two commercially available RNA samples. Universal Human Reference (UHR) is total RNA isolated from a diverse set of 10 cancer cell lines. Human Brain Reference (HBR) is total RNA isolated from the brains of 23 Caucasians, male 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...
Bethesda, MD
Core Facility
The CCR Genomics Core is located in Building 41 on the NIH Bethesda campus. The primary goal of the Core is to provide investigators from CCR/NCI and other NIH Institutes access to genomic technologies and Read More...
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Back Services: Biophysics Facility offers MP as an open-access instrument. First-time users must complete a short training session before gaining access to the instrument training calendar. Training includes mass distribution analysis of a Read More...
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Back Services: Biophysics Facility offers fluorometers as open-access instruments. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3226 Description: Some substances reemit light after Read More...
Frederick, MD
Repositories
Trans NIH Facility
NCI maintains a low temperature repository of implantable in vivo-derived tumors and in vitro-established tumor cell lines from various species, which are available to qualified investigators as a service to the cancer research community. The Read More...
Frederick, MD
Core Facility
The Animal Diagnostic Laboratory (ADL) provides a full range of diagnostic capabilities, including microbiological cultures on various culture medium, microscopic screening for parasites such as mites and pinworms, molecular detection of pathogens, serological evaluation of Read More...
Bethesda, MD
Collaborative
Our operational objectives are to provide state-of-the-art OMICS technologies in support of the Genetics Branch (GB) investigators and collaborators. Research Services Wet Lab Single cell isolation from fresh, frozen, and FFPE tissue, DNA/RNA extractions Read More...
Frederick, MD
Collaborative
Repositories
The Central Repository provides the research community at the NCI with various cryogenic services, including low-temperature storage from +4° C to -196° C, controlled-rate freezing, computerized inventory and distribution of samples. The Central Repository is operated Read More...
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Confocal
Software Image Acquisition Commercial imaging systems of LRBGE Optical Microscopy Core are controlled by acquisition software specifically designed for the appropriate microscope, such as ZEN (Zeiss confocal microscopes), Nikon Elements (Nikon), Imspector (Abberior). Custom-built HILO 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
Alignment RNASeq Mapping Challenges The majority of mRNA derived from eukaryotes is the result of splicing together discontinuous exons, and this creates specific challenges for the alignment of RNASEQ data. Mapping Challenges Reads not perfect Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Obtain RNA-seq test data. The test data consists of two commercially available RNA samples: Universal Human Reference (UHR) and Human Brain Reference (HBR) . Read More...
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Bioinformatics
05/16/2025 - This one-day in-person NIH AI Symposium will bring together researchers from a broad range of disciplines to share their AI-related research, with the goal of disseminating the newest AI research, providing an opportunity to Read More...
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Bioinformatics
04/10/2025 - This one hour online training introduces participants to the tools and techniques for analyzing and quantifying microscopy images using MATLAB’s low-code algorithms. Participants will learn how to preprocess images, segment regions Read More...
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Bioinformatics
02/25/2025 - Quality assessment may reveal low quality sequences and/or contaminations such as adapters in NGS data. Therefore, it is important to perform cleanup to ensure that the input for downstream analyses tools is of Read More...
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Bioinformatics
In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...
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Bioinformatics
In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to 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
Bray-Curtis dissimilarity quantitative Takes into consideration abundance and presence absence Jaccard - qualitative - presence / absence - percentage of taxa not found in both samples Weighted UniFrac quantitative similar to Bray-Curtis but takes into consideration Read More...
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Bioinformatics
Alpha diversity is within sample diversity. When exploring alpha diversity, we are interested in the distribution of microbes within a sample or metadata category. This distribution not only includes the number of different organisms (richness) Read More...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
Now that we know what we mean by denoising, let's apply it to our data. We will use DADA2 , which seems to be the more popular method. To use DADA2, we need to make Read More...
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Bioinformatics
This practice lesson is associated with Lesson 4 of the Microbiome Analysis with QIIME 2. In this practice lesson, we will work on filtering our feature table and representative sequences, classify our features, and generate a phylogenetic Read More...
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Bioinformatics
Practice Lesson 4 This practice lesson is associated with Lesson 4 of the Microbiome Analysis with QIIME 2. In this practice lesson, we will work on filtering our feature table and representative sequences, classify our features, and generate Read More...
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Bioinformatics
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...
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Bioinformatics
The object class used by the DESeq2 package to store the read counts and the intermediate estimated quantities during statistical analysis is the DESeqDataSet. --- Analyzing RNA-seq data with DESeq2 Constructing this object from a Read More...
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Bioinformatics
10/03/2023 - Multiplexed antibody-based imaging enables the detailed characterization of molecular and cellular organization in tissues. Significant advances in the field now allow high-parameter data collection (60+ targets); however, considerable expertise and capital are needed to validate Read More...
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Bioinformatics
What is a FASTQ file? {{Sdet}} Solution{{Esum}} A fastq or fq file is the format for files that contain our sequencing data. Similar to a fasta file, which contains a header line that starts Read More...
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Bioinformatics
Quantitation Counting as a measure of Expression Most RNASEQ techniques deal with count data. The reads are mapped to a reference and the number of reads mapped to each gene/transcript is counted Read counts Read More...
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Bioinformatics
When analyzing high throughput sequencing data, we will need to trim away adapters. Adapters help anchor the unknown sequencing template to the Illumina flow cell and can interfere with alignment. We may also want to Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Learn: FASTQC for assaying quality of sequence reads MultiQC for combining multiple FASTQC reports into one report Trimmomatic for removing sequence data based Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Learn: FASTQC for assaying quality of sequence reads MultiQC for combining multiple FASTQC reports into one report Trimmomatic for removing sequence data based Read More...
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Bioinformatics
Lesson 17: RNA sequencing review 2 Learning objectives This lesson will serve as comprehensive review of Module 2. We will spend roughly the first hour reviewing the Module 2 material the second hour answering specific questions from the poll 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
This page contains content taken directly from the Biostar Handbook by Istvan Albert. Always remember to start the bioinformatics environment. conda activate bioinfo We will be analyzing differential expression of genes on Chr22 from the Read More...
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Bioinformatics
This page contains content taken directly from the Biostar Handbook by Istvan Albert. Always remember to start the bioinformatics environment. conda activate bioinfo We will be analyzing differential expression of genes on Chr22 from the Read More...
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Bioinformatics
A programming language is a formal language that specifies a set of instructions for a computer to perform specific tasks. It is used to write software programs and applications, and to control and manipulate computer Read More...
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Bioinformatics
05/19/2023 - Patient-derived cancer models (PDCM) have become an essential tool in both cancer research and preclinical studies. Each model type offers unique advantages and is better suited for specific research areas: cell lines are low 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
Scaling is important during cluster analysis because it reduces the influence that variables with high magnitude values will have on distance. (https://medium.com/analytics-vidhya/why-is-scaling-required-in-knn-and-k-means-8129e4d88ed7). A common method for scaling is Read More...
Bethesda, MD
Trans NIH Facility
The facilities at AIM are available for use by the entire NIH intramural research community. While we welcome users with any size imaging project, AIM specializes in large, yearlong (or longer), collaborative research efforts with Read More...
Bethesda, MD
Trans NIH Facility
The Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) Initiative The STRIDES Initiative aims to help NIH and its institutes, centers, and offices (ICOs) accelerate biomedical research by reducing barriers in utilizing Read More...
Frederick, MD
Core Facility
The Genomics Technology Laboratory is an integrated, high-throughput molecular biology laboratory focusing on the development of genetics and genomics technologies, data analysis, and information management tools, in support of CCR Investigators. The laboratory develops integrated Read More...
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Back Services: Biophysics Facility offers ITC calorimeters as open-access instruments. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Training includes performing a test experiment and Read More...
Bethesda, Maryland
Core Facility
Repositories
The AgingResearchBiobank was officially launched in January 2019 with a mission to provide a state-of-the-art inventory system for the storage, maintenance, and distribution of de-identified biospecimens and associated phenotypic, clinical, and imaging data from numerous NIA-funded Read More...
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Back Services: Biophysics Facility offers MST as an open-access instrument. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Training includes the KD determination of a Read More...
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Services: Biophysics Facility offers CD as an open-access instrument. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the difference Read More...
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Back Services: Biophysics Facility offers CD as an open-access instrument. First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the Read More...
Frederick, MD
Core Facility
The introduction of DNA sequencing instruments capable of producing millions of DNA sequence reads in a single run has profoundly altered the landscape of genetics and cancer biology. Complex questions can now be answered at 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...
Web Page
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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Bioinformatics
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...
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Bioinformatics
Lesson 5: Microbial diversity, alpha rarefaction, alpha diversity Learning Objectives Understand the difference between alpha and beta diversity Introduce several alpha diversity metrics Understand what rarefaction is and why it is important Introduce the debate regarding Read More...
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Bioinformatics
10/24/2024 - NIH Text Mining and Natural Language Processing SIG is pleased to welcome you to this special event featuring two extraordinary speakers focused on the applications of Deep Learning in Computational Biology. & Read More...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
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...
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Bioinformatics
Lesson 3: Creating a feature table Lesson Objectives Check for primers Generate an ASV count table and representative sequence file Understand the difference between OTU picking and denoising The two primary files that will be used Read More...
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Bioinformatics
Objectives Review important data wrangling functions Put our wrangling skills to use on a realistic RNA-Seq data set Data Wrangling Review Important functions by topic Importing / Exporting Data Importing and exporting data into the R Read More...
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Bioinformatics
Let's align an RNA-Seq sample using the "splice aware" aligner hisat2. First we will need to create the indices. Use this format: hisat2-build REFERENCE_GENOME INDEX_PREFIX Like this: hisat2-build Read More...
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Bioinformatics
Let's align an RNA-Seq sample using the "splice aware" aligner hisat2. First we will need to create the indices. Use this format: hisat2-build REFERENCE_GENOME INDEX_PREFIX Like this: hisat2-build Read More...
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Bioinformatics
Let's align an RNA-Seq sample using the "splice aware" aligner hisat2. First we will need to create the indices. Use this format: hisat2-build REFERENCE_GENOME INDEX_PREFIX Like this: hisat2-build Read More...
Web Page
Bioinformatics
This page contains content taken directly from the Biostar Handbook (Istvan Albert). Always remember to activate the class bioinformatics environment. conda activate bioinfo For this data analysis, we will be using: Two commercially available RNA Read More...
Web Page
Bioinformatics
This page contains content taken directly from the Biostar Handbook (Istvan Albert). Always remember to activate the class bioinformatics environment. conda activate bioinfo For this data analysis, we will be using: Two commercially available RNA Read More...
Web Page
Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Learn: using trimmomatic to remove low-quality bases from a sequence Always remember to activate the bioinformatics environment. conda activate bioinfo We will be Read More...
Web Page
Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Learn: using trimmomatic to remove low-quality bases from a sequence Always remember to activate the bioinformatics environment. conda activate bioinfo We will be Read More...
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Bioinformatics
We will build a database out of all features of the 2014 Ebola genome under accession number KM233118. This data will go into a new directory named "db_2014". mkdir -p db_2014 # Get the 2014 Ebola Read More...
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Bioinformatics
This page uses content directly from the Biostar Handbook by Istvan Albert. Learning objectives: 1. Understand what a sequence alignment is and how different algorithms can effect alignments. 2. Learn how scoring matrices and gap penalties (gap 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
Lesson 16: RNA sequencing review and classification based analysis Before getting started, remember to be signed on to the DNAnexus GOLD environment. Review In the previous classes, we learned about the steps involved in RNA sequencing Read More...
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Bioinformatics
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...
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Bioinformatics
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...
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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
/* 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 how to work with the package pheatmap . Learn how to save a non-ggplot2 plot. Introduce ggplotify to Read More...