Search Results for: zebrafish lines

Thousands of molecular targets have been measured in the NCI panel of 60 human tumor cell lines. Measurements include protein levels, RNA measurements, mutation status, and enzyme activity levels. You can choose to search for a Read More...

The NHLBI Transgenic Core’s main mission is to keep up with the latest advancements in genome engineering technologies and to provide state-of-the-art services to assist NIH scientists in generating genetically engineered animal models. In Read More...

The Developmental Therapeutics Program (DTP) within NCI's Division of Cancer Treatment and Diagnostics (DCTD), has maintained a low temperature repository of transplantable in vivo-derived tumors and in vitro-established tumor cell lines from various species. This Read More...

Swarm is for running a group of commands (job array) on Biowulf. swarm reads a list of command lines and automatically submits them to the system as sub jobs. To create a swarm file, you Read More...

The grep utility is used to search files looking for a pattern match. It is used like this. grep pattern options filename As our first example we will look for restriction enzyme (EcoRI) sites in Read More...

pwd (print working directory) ls (list) touch (creates an empty file) nano (basic editor for creating small text files) using the rm command to remove files. Be careful! mkdir (make a directory) and rmdir (remove Read More...

Here's another Unix trick to make your life easier. Access previous commands with the up and down arrows on your keyboard. You can scroll backwards and forwards. This helps when you've got a Read More...

Who says Unix programmers don't have a sense of humor? Let me introduce cat , head , and tail . The cat command (short for "concatenate") is an extremely useful command for creating new files Read More...

FASTQC to obtain quality metrics for individual FASTQ files. Recall that FASTQ files contain our sequencing data and each file has many sequencing reads. Each read is composed of four lines Header, that starts with @ Read More...

A scripting language that can be used for manipulating data and generating reports. Awk is a utility that enables a programmer to write tiny but effective programs in the form of statements that define text Read More...

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...

The Biological Products Core provides the AIDS research community with high-quality purified preparations of various strains of Human Immunodeficiency Virus (HIV) and Simian Immunodeficiency Virus (SIV), economically prepared by leveraging the economy of scale. Materials Read More...

The Genomics and Pharmacology Facility is part of the NCI's Center for Cancer Research (CCR), within the Developmental Therapeutics Branch. Its mission is to manage and assess molecular interaction data obtained through multiple platforms, increase Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Research Festival The NIH Research Festival highlights the groundbreaking science and the vibrant NIH community driving our Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Spotlight The NIH Lab Managers Working Group have developed a new NIH-wide database of cold Read More...

The Flow Cytometry Core (LGI) offers established technologies to support studies using flow cytometry and cell sorting. Established Technologies Applications that run on FACS Caliburs include: Immunophenotyping (up to 4-color), Intracellular markers, including cytokines and Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Resources Derive Greater Insights and Accelerate your Research Using Bioinformatic Tools! CREx is an NIH Read More...

DTP maintains a repository of synthetic compounds and pure natural products that are available to investigators for non-clinical research purposes. The Repository collection is a uniquely diverse set of more than 200,000 compounds that have been Read More...

NCI LASP Genome Modification Core (GMC) is a CCR-dedicated facility that provides advice, training, and reagents to NCI scientists seeking to utilize CRISPR and other nucleases to generate genome modifications in primary cells, cell lines, Read More...

The Clinical Support Laboratory offers processing, tracking, and testing of a broad range of clinical samples. Support can begin at the early stages of clinical trial development to aid in developing a comprehensive strategy for Read More...

The primary objective of the Protein Technology Core (PTC) is to establish an experimental screening pipeline for single-domain antibodies termed nanobodies. Nanobodies are antibody fragments consisting of a single monomeric variable antibody domain. The PTC, Read More...

12/05/2024 - This one and a half hour online training will provide a demonstration of how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be Read More...

12/03/2024 - This one and a half hour online training  will provide a demonstration of how to build a Bulk RNA-Seq data analysis pipeline using a fastq file. Partek  Flow   Read More...

10/23/2024 - CellMinerCDB is an interactive public web application ( https://discover.nci.nih.gov/cellminercdb/ ) that simplifies access and exploration of cancer cell line pharmacogenomic data across different sources such as the National Cancer Institute (NCI), Read More...

09/13/2024 - Reverse-phase protein arrays (RPPAs) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and develop novel cancer therapies.   To facilitate community-based investigation of the large-scale protein expression data generated by Read More...

03/05/2024 - This in-person workshop will show participants how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Cell Read More...

Last lesson we discussed the three basic components of creating a ggplot2 plot: the data , one or more geoms , and aesthetic mappings . ggplot(data = ) + (mapping = aes()) But, we also learned of other features that greatly Read More...

There are data sets available in R to practice with or showcase different packages. For today's lesson and the remainder of this course, we will use data from the Bioconductor package airway to showcase Read More...

You do not need to load a package to visually explore data. Rather, you can use base R graphics for plotting (from the graphics package). This plotting is fairly different from ggplot2 , which is based Read More...

Let's look a bit into our RStudio layout. Source : This pane is where you will write/view R scripts. Some outputs (such as if you view a dataset using View() ) will appear as a Read More...

01/22/2024 - Dear Colleagues,    Optical Genome Maps (OGM) provide scaffolding information for large DNA molecules. In this talk, we describe the use of this technology for detecting structural variants and chaining them Read More...

Remember, to create a plot all you you need are the data , geom_function(s) , and mapping arguments. However, there are additional components that can be added to our core components to enable us to Read More...

We can use the airway package to see how this container works, including how to access and subset the data. What is the airway package? There are data sets available in R to practice with Read More...

Used to match elements of a vector. %in% returns a logical vector indicating if there is a match or not for its left operand. --- match R Documentation. The returned logical vector will be the Read More...

In tab delimited files, data columns are separated by tabs. To import tab-delimited files there are several options. There are base R functions such as read.delim() and read.table() as well as the readr Read More...

In lesson 3, we learned how to read and save excel spreadsheet data to a R object using the tidyverse package readxl . Today we will use some example data from an excel spreadsheet to learn the Read More...

In comma separated files the columns are separated by commas and the rows are separated by new lines. To read comma separated files, we can use the specific functions ?read.csv() and ?read_csv() . Let' Read More...

11/16/2023 - This class will provide a demonstration of how to identify cell types based on statistics, visualization, and canonical markers. One Peripheral blood mononuclear cells (PBMCs) sample will be used to illustrate a basic Single Read More...

First we will obtain the SRA data from the biostar handbook web site curl http://data.biostarhandbook.com/sra/sra-runinfo-2019-01.tar.gz --output sra-runinfo-2019-01.tar.gz Now we can unpack the data. tar Read More...

Let's say you've got a very large FASTA or FASTQ file, and you want to run an analysis on it. Before working on the whole file, it can be useful to set up Read More...

For this class, we are going to work with data from and associated with two commercially available sets of RNA samples, Universal Human Reference (UHR) and Human Brain Reference (HBR). UHR - bulk RNA from 10 Read More...

This page contains content directly from the Biostar Handbook by Istvan Albert. Always remember to activate your bioinformatics environment. conda activate bioinfo What is a sequence pattern? A sequence pattern is a sequence of bases Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Review: * cd * mkdir * curl * tar * cat * grep * wc * outputting data * piping data from one command to another * cut Learn: * du * pip * csvkit * datamash Read More...

One of the things we will be doing quite often is to visualize genomics data using some sort of genome browser. In this course series, we will use a popular one called Integrative Genome Viewer( Read More...

One of the things we will be doing quite often is to visualize genomics data using some sort of genome browser. In this course series, we will use a popular one called Integrative Genome Viewer( Read More...

More useful Unix Flags and command options - making programs do what they do Use of wildcards Using tab complete for less typing Access your history with the "up" and "down" Read More...

The Human Brain Reference (HBR) RNA sequencing data are derived from RNA extracted from 23 human brains brains are from both males and females, age ranging from 60 to 80 years The Universal Human Reference data used RNA Read More...

More useful Unix Flags and command options - making programs do what they do Use of wildcards Using tab complete for less typing Access your history with the "up" and "down" Read More...

More useful Unix Flags and command options - making programs do what they do Use of wildcards Using tab complete for less typing Access your history with the "up" and "down" Read More...

The Human Brain Reference (HBR) RNA sequencing data are derived from RNA extracted from 23 human brains brains are from both males and females, age ranging from 60 to 80 years The Universal Human Reference data used RNA Read More...

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...

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...

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...

Now that we have downloaded the HBR and UHR dataset and know where analysis tools are, let's start learning about RNA sequencing, by first learning about our reference genome and annotation files. Let's Read More...

We will use the R helper scripts that we used before. cat 22simple_counts.txt | Rscript deseq2.r 3x3 > 22results_deseq2.txt The file 22results_deseq2.txt contains the genes sorted by their adjusted Read More...

We will use the R helper scripts that we used before. cat 22simple_counts.txt | Rscript deseq2.r 3x3 > 22results_deseq2.txt The file 22results_deseq2.txt contains the genes sorted by their adjusted Read More...

We will use the R helper scripts that we used before. cat 22simple_counts.txt | Rscript deseq2.r 3x3 > 22results_deseq2.txt The file 22results_deseq2.txt contains the genes sorted by their adjusted Read More...

Lesson 4: Useful Unix For this lesson, you will need to login to the GOLD environment on DNAnexus. Lesson 3 Review Biowulf is the high performance computing cluster at NIH. When you apply for a Biowulf account Read More...

Now that we have downloaded the HBR and UHR dataset and know where analysis tools are, let's start learning about RNA sequencing, by first learning about our reference genome and annotation files. Let's Read More...

We are going to download some bulk RNA-Seq test data and learn how to decompress it. First we will create a place to store the data. Go to the directory you've created for working Read More...

We were introduced to the hcc1395 RNA sequencing data in Lesson 12 practice session . This study compared the transcriptome of hcc1395 normal and cancer cell lines so it's a normal versus tumor comparison. This dataset Read More...

Lesson 14 Practice Objectives Here, we will practice using the Integrative Genome Viewer (IGV) to visualize the hcc1395 RNA sequencing alignment results. About the data and launching IGV We were introduced to the hcc1395 RNA sequencing Read More...

This page contains content taken directly from the Biostar Handbook by Istvan Albert. Activate the bioinformatics environment. conda activate bioinfo First let's make a place to store today's work. In your biostar_class Read More...

Which reference genome are we using in this IGV session to view the alignment results for samples hcc1395_normal_rep1 and hcc1395_tumor_rep2? On what chromosome are the sequencing data mapping to? {{Sdet}} Solution{{ Read More...

Let's download the Ebola genomes. mkdir -p ebola esearch -db nuccore -query PRJNA257197 | efetch -format fasta > genomes/ebola.fa and check the number of sequences with seqkit. seqkit stat genomes/ebola.fa and Read More...

We are using the datasets below in the Qiagen IPA course. Human Brain Reference (HBR) and Univeral Human Reference (UHR) dataset Using this for the one hour lecture (from 1 - 2 pm) Find more information about Read More...

Another way to run BLAST is to create your own custom database, and search against it with query sequences. Usually you will not have to create your own blast database, you can download prebuilt databases Read More...

This page uses content directly from the Biostars Handbook by Istvan Albert. Always remember to activate the bioinformatics environment. conda activate bioinfo How to align more than two sequences? Let's download the Ebola genomes. Read More...

Lesson 7: Downloading the RNA-Seq Data and Dataset Overview Lesson Review pwd (print working directory) ls (list) touch (creates an empty file) nano (basic editor for creating small text files) using the rm command to remove Read More...

Let's download the data and learn how to decompress it. First, we will create a place to store the data. Go to the directory you created for working with class material. If you haven' Read More...

First Unix command (ls) ls You may see something like this: public reads.tar sample.fasta sample.fastq The "ls" command "lists" the contents of the directory you are in. You Read More...

First Unix command (ls) ls You may see something like this: public reads.tar sample.fasta sample.fastq The "ls" command "lists" the contents of the directory you are in. You Read More...

First Unix command (ls) ls You may see something like this: public reads.tar sample.fasta sample.fastq The "ls" command "lists" the contents of the directory you are in. You Read More...

First Unix command (ls) ls You may see something like this: public reads.tar sample.fasta sample.fastq The "ls" command "lists" the contents of the directory you are in. You Read More...

Getting Started with Biowulf Biowulf is the NIH high performance computing cluster. It is a linux computing cluster with greater than 105,000 processors. The NIH HPC systems also house "hundreds of scientific programs, packages and Read More...

Getting Started with Biowulf Biowulf is the NIH high performance computing cluster. It is a linux computing cluster with greater than 105,000 processors. The NIH HPC systems also house "hundreds of scientific programs, packages and Read More...

Note that we now have differential expression by transcripts and our first column contains the transcript IDs. But what genes do these transcripts map to? We will need to do some data wrangling to find Read More...

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...

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...

Molecular Cytogenetics Core Facility facilitates the assessment of structural and numerical genomic changes in pre-cancer and cancer research models. This core provides comprehensive support for the cytogenetic analysis of cells from human and research animal Read More...

The Antibody Engineering Program (AEP) is located at the Laboratory of Molecular Biology, which is part of the Center for Cancer Research (CCR), an intramural program at the National Cancer Institute (NCI). AEP focuses on 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 Antibody Characterization Laboratory (ACL) is the laboratory responsible for the development of well-characterized monoclonal antibody reagents. The NCI’s Office of Cancer Clinical Proteomics Research funds ACL as a resource to the entire cancer Read More...

The Bloomington Drosophila Stock Center (BDSC) collects, maintains, and distributes genetically defined strains of Drosophila melanogaster for research and education. The BDSC supports a large, worldwide community of scientists using Drosophila as a model organism Read More...

The National Cancer Institute (NCI) is developing a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), patient-derived organoids (PDOrg), and in vitro patient-derived tumor cell cultures (PDCs) and cancer-associated fibroblasts (CAFs). These Read More...

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...

CLIA-Certified Technologies Offered: Fragment Analysis for Micro-satellite Instability Detection, Pharmacoscan Array for Pharmacogenomics, Mutation Detection for PCR and Sanger Sequencing, DNA extraction from whole blood, saliva, FFPE tissues, buccal swabs, nails, hair, PBMCs, buffy coats, Read More...

The Antibody Engineering Program (AEP) is part of the Center for Cancer Research (CCR) at the National Cancer Institute (NCI). The program focuses on generating therapeutic antibodies by phage display technology, including human antibodies and Read More...

The OSTR offers cutting-edge technology platforms to the CCR scientific community through centralized facilities. The videos accessed through this page are designed to introduce the various scientific methodologies OSTR makes available through the cores on Read More...

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...

NISC’s role within NHGRI, and more broadly across NIH, aims to advance genome sequencing and its many applications, with a goal not simply to produce sequence data, but to produce the infrastructure required to Read More...

The FindAllMarkers function is particularly useful in identifying the differentially expressed genes that distinguish several groups, such as seen here in the clusters. What makes this unique is that none of the identities are initially 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...

Now let's filter the rows based on a condition. Let's look at only the treated samples in scaled_counts using the function filter() . filter() requires the df as the first argument followed by Read More...

How do we ultimately get our figures to a publishable state? The bread and butter of pretty plots really falls to the additional non-data layers of our ggplot2 code. These layers will include code to 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...

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...

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...

Learning Objectives Learn about data structures including factors, lists, data frames, and matrices. Load, explore, and access data in a tabular format (data frames) Learn to write out (export) data from the R environment Data Read More...

This lesson will introduce data wrangling with R. Attendees will learn to filter data using base R and tidyverse (dplyr) functionality. Learning Objectives Understand the concept of tidy data. Become familiar with the tidyverse packages. Read More...

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...

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...

Data import and reshape Objectives 1. Learn to import multiple data types 2. Data reshape with tidyr : pivot_longer() , pivot_wider() , separate() , and unite() Installing and loading packages So far we have only worked with objects that Read More...

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...

Objectives To explore Bioconductor, a repository for R packages related to biological data analysis. To better understand S4 objects as they relate to the Bioconductor core infrastructure. To learn more about a popular Bioconductor S4 Read More...

Introduction to dplyr and the %>% Objectives Today we will begin to wrangle data using the tidyverse package, dplyr . To this end, you will learn: how to filter data frames using dplyr how to employ Read More...

From the publication REDO: Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak First we get the project (PRJN) number from the publication: PRJNA257197 Next we're going to query the "sra& Read More...

The bulk RNA-Seq test data we've been working with is in FASTQ format. We'd like to do a BLAST search on a couple of these sequences. Data must be in FASTA format to Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Always remember to activate the bioinfo environment when working on Biostar class materials. conda activate bioinfo The bulk RNA-Seq test data we've Read More...

Why Learn Bioinformatics? Analyze your own data Expand scientific training and skills Provide a path to a new career Have a better understanding of how other people analyze data What is Unix? an operating system, Read More...

Why Learn Bioinformatics? Analyze your own data Expand scientific training and skills Provide a path to a new career Have a better understanding of how other people analyze data What is Unix? an operating system, Read More...

Why Learn Bioinformatics? Analyze your own data Expand scientific training and skills Provide a path to a new career Have a better understanding of how other people analyze data What is Unix? an operating system, Read More...

Why Learn Bioinformatics? Analyze your own data Expand scientific training and skills Provide a path to a new career Have a better understanding of how other people analyze data What is Unix? an operating system, Read More...

How can we better automate downloads from the SRA? For example, what if we want the sequence files from the publication Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak First we need Read More...

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...

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...

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...

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...

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...

In lesson 9, we learned that reference genomes came in the form of FASTA files, which essentially store nucleotide sequences. In this lesson, we will learn about the FASTQ file, which is the file format that Read More...