Search Results for: Total Internal Reflection Fluorescence

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...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Resources Advance your research with the NIH Mouse Imaging Facility (MIF) The NIH Mouse Imaging Read More...

Back Services: Biophysics Facility offers MDS 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 standard molecular Read More...

Total end-to-end system for single-cell research [embed]https://youtu.be/vMzhSzg1rUw[/embed] The BD Rhapsody Single-Cell Analysis system empowers and streamlines your research with a complete system of tools, including reagents and analysis software, Read More...

The Functional Genomics Laboratory (formerly, the RNAi Screening Facility) of the National Center for Advancing Translational Sciences (NCATS) assist investigators with all stages of project planning and execution, beginning with assay development through genome-wide siRNA Read More...

The Mouse Imaging Facility (MIF) is a shared, trans-NIH intramural resource for animal imaging studies. MIF provides access to state-of-the-art radiological imaging methods optimized for mice, rats, other animals, and tissue samples. MIF provides intellectual, Read More...

The Biophysics Resource (BR) was established in January 2001. Our mission is to provide CCR investigators with access to both the latest instrumentation and expertise in characterizing the biophysical aspects of systems under structural investigation. The Read More...

.contrast_primary_button{margin-bottom: 29.124px;margin-top: 0px;} Established in 2016, CREx is an NIH-exclusive online research resource marketplace designed to increase transparency around the advanced technologies and technical expertise available within the Intramural Research Program (IRP). Read More...

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...

The core provides access to several different state-of-the-art 3D microscopes as well as computers to visualize and process image data. The facility houses equipment for 2D or 3D imaging of fixed and living specimens. High Read More...

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...

The Optical Microscopy Analysis Core (OMAC), formerly known as the Optical Microscopy Analysis Lab (OMAL),  focuses its research and development activities to quantitatively understand the molecular basis of three-dimensional (3D) cell organization, motility, invasion, and Read More...

The NCI High-Throughput Imaging Facility (HiTIF) works in a collaborative fashion with NCI/NIH Investigators by providing them with the necessary expertise, instrumentation, and software to develop and execute advanced High-Throughput Imaging (HTI) assays. These Read More...

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...

The LCBG Microscopy Core offers imaging technologies and training. The Core has established instrumentation for for 2D and 3D imaging of both fixed and living specimens.

Many established and emerging technologies are available to CCR scientists.  This technology-rich environment makes the CCR a unique place to conduct scientific research.  Through the OSTR, the CCR continues to find Read More...

The Department of Laboratory Medicine provides state-of-the-art laboratory testing in support of Clinical Center patient care and will serve as a center of excellence in research and training in laboratory medicine, particularly in areas which Read More...

The research conducted within the Synthetic Biologics Core (SBC) Facility has a dual role: Generate chemical biology tools and drug candidates for molecular targets identified by NCI research groups, Develop novel effective methods and tools Read More...

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...

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...

Back Services: Biophysics Facility offers DSC as an open-access instrument. First-time users must complete training before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: The differential scanning calorimeter measures the constant pressure Read More...

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...

Supplemental Technology Award Review System (STARS) Overview STARS Request Form STARS System The Supplemental Technology Award Review System (STARS) is a web-based interface for submission and review of S&S supplement requests by CCR 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 Clinical Image Processing Service (CIPS) offers timely and accurate advanced image processing of diagnostic radiology images for clinical care, research, and training. CIPS’ functions include clinical services and scientific researches. Established Technologies CIPS can Read More...

The Biomedical Engineering and Physical Science (BEPS) shared resource supports NIH’s intramural basic and clinical scientists on applications of engineering, physics, imaging, measurement, and analysis. BEPS is centrally located on the main NIH campus 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 Biophysics Core’s mission is to provide support in the study of macromolecular interactions, dynamics, and stability by offering consultations, training, professional collaborations, and instrument access. General Services Multi-technique molecular interaction studies, Kinetic and Read More...

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...

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...

The Chemistry and Synthesis Center (CSC) of the National Heart, Lung, and Blood Institute (NHLBI) provides IRP scientists with targeted imaging probes and chemical tools that help accelerate cell-based assays, in vivo imaging studies, and Read More...

[tabby title="Home"] About NICE-NIH Intramural CryoEM Consortium  NIH Intramural CryoEM Consortium (NICE) serves intramural investigators in all NIH IC’s. NICE provides access to state-of-the-art Titan Krios cryo-electron microscopes for atomic-resolution structure determination of Read More...

In order to create a ggplot2 bar plot we will need to reshape the data. The sample names should be in a single column named Sample and the gene counts in a single column named Read More...

Our Team Tatiana S. Karpova Ph.D.Core Headkarpovat@nih.govBuilding 41, Room C615240-760-6637 David A. Ball Ph.D.Core Biologistballa@nih.govBuilding 41, Room B114D240-760-6577 Mohamadreza Fazel, Ph.D.Core Biologistmohamadreza. Read More...

Leica SP8 LSCM with white light laser The SP8 LIGHTNING confocal microscope allows you to make proper and detailed observations of fast biological processes. Your experimental work will have the benefit of super-resolution, high-speed imaging, Read More...

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...

10/29/2025 - The Buenrostro lab is broadly dedicated to advancing our knowledge of gene regulation and the downstream consequences on cell fate decisions. To do this, the Buenrostro lab develops new technologies utilizing molecular biology, microscopy Read More...

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...

Software LAS Leica Application Suite X (LAS X) is the one software platform for all Leica microscopes: It integrates confocal, wide field, stereo, super-resolution, and light-sheet instruments from Leica Microsystems. MetaMorph The MetaMorph® Microscopy Automation Read More...

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...

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...

The following represents the basic ggplot2 template. ggplot(data = ) + (mapping = aes()) The only required components to begin plotting are the data we want to plot, geom function(s), and mapping aesthetics. Notice the + symbol following 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...

The general experimental design was as follows: WT vs DKO mice at two time points, 0 and 6 days. At day 0, cells were in a preadipocyte state, while at day 6 they had differentiated into adipocytes. Each time Read More...

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...

The following represents the basic ggplot2 template: ggplot(data = ) + (mapping = aes()) We need three basic components to create a plot: the data we want to plot , geom function(s) , and mapping aesthetics . Notice the + symbol 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...

Try googling your problem or using some other search engine. rseek is an R specific search engine that searches several R related sites. If using google directly, make sure you use R to tag your 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...

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...

As we have discussed, R objects are used to store things created in R to memory. This includes plots. scatter_plot

Load in a tab delimited file (file_path= "./data/WebexSession_report.txt") using read_delim() . You will need to troubleshoot the error message and modify the function arguments as needed. {{Sdet}} Solution } library ( Read More...

First, we will want to fix the three immediate problems discussed above. Once those have been fixed, we are going to create a bar plot, using ggplot2 to plot the total gene counts per sample. 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...

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...

Remember ~90% of RNA is ribosomal RNA. Therefore enrich your total RNA sample by: polyA selection (oligodT affinity) of mRNA (eukaryote), or rRNA depletion - RiboZero is typically used (costs extra)

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...

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...

samtools flagstat SRR1972739.bwa.bam produces this 20740 + 0 in total (QC-passed reads + QC-failed reads) 0 + 0 secondary 740 + 0 supplementary 0 + 0 duplicates 15279 + 0 mapped (73.67% : N/A) 20000 + 0 paired in sequencing 10000 + 0 read1 10000 + 0 read2 14480 + 0 properly paired (72.40% : N/A) 14528 + 0 with itself and mate mapped 11 + 0 singletons (0.05% : N/ Read More...

samtools flagstat SRR1972739.bwa.bam produces this 20740 + 0 in total (QC-passed reads + QC-failed reads) 0 + 0 secondary 740 + 0 supplementary 0 + 0 duplicates 15279 + 0 mapped (73.67% : N/A) 20000 + 0 paired in sequencing 10000 + 0 read1 10000 + 0 read2 14480 + 0 properly paired (72.40% : N/A) 14528 + 0 with itself and mate mapped 11 + 0 singletons (0.05% : N/ 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...

General Microscopy Resources Confocal Listserv Email discussion list focused on confocal microscopy, but also including topics on fluorescence microscopy and digital imaging. MicroscopyU Online learning platform by Nikon.  An online source for Microscopy education. Leica Read More...

The computational chemistry and protein modeling team in the Advanced Biomedical Computational Science (ABCS) group provides novel solutions in structural modeling and computational chemistry. Computational scientists in the group collaborate with NCI researchers by using Read More...

03/13/2025 - UCSC Xena showcases seminal cancer genomics datasets from The Cancer Genome Atlas (TCGA) and the Pan-Cancer Atlas, as well as the Genomic Data Commons, Pan-cancer Atlas of Whole Genomes, and the International Cancer Genome Read More...

In this tutorial, we will continue to use data from Nanduri et al. 2022, Epigenetic regulation of white adipose tissue plasticity and energy metabolism by nucleosome binding HMGN proteins , published in Nature Communications . As a reminder, Read More...

In this tutorial, we will continue to use data from Nanduri et al. 2022, Epigenetic regulation of white adipose tissue plasticity and energy metabolism by nucleosome binding HMGN proteins , published in Nature Communications . As a reminder, Read More...

One particular critique of differential expression in single cell RNASeq analysis is p-value "inflation," where the p-values get so small that there are far too many genes exist with p-values below 0.05, even after Read More...

The Advanced Biomedical Computational Science (ABCS) group focuses on applications of bioinformatics, computational and data science, and artificial intelligence to support NCI researchers. ABCS provides: • Subject matter expertise in genomics, proteomics, and imaging. • Machine learning/ Read More...

03/13/2024 - Dear Colleagues,    UCSC Xena is a web-based visual integration and exploration tool for multi-omic data and associated clinical and phenotypic annotations.   Xena showcases seminal cancer genomics datasets from Read More...

As mentioned, an object's mode can be used to understand the methods that can be applied to it. Objects of mode numeric can be treated as such, meaning mathematical operators can be used directly Read More...

#Setting a theme my_theme

Excel files are the primary means by which many people save spreadsheet data. .xls or .xlsx files store workbooks composed of one or more spreadsheets. Importing excel files requires the R package readxl . While this Read More...

Why did we focus so heavily on the tidyverse if it can't be used to manipulate Bioconductor objects? Well, for one, regardless of whether you are a user of Bioconductor packages, you will often Read More...

A geom is the geometrical object that a plot uses to represent data. People often describe plots by the type of geom that the plot uses. --- R4DS There are multiple geom functions that Read More...

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...

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...

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...

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...

ggplot2 will automatically assign colors to the categories in our data. Colors are assigned to the fill and color aesthetics in aes() . We can change the default colors by providing an additional layer to our Read More...

Help Session Lesson 3 Loading data Import data from the sheet "iris_data_long" from the excel workbook (file_path = "./data/iris_data.xlsx"). Make sure the column names are unique and 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...

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...

All Unix commands have a man or "manual" page that describes how to use them. If you need help remembering how to use the command ls , you would type: man ls There are Read More...

The Golden Snidget reference genome is located at http://data.biostarhandbook.com/books/rnaseq/data/golden.genome.tar.gz. Can you download and extract? {{Sdet}} Solution{{Esum}} Download wget http://data.biostarhandbook.com/books/rnaseq/ Read More...

ORA and FCS discard a large amount of information. These methods use gene sets, and even if the gene sets represent specific pathways, structural information such as gene product interactions, positions of genes, and types Read More...

This data set is from the Griffith lab RNA sequencing tutorial and are kept at http://genomedata.org/rnaseq-tutorial/practical.tar. This dataset is derived from a study that profiled the transcriptome of HCC1395 breast Read More...

Factor in at least 3 replicates (absolute minimum), but 4 if possible (optimum minimum). Biological replicates are recommended rather than technical replicates. Always process your RNA extractions at the same time. Extractions done at different times lead Read More...

Before we start, remember to change into the ~/biostar_class/snidget folder and then list the content to review what is available. cd ~/biostar_class/snidget ls -l QC total 117384 drwxrwxr-x 1 joe joe 1188 Oct 31 23:29 QC Read More...

Lesson 12 Practice Objectives In this practice session, we will work with something new, which is a dataset from the Griffith lab RNA sequencing tutorial. Here, we will have a chance to practice what we have Read More...

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...

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...

This page uses content directly from the Biostars Handbook by Istvan Albert (https://www.biostarhandbook.com). Always remember to load the bioinformatics environment. conda activate bioinfo SAM files SAM format is TAB-delimited, line-oriented, human-readable text Read More...

This page uses content directly from the Biostars Handbook by Istvan Albert (https://www.biostarhandbook.com). Always remember to load the bioinformatics environment. conda activate bioinfo SAM files SAM format is TAB-delimited, line-oriented, human-readable text Read More...

The bowtie2-build indexer builds a Bowtie index from a set of DNA sequences ([ref]. "bowtie2-build" builds a Bowtie index from a set of DNA sequences. "bowtie2-build" outputs a Read More...

Lesson 9 Practice Objectives In this practice session, we will apply our knowledge to learn about the reference genome and annotation file for the Golden Snidget dataset visualize the Golden Snidget genome using the Integrative Genome Read More...

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...

Intro_scikit-learn_part2 In [130]: ## Please uncomment the folloing line and run pip install to install scikit-plot for visualization for first run of the notebook. # Once it is installed, you can comment it out again for 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...

This lesson provides an introduction to R in the context of single cell RNA-Seq analysis with Seurat. Learning Objectives Learn about options for analyzing your scRNA-Seq data. Learn about resources for learning R programming. Learn 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...

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 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...

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

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...

All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only includes the columns Read More...

Help Session Lesson 5 All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only 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...

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...

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...

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...

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...

This page uses content directly from the Biostar Handbook by Istvan Albert. Always remember to activate the bioinfo environment when working on Biostar class material. conda activate bioinfo Retrieving a FASTA genome from NCBI/GenBank Read More...

Recall that the Golden Snidget data resides in ~/biostar_class/snidget folder. Can you change into the folder and find where the sequencing reads are (ie. in which folder they are located)? {{Sdet}} Solution{{Esum}} Read More...

BBDuk is another tool that can be used for adapter and quality trimming. In addition, BBDuk can be used to filter out contaminations, perform GC filtering, filter for length, etc. (see https://jgi.doe.gov/ Read More...

Lesson 10 Practice Objectives In this lesson, we introduced the structure of the FASTQ file and learned to assess quality of raw sequencing data using FASTQC. Here, we will practice what we learned using the Golden Read More...

Before we can align the HBR and UHR raw sequencing data to human chromosome 22 transcriptome, we need to create an index of this transcriptome (like we did with the genome). This will make the alignment 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...

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 previously stored FASTQC results for the HBR and UHR raw sequencing data in the ~/biostar_class/hbr_uhr/QC directory (recall that ~ denotes home directory). So before getting started, change into this folder. cd ~/ Read More...

Lesson 13 Practice Objectives In this lesson we learned how to align raw sequencing reads to reference and to process alignment results for downstream analysis. Here, we will test our knowledge by continuing with the Golden Read More...

Here, let's change back in the ~/biostar_class/hbr_uhr/hbr_uhr_hisat2 folder. cd $hbr_uhr_hisat2 To align FASTQ files for one sample, we construct the HISAT2 command with the following options 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...

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...

Below, you will find questions and answers brought up in the course polls for the BTEP Bioinformatics for Beginners course series that took place from September 13th, 2022 to December 13th, 2022. Question 1 : Normalization - when to Read More...

BTEP Bioinformatics for Beginners (September 13th, 2022 - December 13th, 2022) Questions and Answers Below, you will find questions and answers brought up in the course polls for the BTEP Bioinformatics for Beginners course series that took Read More...

Lesson 11: Merging FASTQ quality reports and data cleanup Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 10 Review In the previous lesson, we learned about the structure of the FASTQ Read More...

To align FASTQ files for one sample, we construct the HISAT2 command with the following options. The "-x" flag prompts us to enter the base name (ie. without extension) of genome index. The Read More...