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

For the following plots, let's use the diamonds data ( ?diamonds ). The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and cut of each diamond. --- R4 Read More...

According to the data availability statement, the data can be found in PRJNA803155 . Change to the Practice directory created above or make it now. Then make a new directory named raw_data . {{Sdet}} Solution{{Esum}} 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...

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...

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...

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...

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...

You will need: active, unlocked Biowulf account (hpc.nih.gov) active Globus account for transferring files OR set up a file transfer program ( Filezilla ) for Mac or WinSCP for Windows PC. program to establish a Read More...

Download data from the SRA with fastq-dump split files into forward and reverse reads download part, not all, of the data Compare fastq-dump to fasterq-dump Introduce prefetch Look at XML-formatted data with sra-stat Grab SRA Read More...

Download data from the SRA with fastq-dump split files into forward and reverse reads download part, not all, of the data Compare fastq-dump to fasterq-dump Introduce prefetch Look at XML-formatted data with sra-stat Use e-utilities ( 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...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Let's talk about obtaining expression read counts using an application called featureCounts First let's create a new directory in our ~biostar_class/hbr_uhr folder to store the counts. mkdir hbr_uhr_deg_ Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Make a directory called Lesson6_practice and change directories. {{Sdet}} Solution{{Esum}} mkdir Lesson6_practice cd Lesson6_practice {{Edet}} Navigate to the NCBI website and grab the accession information for the associated BioProject. Download the Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Review: * downloading data from SRA * decompressing tar files * e-utilities * fastq-dump Learn: * sra-stat * XML format * automating SRA downloads * working with comma-separated values (csv) format * Read More...

touch creates an empty file nano basic editor for creating small text files rm remove files or directories. Be careful! mkdir make a directory and rmdir (remove a directory with NO files) mv rename or Read More...

cat hcc1395_sample_ids.txt | parallel "bowtie2 -x references/22 -1 reads/{}_R1.fq -2 reads/{}_R2.fq -S hcc1395_bowtie2/{}.sam" Change into hcc1395_bowtie2 and remove hcc1395 from the SAM alignment outputs. Read More...

Go back to /data/user/hcc1395_b4b. cd /data/user/hcc1395_b4b Create a directory called hcc1395_featurecounts. mkdir hcc1395_featurecounts Go back into /data/user/hcc1395_b4b/hcc1395_hisat2 for this Read More...

Let's talk about obtaining expression read counts using an application called featureCounts First let's create a new directory in our ~biostar_class/hbr_uhr folder to store the counts. mkdir hbr_uhr_deg_ Read More...

The module featureCounts from the subread package will be used to quantify gene expression. In the featureCounts command below: -p: specifies the presence of paired end data. --countReadPairs: specifies to count both reads in a Read More...

In the notebook panel of Jupyter Lab, there is a menu bar that allows users to save, cut/copy and paste and run cells. It also informs users which language the notebook is running. Importantly, Read More...

clusterProfiler also supports the Broad Institute software method of gene set enrichment analysis (GSEA) developed by Subramanian et al. 2005. Because this method uses all of the data (complete ranked gene list), this method is able Read More...

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The FNLCR Molecular Histopathology Laboratory (MHL) provides comprehensive veterinary pathology support for animal health monitoring, biomarker discovery and validation, drug development, genomics, and proteomics on a cost recovered basis. The MHL is organized into multiple 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...

This is part II of the article highlighting nf-core pipelines and specifically addresses the use of these pipelines in the DNAnexus cloud environment. Part I of the article can be found in the October 2023 topic Read More...

The data type of an R object affects how that object can be used or will behave. Examples of base R data types include numeric, integer, complex, character, and logical. R objects can also have Read More...

Help Session Lesson 4 Plotting with ggplot2 For the following plots, let's use the diamonds data ( ?diamonds ). The diamonds dataset comes in ggplot2 and contains information about ~54,000 diamonds, including the price, carat, color, clarity, and Read More...

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...

Lesson 6 Practice The following was designed to practice skills learned in lesson 6. Find the data Here is a paper examining the relationship between the oral microbiome and nasopharyngeal carcinoma. Where can you find the associated Read More...

Lesson 16 Practice Objectives In this lesson, we learned about the classification based approach for RNA sequencing analysis. In this approach, we are aligning our raw sequencing reads to a reference transcriptome rather than a genome. 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...

Remember that the deseq2.r script requires that the expression counts table be in csv format. It is currently in tab delimited format as generated by featureCounts. There is also a header line that we Read More...

Module 1 Week 1 Introductions and File systems L1 Why bioinformatics? L2 Intro to statistics? Lesson 1 Intro to Course, learning objectives Intro to Unix operating system What is a shell (how to proceed Windows vs Mac) What Read More...

Lesson 6: sra-tools, e-utilities, and parallel This page uses some content directly from the Biostar Handbook by Istvan Albert. Lesson 5 Review: The majority of computational tasks on Biowulf should be submitted as jobs: sbatch or swarm Read More...

Lesson 6: Downloading data from the SRA For this lesson, you will need to login to the GOLD environment on DNAnexus. Lesson 5 Review: The majority of computational tasks on Biowulf should be submitted as jobs: sbatch Read More...

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...

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...

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...

This page uses content directly from the Biostar Handbook by Istvan Albert. Learn * What are sequence adapters? * Do we need to trim them before alignment? * How can I trim with a new adapter sequence? Be Read More...

This page uses content directly from the Biostar Handbook by Istvan Albert. Learn * What are sequence adapters? * Do we need to trim them before alignment? * How can I trim with a new adapter sequence? Be 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...

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...

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...

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...

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...

Lesson 15 Practice Objectives Previously, we performed QC on the Golden Snidget RNA sequencing data, aligned the sequencing reads to its genome, and obtained expression counts. We can now finally perform differential expression analysis, to find Read More...

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

R objects have certain attributes, and these attributes will be important for how they can interact with certain methods / functions. Understanding the mode (storage type) or the class of an object will be important for Read More...

Make a directory called Lesson5_practice and change directories. Solution mkdir Lesson5_practice cd Lesson5_practice Navigate to the NCBI website and grab the accession information for the associated BioProject. Download the first 10 samples using Read More...

Remember that the deseq2.r script requires that the expression counts table be in csv format. It is currently in tab delimited format as generated by featureCounts. There is also a header line that we Read More...

In this session, participants will practice generating a gene expression matrix for the HBR-UHR data. Sign onto Biowulf and change into the /data/user/hbr_uhr_b4b folder. Solution ssh user@biowulf.nih.gov Read More...

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

Tasks to do at the Analysis Wizard: Provide an input gene list (either copy paste or upload as a text file) Specify the gene identifier type. Gene identifiers can be gene symbol, Ensembl IDs, Entrez Read More...

NIH Bioinformatics Calendar, sponsored by the NCI CCR Bioinformatics Training and Education Program (BTEP), contains information on all bioinformatics (and some data science) trainings/ presentations/ classes offered on the NIH campus. BTEP Distinguished Speakers Seminar Read More...

Data types are familiar in many programming languages, but also in natural language where we refer to them as the parts of speech, e.g. nouns, verbs, adverbs, etc. Once you know if a word Read More...

The CCR Collaborative Bioinformatics Resource (CCBR) is a centrally funded resource group which provides a mechanism for CCR researchers to obtain many different types of bioinformatics assistance to further their research goals. The group has Read More...

Our Mission The NCI Optical Microscopy Cores are instrumental in advancing cancer research through optical measurements and analysis. Serving the Center for Cancer Research community, which is home to approximately 250 Principal and Senior Investigators across 50 Read More...

2024 Senatorov IS, Bowman J, Jansson KJ, Alilin AN, Capaldo BJ, Lake R, Riba M, Abbey YC, Mcknight C, Zhang X, Raj S, Beshiri ML, Shinn P, Ngyuyen H, Thomas CJ, Corey E, Kelly K. Castrate Read More...

Contact the LCBG Microscopy Core to discuss your experiment Please login to the Bookitlab with your NIH credentials and register as user. Once you have registered on the website, coordinate a 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...

General Usage Policies Principal investigators should read this document and sign it. PI’s/postdocs should attach a short-written summary of the project to the signed doc. If the project changes, Read More...

2024 L. Balagopalan, T. Moreno, H. Qin, B. C. Angeles, T. Kondo, J. Yi, K. M. McIntire, N. Alvinez, S. Pallikkuth, M. E. Lee, H. Yamane, A. D. Tran, P. Youkharibache, R. E. Cachau, N. Taylor, Read More...

Gianluca Pegoraro, PhD gianluca.pegoraro@nih.gov Facility Head 240-760-6696 Bldg. 41, Room B909 Dr. Pegoraro received his Ph.D. in Molecular Genetics from the International School of Superior Studies in Trieste, Italy in 2004. After Read More...

Stephen Lockett, Ph.D. Director, OMAL locketts@nih.gov 301-846-5515 Valentin Magidson, Ph.D. Scientist magidsonv@mail.nih.gov 301-846-6092 Will Heinz, Ph.D. Scientist heinzwf@nih.gov 301-846-1239 David Read More...

2024 Coutinho, L. L., Femino, E. L., Gonzalez, A. L., Moffat, R. L., Heinz, W. F., Cheng, R. Y. S., Lockett, S. J., Rangel, M. C., Ridnour, L. A. & Wink, D. A. NOS2 and Read More...

Contact the CCR Microscopy Core to discuss your experiment Thank you for your interest in using the CCR Microscopy Core. Please login to the Bookitlab with your NIH credentials and register 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...

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...

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...

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...

Practice Lesson 2 For the help sessions, we will work on processing sequences generated in Zhang Z, Feng Q, Li M, Li Z, Xu Q, Pan X, Chen W. Age-Related Cancer-Associated Microbiota Potentially Promotes Oral Squamous Read More...

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...

Lesson 15: Finding differentially expressed genes Before getting started, remember to be signed on to the DNAnexus GOLD environment. Lesson 14 review In the previous lesson, we learned to visualize RNA sequencing alignment results in the Integrative Read More...

How to download data from the Sequence Read Archive (NCBI/SRA) to your account on NIH HPC Biowulf You will need: active, unlocked Biowulf account (hpc.nih.gov) active Globus account for transferring files OR Read More...

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...

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...

Prior to differential expression analysis, we need to generate a design.csv file that contains the samples and their corresponding treatment conditions. Note that csv stands for comma separated value so the columns in these 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...

“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...

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...

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...

Lesson 1: Introduction to Biowulf, Unix, and R Learning Objectives Learn about why you may want to use R on Biowulf. Refresh Unix and R skills. This lesson will not be hands on. Why use R Read More...

High resolution single cell profiling assays have provided an unprecedented view of many biological systems and processes, but the spatial context in which this biology is occurring is often crucial. Spatial profiling, including spatial transcriptomic Read More...

Scatter plots and plot customization Objectives Learn to customize your ggplot with labels, axes, text annotations, and themes. Learn how to make and modify scatter plots to make fairly different overall plot representations. Load a Read More...

R basics 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 Read More...

02/20/2020 - Learn how to easily analyze your gene expression data yourself - using Qlucore Omics Explorer NCI/CCR:To get access to Qlucore, put a request into NCI at Your Service under Get Help https:// Read More...

There are a number of core facilities available to NCI researchers. See more information from the Office of Science and Technology Resources. We most commonly see data from the following cores: CCR Sequencing Facility (CCR-SF) Read More...

Prior to differential expression analysis, we need to generate a design.csv file that contains the samples and their corresponding treatment conditions. Note that csv stands for comma separated value so the columns in these Read More...

A script allows users to string together analysis steps and keep them in one document. It can be reused with or without modification to analyze similar datasets. The script (SRR23341296_statistics.sh) below will use Read More...

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