Powerful and Intuitive Gene Expression Visualization Tools to Interpret Biological Signals – Bulk and Single Cell Data

The increasing use of genomic technologies, such as RNA-Seq and single cell RNA-Seq, to assess gene expression patterns has led to an unprecedented amount of data. For many, the size and complexity of these data sets make it challenging to see the biological signals. But not anymore.

The visualization tools in Partek^® Flow^® provide the flexibility needed to display gene expression results ready for publication. Our powerful, interactive plots also facilitate novel discovery and provide fast and accurate QAQC. Together with the easy-to-use point and click interface, Partek Flow allows you to answer more questions and move forward with your research.

In this webinar, you will learn how to visualize gene expression data using:

• Feature distribution plots
• Sample correlation plots
• Volcano plots
• Chromosome view
• Dot plots
• Violin plots
• Hierarchical clustering
• PCA
• t-SNE
• Customizable scatterplots

WebEx link: https://cbiit.webex.com/cbiit/j.php?MTID=m634db94c7c42f1eb6dcf1850c27bd2c6

During the May Accelerating Therapeutics for Opportunities in Medicine (ATOM) Webinar Series, discover how computing and machine learning can accelerate molecular optimization for cancer and infectious disease therapeutics.

The ATOM Consortium is a public-private partnership whose mission is to transform drug discovery by accelerating the development of more effective therapies for patients.

This webinar will demonstrate how ATOM strives to:

• speed up molecular optimization for applications ranging from cancer to infectious disease therapeutics with the help of computing and machine learning,
• establish multiparameter property optimization across efficacy, safety, pharmacokinetics, and developability, and,
• develop systems with the potential to guide and optimize experimental data collection and design validation.

Presenter:

Mr. Jim Brase is the deputy associate director for computing at Lawrence Livermore National Laboratory (LLNL). He leads LLNL research in the application of high-performance computing, large-scale data science, and simulation to a broad range of national security and science missions. Mr. Brase is also co-lead of the ATOM Consortium for computational acceleration of drug discovery and on the leadership team of the COVID-19 HPC Consortium. His research interests focus on the intersection of machine learning, simulation, and high-performance computing. He is currently leading efforts on large-scale computing for life science, biosecurity, and nuclear security applications.

All Biowulf users, and all those interested in using the systems, are invited to stop by our Zoom session to discuss problems and concerns, from scripting problems to node allocation, to strategies for a particular project, to anything that is affecting your use of the HPC systems. Users will be assigned to a breakout-session with a member of the HPC staff to discuss the problem 1-on-1.  We’ll try to address simpler issues on the spot and follow up on more complex questions after the Zoom-In.

At the Zoom-In: You will initially join the  main lobby and triage area.  There, you can briefly describe your issue, and then will be invited to join a 1-on-1 breakout room with a staff member.

Once you are finished with your focused consultation you can return to the main meeting room if you have additional questions or topics to discuss.  Please

– mute when not speaking

– refrain from screen sharing until asked to do so in the breakout room

– screen share as you would in a public space with the understanding that other NIH HPC staff may join and view what you are sharing (i.e. look over your shoulder)

– be prepared to wait your turn if staff are already helping other users

For inquiries please email to: staff@hpc.nih.gov

Data is everywhere! In cancer research, data has had an impact on everything from how cancer is diagnosed to how decisions are made about prognosis and treatment. To illustrate the ubiquity of data and its influence on cancer research, Dr. Jill Barnholtz-Sloan will present, “DataMatters—Leveraging Big Data for Impact on Cancer.”

In her lecture, she’ll:

•  focus on how big data has impacted cancer to date and its impact on future research,
•  use specific examples from her work researching brain tumors, and
•  discuss big data resources available through NCI with detailed descriptions.

This presentation is part of the 2022 Special Lecture Series hosted by Big Data Training for Cancer Research, a program of Purdue University’s Center for Cancer Research.

Presenter:

Jill Barnholtz-Sloan, Ph.D.

Dr. Barnholtz-Sloan is the associate director for the Informatics and Data Science Program at NCI CBIIT and a senior investigator for NCI’s Division of Cancer Epidemiology and Genetics.

Python is one of the preferred programming languages for scientists to solve a wide variety of biological problems. We find that many scientists who come to Software Carpentry workshops use Python and want to learn more about its capabilities.

If you are a novice and want to learn how to program in Python to help you in your work, please join our six-week series of two-hour workshops! Instructors will use live code and you will follow along on your own computer. You will gain a strong foundation in the fundamentals of Python along with best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

NOTE: This is a six-part course, held weekly for 6 weeks from 11 am – 1 pm, with a 20-minute lunch break. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to all six sessions

Workshop Recordings and Materials:

• Recordings and Files: https://github.com/CBIIT/python-carpentry-workshop. This page contains last year’s material as well.
• Software Carpentry Lesson: Plotting and programming with Python
• Workshop Webpage at the NCI Data Science Learning Exchange: Introduction to Python A Series of Hands-on Software Carpentry Workshops (2022)

Before the workshop: We will use Google Colab for this workshop. Colab allows us to write and execute Python code through the browser. A Google Account is required for using Colab. If you do not have one, please create a Google Account before the workshop. For technical assistance, contact NCI technical support at https://service.cancer.gov/ncisp.

Presenters: Pinyi Lu, PhD, Data Scientist; Andrew Weisman, PhD, Bioinformatics Analyst; and George Zaki, PhD, Bioinformatics Manager, Frederick National Laboratory for Cancer Research (FNLCR)

Questions? Contact the NCI Data Science Learning Exchange

This training will provide an introduction to RNA-seq data analysis followed by tutorials showing the use of popular RNA-seq analysis packages and preparing participants to independently run basic RNA-Seq analysis for expression profiling. The exercise will run on the Galaxy platform using Illumina paired-end RNA-seq data.

Participants will have a chance to: run quality control check on sequencing data; align the sequencing reads to a reference genome; generate alignment statistics and check mapping quality; measure abundance of transcripts; perform differential expression analysis; and visualize the output of RNA-seq analyses.

Python is one of the preferred programming languages for scientists to solve a wide variety of biological problems. We find that many scientists who come to Software Carpentry workshops use Python and want to learn more about its capabilities.

If you are a novice and want to learn how to program in Python to help you in your work, please join our six-week series of two-hour workshops! Instructors will use live code and you will follow along on your own computer. You will gain a strong foundation in the fundamentals of Python along with best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

NOTE: This is a six-part course, held weekly for 6 weeks from 11 am – 1 pm, with a 20-minute lunch break. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to all six sessions!

Workshop Recordings and Materials:

• Recordings and Files: https://github.com/CBIIT/python-carpentry-workshop. This page contains last year’s material as well.
• Software Carpentry Lesson: Plotting and programming with Python
• Workshop Webpage at the NCI Data Science Learning Exchange: Introduction to Python A Series of Hands-on Software Carpentry Workshops (2022)

Before the workshop: We will use Google Colab for this workshop. Colab allows us to write and execute Python code through the browser. A Google Account is required for using Colab. If you do not have one, please create a Google Account before the workshop. For technical assistance, contact NCI technical support at https://service.cancer.gov/ncisp.

Presenters: Pinyi Lu, PhD, Data Scientist; Andrew Weisman, PhD, Bioinformatics Analyst; and George Zaki, PhD, Bioinformatics Manager, Frederick National Laboratory for Cancer Research (FNLCR)

Questions? Contact the NCI Data Science Learning Exchange

Python is one of the preferred programming languages for scientists to solve a wide variety of biological problems. We find that many scientists who come to Software Carpentry workshops use Python and want to learn more about its capabilities.

If you are a novice and want to learn how to program in Python to help you in your work, please join our six-week series of two-hour workshops! Instructors will use live code and you will follow along on your own computer. You will gain a strong foundation in the fundamentals of Python along with best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

NOTE: This is a six-part course, held weekly for 6 weeks from 11 am – 1 pm, with a 20-minute lunch break. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to all six sessions!

Workshop Recordings and Materials:

• Recordings and Files: https://github.com/CBIIT/python-carpentry-workshop. This page contains last year’s material as well.
• Software Carpentry Lesson: Plotting and programming with Python
• Workshop Webpage at the NCI Data Science Learning Exchange: Introduction to Python A Series of Hands-on Software Carpentry Workshops (2022)

Before the workshop: We will use Google Colab for this workshop. Colab allows us to write and execute Python code through the browser. A Google Account is required for using Colab. If you do not have one, please create a Google Account before the workshop. For technical assistance, contact NCI technical support at https://service.cancer.gov/ncisp.

Presenters: Pinyi Lu, PhD, Data Scientist; Andrew Weisman, PhD, Bioinformatics Analyst; and George Zaki, PhD, Bioinformatics Manager, Frederick National Laboratory for Cancer Research (FNLCR)

Questions? Contact the NCI Data Science Learning Exchange

Python is one of the preferred programming languages for scientists to solve a wide variety of biological problems. We find that many scientists who come to Software Carpentry workshops use Python and want to learn more about its capabilities.

If you are a novice and want to learn how to program in Python to help you in your work, please join our six-week series of two-hour workshops! Instructors will use live code and you will follow along on your own computer. You will gain a strong foundation in the fundamentals of Python along with best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

NOTE: This is a six-part course, held weekly for 6 weeks from 11 am – 1 pm, with a 20-minute lunch break. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to all six sessions!

Workshop Recordings and Materials:

• Recordings and Files: https://github.com/CBIIT/python-carpentry-workshop. This page contains last year’s material as well.
• Software Carpentry Lesson: Plotting and programming with Python
• Workshop Webpage at the NCI Data Science Learning Exchange: Introduction to Python A Series of Hands-on Software Carpentry Workshops (2022)

Before the workshop: We will use Google Colab for this workshop. Colab allows us to write and execute Python code through the browser. A Google Account is required for using Colab. If you do not have one, please create a Google Account before the workshop. For technical assistance, contact NCI technical support at https://service.cancer.gov/ncisp.

Presenters: Pinyi Lu, PhD, Data Scientist; Andrew Weisman, PhD, Bioinformatics Analyst; and George Zaki, PhD, Bioinformatics Manager, Frederick National Laboratory for Cancer Research (FNLCR)

Questions? Contact the NCI Data Science Learning Exchange

Learn how to get started on using QIAGEN’s Ingenuity Pathway Analysis (IPA) to quickly identify biological relationships, mechanisms, pathways, functions and diseases most relevant to experimental datasets. IPA is cited in tens of thousands of peer-reviewed articles. The class will demonstrate how to explore IPA’s knowledge & discovery tools to relate the most recent literature findings to your research. The demo session will mainly focus on biological interpretation of expression data but will also cover multi-omics analysis including variant data and phosphoproteomics.

Getting Started: fundamentals of IPA; overview of key features; search & pathway building; advanced search; building & editing pathways; using Build & Overlay tools. Dataset Analysis: data upload & analysis; interpretation of gene, transcript, protein & metabolite data; pathway analysis & canonical pathways; downstream effects & interpreting the heat map; causal regulators and their directional effect on genes, functions and diseases across multiple time points or doses; interpreting networks; comparison & multiple observations analysis; miRNA and isoform analysis; BioProfiler: define relationships between molecule activity and diseases/processes in the literature. Q & A session: A QIAGEN Ingenuity Field Applications Scientist will be available to answer individual questions or discuss specific projects.

During this seminar, Washington University in St. Louis’ Dr. Obi L. Griffith will present CIViC: an open access, open source, community-driven web resource for clinical interpretation of variants in cancer. The goal of this resource is to enable precision medicine by providing an educational forum for dissemination of knowledge and active discussion of the clinical significance of cancer genome alterations.

The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.

Presenter:

Obi L. Griffith, Ph.D.

Dr. Griffith is an associate professor of medicine (oncology) and the assistant director of the McDonnell Genome Institute at Washington University in St. Louis School of Medicine. He has his doctorate in medical genetics from the University of British Columbia in Vancouver, Canada. Dr. Griffith’s research interests include cancer informatics, clinical statistics, and breast cancer.

This webinar will discuss the various single cell RNA-Seq data formats and how to process them with Partek Flow.

You will learn about:

• Single cell data file formats .h5, .fastq, .tsv, .mtx, .bcl
• Trimming tags
• Alignment
• Deduplicating UMI
• Filtering barcodes (cells)
• Knee plots

Sarah Teichmann, Ph.D., Fellow of the Academy of Medical Sciences (UK FMedSci), Fellow of the Royal Society (FRS), Wellcome Sanger Institute

Sarah Teichmann is co-founder and principal leader of the Human Cell Atlas (HCA) international consortium. The International Human Cell Atlas initiative aims to create comprehensive reference maps of all human cells to further understand health and disease.

The team’s research focuses on four complementary study areas:

• Transcriptional regulation and gene expression
• Single-cell genomics
• Immunology
• Protein complexes