1 Introduction
2 A Very General Genomics Overview
Genomics Workflow Overview
10 attempts allowed
Metadata Guidelines
10 attempts allowed
4 Considerations for choosing tools
Considerations for tools
10 attempts allowed
5 General Data Analysis Tools
General data analysis
10 attempts allowed
6 Sequencing Data
Sequencing data overview
10 attempts allowed
7 Microarray Data
Microarray data overview
10 attempts allowed
8 Annotating Genomes
Annotating genomes
10 attempts allowed
9 DNA Methods Overview
10 Whole Genome or Exome Sequencing
11 RNA Methods Overview
12 Bulk RNA-seq
13 Single-cell RNA-seq
14 Spatial transcriptomics
15 Chromatin Methods Overview
16 ATAC-Seq
17 Single cell ATAC-Seq
18 ChIP-Seq
19 DNA Methylation Sequencing
20 ITCR -omic Tool Glossary
About this Course
About the Authors
References
Choosing Genomics Tools
Choosing Genomics Tools
There's a multitude of genomic data analysis tools and resources out there. How do you find what you need for your data types and questions? This course aims to give you the foundational information you need and equip you with knowledge of the genomics tools out there so you can make informed decisions about your research.
The instructors are letting you choose the price you pay for this course!
The instructors are letting you choose the price you pay for this course!
There's a multitude of genomic data analysis tools and resources out there. How do you find what you need for your data types and questions? This course aims to give you the foundational information you need and equip you with knowledge of the genomics tools out there so you can make informed decisions about your research.
About
About the Course
This course is part of a series of courses for the Informatics Technology for Cancer Research (ITCR) called the Informatics Technology for Cancer Research Education Resource. This material was created by the ITCR Training Network (ITN) which is a collaborative effort of researchers around the United States to support cancer informatics and data science training through resources, technology, and events. This initiative is funded by the following grant: National Cancer Institute (NCI) UE5 CA254170. Our courses feature tools developed by ITCR Investigators and make it easier for principal investigators, scientists, and analysts to integrate cancer informatics into their workflows. Please see our website at www.itcrtraining.org for more information.
The course is intended for students in the biomedical sciences and researchers who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
This course is written for individuals who:
- Have genomic data and don’t know what to do with it.
- Want a basic overview of genomic data types.
- Want to find resources for processing and interpreting genomics data.
Cancer datasets are plentiful, complicated, and hold untold amounts of information regarding cancer biology. Cancer researchers are working to apply their expertise to the analysis of these vast amounts of data but training opportunities to properly equip them in these efforts can be sparse. This includes training in reproducible data analysis methods.
Often students and researchers need to utilize genomic data to reach the next steps of their research but may not have formal training in computational methods or the basics of the genomic data they are attempting to utilize.
Often researchers receive their genomic data processed from another lab or institution, and although they are excited to gain insights from it to inform the next steps of their research, they may not have a practical understanding of how the data they have received came to be or what needs to be done with it.
Categories
Price
Course Price
Minimum price
Free!
$19.00
You pay
$19.00Instructors
About the Instructors
Carrie Wright
Carrie Wright is a Senior Staff Scientist at the Fred hutchinson Cancer Center and a member of the Fred Hutchinson Data Science Lab. Previously Carrie was an Assistant Scientist in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and a faculty member of the Johns Hopkins Data Science Lab. Her work focuses on making data science and informatics more approachable and accessible. She is also a faculty member of the open case studies project, the Informatics Technology for Cancer Research (ITCR) Training Network (ITN), and a co-founder of the LIBD rstats club, a community designed to encourage others to learn more about R programming and statistics. Learn more about Carrie at https://carriewright11.github.io/.
Material
Course Material
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