Choosing Genomics Tools (The Course)
Course Info
This course includes 1 attempt.
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.
Course Material
- 1 Introduction
- 2 A Very General Genomics Overview
- Genomics Workflow Overview10 attempts allowed
- Metadata Guidelines10 attempts allowed
- 4 Considerations for choosing tools
- Considerations for tools10 attempts allowed
- 5 General Data Analysis Tools
- General data analysis10 attempts allowed
- 6 Sequencing Data
- Sequencing data overview10 attempts allowed
- 7 Microarray Data
- Microarray data overview10 attempts allowed
- 8 Annotating Genomes
- Annotating genomes10 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
Instructors
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/.
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