BIOF 555 - Foundations for Practical Single Cell RNA-seq Analyses

Course Description

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Foundations for Practical Single Cell RNA-seq Analyses will explore the use and analyses of single cell RNA-seq datasets that will enable precision exploration of the basic unit of life: the cell. This course will examine how single cell RNA-seq experiments are conducted, dive into the computational challenges and solutions to analyze these data, and extract biological meaning from the wealth of information afforded by single cell RNA-seq. It seeks to provide foundational concepts and bioinformatic skills to inquire about the wealth of information (and limitations) of single cell RNA-seq data. In addition to the didactic learning opportunities in the class, there will be practicum lectures and longitudinal project that will provide a hands-on analysis of a published, publicly available single cell dataset. These hands-on analyses will take learners through the computational techniques commonly employed in single cell RNA-seq data analyses.
At the end of the course, you will be able to assess and perform the foundational analyses for a standard single cell RNA-seq dataset using R. You will communicate your findings to peers and evaluate findings of published and peer analyses of single cell RNA-seq data.

Learner Outcomes

When you complete the course successfully, you will be able to:

Describe the advantages and limitations of various single cell RNA-seq approaches
Compare the quality and biases of different single cell RNA-seq datasets generated from the same tissues
Apply the best practices of single cell RNA-seq analyses to a set of published single cell RNA-seq datasets
Formulate and conduct an analysis plan to investigate specific hypotheses using single cell RNA-seq data
Draw biologically meaningful conclusions supported by data and analyses of single cell RNA-seq data

Microcredential(s)

This course applies toward the Bioinformatics Endeavor digital badge.

Textbook Information

There is no textbook for purchase required for this course.

Prerequisites

Statistics requires completion of one of the following:

BIOF 099 or STAT 515
STAT 101 or BIOF 098 AND self tutorial and completion of https://www.modernstatisticswithr.com/
Self tutorial and completion of swirl advanced (https://github.com/swirldev/swirl_courses#swirl-courses)
Coursework/expertise in a related field (bioinformatics, data science, public health, statistics, etc.)

AND

R-Programming requires completion of one of the following:

BIOF 501 AND self tutorial and completion of https://r4ds.had.co.nz/
Prior coursework AND self tutorial and completion of https://r4ds.had.co.nz/
Self tutorial and completion of swirl beginner AND intermediate course (https://github.com/swirldev/swirl_courses#swirl-courses)

AND

Biological sciences requires completion of one of the following:

Coursework or other expertise in biology, molecular biology, or a related biomedical sciences field
Omics or sequencing coursework, such as BIOF 521 or BIOF 450 or BIOF 540 or BIOF 074 or BIOF 048 or BIOF 518 or BIOF 519

Refund
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Funding Justification Guide

Some labs and institutes may have specific funds set aside for trainees to continue their education and professional development. FAES has created a guide intended to help trainees request funds that may be available and, if they are available, request use of the training funds for continued professional development. More details

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BIOF 555 - Session A

Fall 2024

Aug 28, 2024 to Oct 15, 2024

Available

Foundations for Practical Single Cell RNA-seq Analyses

Online Asynchronous

Aug 28, 2024 to Oct 15, 2024

Eligible Discounts Can Be Applied at Checkout (2 Credits)

$775.00

.Gov Discount 2 Credit Course

2 Credit(s)