Lecture

Genomic Data Analysis: Identifying Differentially Expressed Genes

In course

Laboris irure irure proident ad dolore. Magna ipsum cupidatat eu ad exercitation adipisicing laborum sint irure Lorem nostrud. Nulla do eu proident mollit laboris enim laboris laboris pariatur pariatur aliqua ut magna dolor. Consequat excepteur ipsum culpa enim consequat duis enim adipisicing amet laboris esse. Eiusmod sit aliquip qui anim magna. Aute commodo excepteur ea cupidatat do veniam non amet. Laborum anim in amet proident excepteur adipisicing Lorem fugiat do.

Description

This lecture covers statistical methods for identifying differentially expressed genes in genomic data analysis. It discusses informal methods for gene identification, such as fold change thresholds and QQ plots. The lecture also delves into the challenges of assessing significance in replicated experiments and the use of moderated t-statistics to rank genes based on evidence of differential expression.

Official source

https://mediaspace.epfl.ch/media/0_49adv7vt

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Statistics

Statistical inference: Statistical hypothesis testing

Related lectures (34)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.