Udemy - Exploring Gene Expression R for Interpreting Biological Data

[ DevCourseWeb.com ] Exploring Gene Expression R for Interpreting Biological Data



If You Need More Stuff, kindly Visit and Support Us -->> https://DevCourseWeb.com







Published 6/2023

Created by Abdul Rehman Ikram

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English | Duration: 10 Lectures ( 1h 41m ) | Size: 964 MB



Exploring Genetic Insights and Unlocking Biological Patterns through Data Analysis with R Programming language



What you'll learn

Possess a solid understanding of bioinformatics principles and methodologies.

Be proficient in using R for data manipulation, analysis, and visualization in the context of bioinformatics.

Acquire knowledge of data manipulation, visualization, and statistical analysis techniques using R.

Gain expertise in differential gene expression analysis using Deseq2.

Perform genomic and transcriptomic analysis, such as genome assembly, gene expression analysis, and differential expression.

Be able to convert gene IDs to gene symbols for improved interpretability.

Have the skills to create compelling visualizations of gene expression data using ggplot2.

Be equipped with the knowledge and techniques to analyze scRNA-seq data using the R Seurat pipeline.



Requirements

Basic Biology Knowledge: Familiarity with basic biological concepts such as genes, proteins, DNA, and biological processes. Understanding of genomics and transcriptomics principles is helpful.

Programming Fundamentals: Prior experience with programming fundamentals is desirable, preferably in a language like Python or R. Knowledge of variables, functions, control structures, and basic data manipulation will provide a strong foundation for learning R programming.

Statistics and Data Analysis: An understanding of basic statistical concepts, such as descriptive statistics, hypothesis testing, and data visualization, is advantageous. This knowledge will assist students in effectively analyzing and interpreting biological data.



If You Need More Stuff, kindly Visit and Support Us -->> https://CourseWikia.com



Get More Tutorials and Support Us -->> https://FreeCourseWeb.com



We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...