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RNA-Seq with Bioconductor in R

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Course Report - RNA-Seq with Bioconductor in R

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

RNA-Seq is a next-generation sequencing technique which identifies genes or pathways that are responsible for certain diseases and conditions. It's exciting. As high-throughput sequencing data becomes more affordable and easier to access, the ability to analyze it is becoming a valuable skill. You will learn about the RNA sequencing process and how to identify genes or biological processes that might be relevant for you. This course will give you a brief overview of the RNA sequencing process, with a special focus on differential expression (DE). The course will start with gene counts. The course will then discuss how to prepare data for DE analysis. The DESeq2 package is used to model the count data using a negative binary model, and test for differentially expressed genes. You can visualize the results with heatmaps and volcano plots. You can save the genes that are differentially expressed.

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Highlights

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Rating & Reviews

Top 30 Percentile

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Pedagogy

Top 30 Percentile

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Parameters

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Pedagogy

Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

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Rating & Reviews

This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Bioconductor in R

Introduction to Data Visualization with ggplot2

What You Will Learn

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions

Starting with the counts for each gene, the course will cover how to prepare data for DE analysis, assess the quality of the count data, and identify outliers and detect major sources of variation in the data

Course Instructors

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Mary Piper

Bioinformatics Consultant and Trainer

Mary Piper serves dual roles as research analyst and bioinformatics trainer in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. However, her primary role is the devel...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

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