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Professional Certificate in RNA-Seq Data Quality Control
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Course Details
- RNA-Seq Data Quality Control: Introduction and Best Practices
- Assessing Raw Read Quality using FastQC and MultiQC
- RNA-Seq Alignment and Mapping with STAR and HISAT2
- Assessing Alignment Quality Metrics: Properly evaluating read mapping rates and insert size distributions
- Detection and Removal of Adapter Sequences and Contaminants
- Gene Quantification and Normalization Methods: FPKM, TPM, and RPKM
- Quality Control for Differential Gene Expression Analysis
- Dealing with Batch Effects and Technical Variability in RNA-Seq Data
Career Path
Career Role Description Bioinformatician (RNA-Seq) Analyzes large RNA sequencing datasets, performing quality control, alignment, and differential expression analysis.
High demand in genomics and pharmaceutical research.
Data Scientist (Genomics) Develops and implements machine learning models for RNA-Seq data, extracting biological insights and improving prediction accuracy.
Strong RNA-Seq data processing and statistical skills required.
Research Scientist (RNA Biology) Conducts independent research using RNA-Seq data to investigate gene regulation, alternative splicing, and other RNA-related processes.
Expertise in experimental design and RNA-Seq data analysis essential.
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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