Introduction to RNA Sequencing
RNA sequencing (RNA-Seq) is revolutionizing the study of the transcriptome. A highly sensitive and accurate tool for measuring expression across the transcriptome, it is providing researchers with visibility into previously undetected changes occurring in disease states, in response to therapeutics, under different environmental conditions, and across a broad range of other study designs.
RNA-Seq allows researchers to detect both known and novel features in a single assay, enabling the detection of transcript isoforms, gene fusions, single nucleotide variants, and other features without the limitation of prior knowledge.
End-to-End Applied Machine Learning and Data Science Recipes
Benefits of RNA Sequencing
RNA-Seq with next-generation sequencing (NGS) is increasingly the method of choice for researchers studying the transcriptome. It offers numerous advantages over gene expression arrays.
- Broader dynamic range enables more sensitive and accurate measurement of gene expression
- Not limited by prior knowledge – captures both known and novel features
- Can be applied to any species, even if reference sequencing is not available
- A better value, often delivering advantages at a comparable or lower price per sample than many arrays
End-to-End Applied Machine Learning and Data Science Recipes
Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.
Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners
Latest end-to-end Learn by Coding Projects (Jupyter Notebooks) in Python and R:
All Notebooks in One Bundle: Data Science Recipes and Examples in Python & R.
End-to-End Python Machine Learning Recipes & Examples.
End-to-End R Machine Learning Recipes & Examples.
Applied Statistics with R for Beginners and Business Professionals
Data Science and Machine Learning Projects in Python: Tabular Data Analytics
Data Science and Machine Learning Projects in R: Tabular Data Analytics
Python Machine Learning & Data Science Recipes: Learn by Coding
R Machine Learning & Data Science Recipes: Learn by Coding
Comparing Different Machine Learning Algorithms in Python for Classification (FREE)
There are 2000+ End-to-End Python & R Notebooks are available to build Professional Portfolio as a Data Scientist and/or Machine Learning Specialist. All Notebooks are only $29.95. We would like to request you to have a look at the website for FREE the end-to-end notebooks, and then decide whether you would like to purchase or not.