Transcriptomics, Basic PCA: making a scatterplot of Principle Component Analysis results in Excel

After we run a pipeline to process raw reads from the FASTQ file, we can study the gene expression table. Working with the gene expression table includes understanding our column and row names, as well as numbers that correspond with gene expression level. We can filter the table, selecting specific values or genes and we can do a comprehensive analysis of the full table. We will learn about these by using Quantile Normalization to transform numbers into a consistent scale that provides us with “normal distribution” and use principle component analysis (PCA) to study variability between samples. Multi-sample normalization is a standard and necessary part of every RNA-seq dataset analysis. In the scatter plot obtained, the red points represent ER+ samples, while the green represent TN samples. Each set of samples from ER and TN clearly separate along PC 1 (X axis). For better understanding, visit the lesson in the Transcriptomics course on Principle Component Analysis on the Omicslogic Learn Portal - https://learn.omicslogic.com/Learn/course-5-transcriptomics/lesson/07-t2-practical-normalization-and-pca-of-gene-expression-data ABOUT OUR CHANNEL Our channel is about bioinformatics and its application to various biomedical and biotechnology challenges. We cover lots of cool topics on data analysis, machine learning and various technologies that generate high-throughput data like genomics, transcriptomics, metagenomics, epigenomics and others. Check out our channel here: https://www.youtube.com/c/Pine-biotech Don’t forget to subscribe! All of this content and more can be found on our training portal: https://learn.omicslogic.com Other videos about bioinformatics: https://www.youtube.com/watch?v=HR_Ndwfdu64 https://www.youtube.com/watch?v=otAEibvhi6U https://www.youtube.com/watch?v=3NT5zPXckS4 We offer bioinformatics training and analysis software, check them out here: https://learn.omicslogic.com https://server.t-bio.info Learn more about our team here: https://pine-biotech.com GET IN TOUCH! Contact us on marketing at omicslogic.com FOLLOW US ON SOCIAL: Get updates or reach out to Get updates on our Social Media Profiles! Twitter: https://twitter.com/pinebiotech Facebook: https://www.facebook.com/pinebiotech Instagram: https://www.instagram.com/bioinformaticspine/ LinkedIn: https://www.linkedin.com/showcase/omicslogic