Tutorial: Applying machine learning to NGS transcriptomic data
gravatar for elia.brodsky
2.2 years ago by
United States
elia.brodsky330 wrote:

Next generation sequencing is a rich source of data for sample classification. Exploring data with unsupervised methods like clustering is limited since many samples might have several possible cluster placements, so supervised classification of a portion of samples is a great approach. However, powerful classification techniques like SVM cannot accept typical gene expression tables with thousands of genes, so it is useful to first use a classifier with feature selection like step-wise linear discriminant analysis to reduce the number of features that is closer to the number of samples the study. This approach improves the quality of classification from standard LDA and increases confidence in NGS-based classification. These topics of machine learning techniques for NGS data are the subject of our series of workshops (https://edu.t-bio.info/workshops/) and the Transcriptomics 3 course on edu.t-bio.info. (https://edu.t-bio.info/course/transcriptomics-3/)

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rna-seq next-gen tutorial • 1.7k views
ADD COMMENTlink modified 2.2 years ago • written 2.2 years ago by elia.brodsky330

Soo..that's a beautifully colourful figure, but where's the tutorial? :D

ADD REPLYlink written 2.2 years ago by cschu1812.3k

sorry, something went wrong with formatting. The full tutorial is here: https://edu.t-bio.info/course/transcriptomics-3/

ADD REPLYlink written 2.2 years ago by elia.brodsky330

Quiz in the course and hands-on require company's product use.

ADD REPLYlink modified 2.2 years ago • written 2.2 years ago by cpad011213k

if you take the course, you will see that by registering and requesting educational access, you get a free trial for 14 days - the course is completely free and the pipelines on the platform provide an output in R that you can download and modify.

ADD REPLYlink written 2.2 years ago by elia.brodsky330
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