March 12, 2019

Introduction to the program

  • Overview of the tools and resources for this program ( courses, projects and datasets and the T-BioInfo Analytics Platform)
  • Expectations and schedule review for the training program, important deadlines
March 19, 2019

Processing of NGS data

  • Role of pre-processing in standard RNA-seq pipelines (Trimmomatic and PCR-clean)
  • Mapping techniques: mapping on transcriptome, mapping on genome and combined strategies (Bowtie, BWA and TopHat/HiSat)
  • Quantification and Generating a table of expression: RSEM, HTSeq and Sailfish
March 26, 2019

Exploratory Data Analysis

  • Filtering, removing noise and Normalization Techniques
  • Exploring multi-dimensional data using PCA visualization
  • Principal Components and variance – outliers, filtering, normalization
April 2, 2019

Analysis of Gene Expression

  • Correlation – detecting correlation of features and factors
  • Clustering of samples using gene expression profiles
  • Clustering of genes by expression profiles across samples
April 9, 2019

Introduction to Supervised Data Mining

  • What is machine learning, categories of methods
  • Regression, factors and features – Factor Regression Analysis
  • Challenges associated with different kinds of machine learning
April 16, 2019

Using Machine Learning for Expression Data

  • Decision Trees, Discriminant Analysis and Support Vector Machines
  • Feature Selection and expanding the list of features
  • Data Visualization
April 23, 2019


  • Annotation using Gene Ontology
  • Human GAGE: Gene Set Enrichment Analysis
  • Statistical Significance and Reproducibility
Tuesday, April 23, 2019 – Thursday, May 23, 2019

Independent project work

More Information About the Long Term Bioinformatics Training Curriculum:

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