Genomics is the study of whole genomes of organisms, and incorporates elements from genetics. Genomics uses a combination of recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble, and analyse the structure and function of genomes.

Introduction: Gene expression can be studied through microarray experiments that interrogate genomewide transcripts to understand the underlying mechanisms of gene regulation in samples of interest. This course teaches researchers to perform analysis on Affymetrix data and transform a chip image to a list of genes that are up or down-regulated in an experiment. Various tools will be covered - Affymetrix Expression Console (replacing GCOS), Microsoft Excel, MathWorks MATLAB, and free tools like R/Bioconductor and dChip. It is geared towards researchers who conduct microarray experiments to study genome-wide expression changes and understand the underlying mechanisms of gene regulation in samples of interest.


Why learn gene expression analysis? Most scientists are not able to analyze microarray data themselves and are not able to get desired results using traditional computer tools like Microsoft Excel or even with advanced software provided by commercial vendors. The freeware solutions come either with a steep learning curve or as black-box interfaces that provide limited functionality with little or no technical support. In the midst of all this is the fundamental lack of understanding among scientists on how the technology works and what the fundamental parts of the analysis are is striking. This course demystifies the analysis.


Logistics: The course is divided into 8 sessions with pre-recorded videos, handouts, reference cards, examples, data, scripts and quizzes. Enrollees can contact the instructor with questions and get help on the projects. The main topics are listed below. Homework assignments will involve running commands learned in the live lectures.


Introduction: No experience is required, although prior experience with any other programming language will be helpful. Math skills will also be useful.

Price: $2400 for Commercial/Government enrollees and $1200 for Academic researchers and students.

Syllabus:

  • - Expression Console for DAT->CEL->CHP. Quality metrics
  • - Creating and saving experiments, importing and exporting data, normalization settings
  • - Data transformation, filtering, hypothesis testing, differential expression analysis
  • - Dchip software
  • - R and Bioconductor
  • - Matlab and bioinformatics toolbox
  • - Clustering and classification for biomarker discovery
  • - Gene set, pathway and ontology enrichment analysis

Introduction: Genomewide SNP genotypes can be determined through microarray experiments so we can identify variants that cause disease. This course teaches researchers to perform analysis on Affymetrix data and transform a chip image to genotypes for each SNP and even the copy number. Various tools will be covered such as GCOS, GTYPE, BRLMM, CNAT, Excel, MATLAB and dChip.


Why learn SNP genotyping analysis: Most scientists are not able to analyze microarray data themselves and are not able to get desired results using traditional tools like Microsoft Excel or even advanced software provided by commercial vendors. The free solutions come either with a steep learning curve or as black-box interfaces that provide limited functionality, with little or no technical support. In the midst of all this is the fundamental lack of understanding among scientists on how the technology works and what the fundamental parts of the analysis are. This course demystifies the analysis.


Logistics: The course is divided into 8 sessions with pre-recorded videos, handouts, reference cards, examples, data, scripts and quizzes. Enrollees can contact the instructor with questions and get help on the projects. The main topics are listed below. Homework assignments will involve running commands learned in the live lectures.


Requirements:No experience is required, although prior experience with a programming language will be helpful. Math skills will also be useful.


Price: $2400 for Commercial/Government enrollees and $1200 for Academic researchers and students.


Instructor: Shailender Nagpal


Syllabus:

  • - Introduction to GCOS for working with Affymetrix genotyping chips
  • - Algorithms, tools for generating genotypes - GTYPE, BRLMM
  • - Sample mismatch report, gender calls, pedigree check, creating virtual sets
  • - dChip software: various analysis
  • - Matlab software: various analysis
  • - Creating PLINK ped and map files for linkage analysis

Introduction: Image processing is a set of computational techniques to analyze, manipulate and process biological images, then extract meaningful information from them.


Why learn Image Processing? For large quantities of images that need to be analyzed with the same algorithm, the course teaches how to automate these routine tasks and generate reports in a high throughput fashion. Researchers will save time!


Logistics: The course is divided into 4 sessions with pre-recorded videos, handouts, reference cards, examples, data, scripts and quizzes. Enrollees can contact the instructor with questions and get help on the projects. The main topics are listed below. Homework assignments will involve running commands learned in the live lectures.


Requirements: No experience is required, although programming experience will be useful


Price: $1200 for Commercial/Government enrollees and $600 for Academic researchers and students


Instructor: Shailender Nagpal


Syllabus:

  • - Types of image file formats
  • - How image data is stored
  • - Simple operations such as zoom, pan, rotate, crop
  • - Contrast and brightness adjustment, sampling, transformation
  • - Image filtering, registration, morphological operations
  • - Noise removal, image deblurring, image conversion, edge detection
  • - Automation and application development

Introduction: This course provides attendees with a basic overview of how and where bioinformatics is used and applied.


Logistics: Shailender Nagpal

Requirements: Unknown

Instructor: Shailender Nagpal

Introduction: Primers are short oligonucleotide sequences that are designed to hybridize to their complementary targets on the template DNA, to create a PCR amplicon. This course teaches biologists how to design probes and primers for various DNA and RNA based assays or experiments.


Why learn Primer Design? Those involved in conducting qualitative or quantitative PCR reactions will know the importance of good initial design principles to ensure success with PCR and to identify reasons for failure or low sensitivity and specificity.


Logistics: The course is divided into 4 sessions with pre-recorded videos, handouts, reference cards, examples, data, scripts and quizzes. Enrollees can contact the instructor with questions and get help on the projects. The main topics are listed below, but we teach mostly everything there is to know about NGS analysis. Homework assignments will involve running commands learned in the live lectures. A background in molecular biology is required to understand principles of PCR.


Price: $1200 for Commercial/Government enrollees and $900 for Academic researchers and students. Discounts are available for multiple attendees from the same organization or for individuals taking multiple courses. To sign up, click here.

Instructor:

Syllabus:

  • Role of short oligonucleotides in biology
  • Applications-various experimental techniques like PCR, aCGH, cloning, exome-capture
  • Primer design criteria and characteristics of primers for singleplex and multiplex assays
  • Primer picking for various types of assays
  • Target identification and target region selection
  • ePCR and eDigest