Git Product home page Git Product logo

hts_workshop2019's Introduction

A Practical Introduction to Data Analysis for Genomics and Transcriptomics - KAUST 2019

Table of Content

About

Genomics and transcriptomics are rapidly becoming standard methods to examine living systems. This workshop provides an introduction to the methods and tools used to analyse next-generation-sequencing data, provides understanding of its limitations and a basic understanding on how the analysis algorithms work. This workshop will take the participants through an example project demonstrating how to evaluate the quality of data as provided by a sequencing facility, how to perform a de-novo genome assembly, and how to align the data against a known and annotated reference genome. Furthermore, participants will learn how to compare transcription data between different samples.

The workshop is scheduled for 18th - 22nd of August, from 9:30 to 17:00, and will consist of seminars intertwined with hands-on sessions and discussions. The course is open for all students, postdocs and research scientists of BESE division.

Major topics to be covered: Genome assembly, Transcriptomics, Visualization and Tips/tricks.

Program

Sunday - 18th of August, Building 5, Level 5, Room 5220: The Tools of Computational Biology

  1. Introduction to programming basics
  2. Utility commands in data management
  3. Common file formats in NGS data
  4. Introduction to High-Performance Computing environment

Monday - 19th of August, Building 5, Level 5, Room 5220: Where do the data come from?

  1. Introduction to Next-Generation-Sequencing
  2. Quality control on raw data
  3. Assembling a small genome sequence

Tuesday - 20th of August, Building 3, Level 5, Room 5220: How to make a genome

  1. Assembly QC
  2. Annotating genes
  3. Using long reads for assembly
  4. Hybrid Assembly QC

Wednesday - 21th of August, Building 3, Level 5, Room 5220: How to quantify transcription

  1. Experimental design and strategies
  2. Data cleaning + mapping
  3. Quantification
  4. Visualization

Thursday - 22th of August, Building 3, Level 5, Room 5220: How to compare transcription between samples

  1. Differential expression
  2. Functional annotation
  3. Alternative splicing
  4. Summary + QA + Recap

Speaker

  • Arun Nagarajan, PostDoc at KAUST, is interested in understanding the molecular mechanism of acclimatization to stress by a biological organism using new-age technology.
  • Robert Lehmann, Research Scientist at KAUST, integrates genetic and transcriptomic data to gain insights into genetic responses to stress in established model organisms as well as new marine model organisms.
  • Octavio Salazar Moya, PostDoc at KAUST, is interested in increasing food production, particularly by increasing salt tolerance of plants.
  • Manjula Thimma, Research Scientist at KAUST, is interested in understanding the role of retrotransposons in cell identity, reprogramming and differentiation.
  • Alaguraj Veluchamy, Research Scientist at KAUST, is interested in TBA

Location

TBA

Contacts

hts_workshop2019's People

Contributors

roblehmann avatar

Watchers

James Cloos avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.