Intro to Bioinformatics for NGS Data

This course will cover some examples of using the Tufts High Performance Compute Cluster (HPC) to manipulate Next Generation Sequencing (NGS) data.

Topics covered include quality control, read alignment, transcript quantification and visualization.

It is recommended to take the “Introduction to Linux” and “Introduction to Tufts HPC” workshops in preparation for this class. An account on Tufts HPC Cluster is required, see below for instructions**.

MedfordBoston
Friday, December 6, 2019
10 am -12 pm
Mark Lab Rm 103, Tisch Library
Register here
Tuesday, December 10, 2019
10 am -12 pm
Sackler 514
Register here

Introduction to Tufts High Performance Compute Cluster

This workshop is a brief introduction of the structure of the Tufts HPC cluster, as well as the basic usage of it’s scheduler “SLURM”. 

This is a hands-on workshop and an account on the HPC cluster is required**.

Basic Linux knowledge is required. If you are not familiar with Linux, please check out our “Introduction to Basic Linux Workshop”.

MedfordBoston
Friday, October 25, 2019
10 – 11:30 am
Mark Lab Rm 103, Tisch Library
Register here
Tuesday, October 22, 2019
10 – 11:30 am
Sackler 514
Register here

Introduction to Linux

This is designed to be an introductory level workshop on Basic Linux (the command line environment and some useful commands).

This is a hands-on workshop and an account on the HPC cluster is required**.

No previous Linux experience is required.

MedfordBoston
Friday, October 11, 2019
10 am -12 pm
Mark Lab Rm 103, Tisch Library
Register here
Tuesday, October 15, 2019
10 am -12 pm
Sackler 514
Register here

**REQUIRED** Workshops utilize the Tufts High Performance Computer Cluster. If you don’t already have access to Tufts HPC cluster, please go to https://research.uit.tufts.edu/ and fill out the “Request account for Research Computing Cluster” Form at least 2 days before the workshop.

TTS offers workshops on many other topics on both the Medford and Boston campuses on which can be found on the Data Lab Website