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DTSTAMP:20260711T155248Z
UID:b91e72ce-3277-4417-aba8-1d300fa1cabf
DTSTART:20180820T150000Z
DTEND:20180820T163000Z
DESCRIPTION:#### Computational requirements for running the H3ABioNet GWAS 
 workflows\n\nThe first of a series of seven online lectures for Genome Wid
 e Association Studies (GWAS) will cover the technical requirements for set
 ting up a your computational environment for running the H3ABioNet GWAS wo
 rkflows. In this inaugural lecture of the series\, Prof. Hazelhurst will c
 over the the following topics:\n    Installing and using Nextflow\n    Ins
 talling and using Github\n    Use of containers for packaging and running 
 tools\n    Pulling the GWAS pipeline from Github and running it\n\nAs this
  lecture aims to provide attendees with an environment to the run the H3AB
 ioNet GWAS workflow at their own pace\, there are some preliminary softwar
 e requirements:\n    Either a Linux machine or an Apple running macOS\n   
  Ideally you should have machine with at least 2-4 cores and 8GB of RAM.\n
     Java 8\n    Nextflow installed (see installation instructions at https
 ://www.nextflow.io/)\n    Python 3\n\nPlease also install either Docker OR
  the following dependencies using pip3:\nPandas\, Matplotlib\, Openpyxl\, 
 SciPy\, NumPy\nPLINK 1.9\n\n[Please also refer to the following documentat
 ion to obtain the H3ABioNet GWAS workflow]:\nhttps://github.com/h3abionet/
 h3agwas/blob/master/README.md
SUMMARY:H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture serie
 s - Lecture 1
URL;VALUE=URI:https://www.youtube.com/watch?v=4_-pxWFUpfU&list=PLcQ0XMykNhC
 QJPz0amnbz9BPM4Bu0Nkgf
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