[Neurodebian-users] ReproNim (Reproducible Neuroimaging) SFN Training Nov. 2-3
Yaroslav Halchenko
debian at onerussian.com
Wed Sep 12 17:57:46 BST 2018
Dear NeuroDebian folks,
If you are going to SfN, I would like to invite you to join the
pre-SfN training event where you might see some of the familiar
name/face(s) and learn more about how to make your neuroimaging research
more efficient and reproducible.
Cheers,
----- Forwarded message from info at humanbrainmapping.org -----
Date: Wed, 29 Aug 2018 10:38:05 -0500
From: info at humanbrainmapping.org
To: yoh at dartmouth.edu
Subject: ReproNim SFN Training Nov. 2-3
ReproNim SFN Training Nov. 2-3
Register: https://tinyurl.com/repronim-sfn18
Purpose:
An increasing body of evidence point to some issues in reproducibility in
biomedical or life sciences, raising concerns in the scientific community.
ReproNim has developed a curriculum that will give the students the
information, tools and practices to perform repeatable and efficient
research and a map of where to find the resources for deeper practical
training.
This training workshop will introduce material on the key aspects of
reproducible brain imaging and will orient attendees using a hands on and
practical experience to conduct neuroimaging analyses, using the next
generation of tools. By the end of this course, the student will be aware
of training materials and concepts necessary to perform reproducible
research in neuroimaging. The student will be able to reuse these
materials to conduct local workshops and training and be able to customize
the training for their specific scenario.
Prerequisites:
If you are a student, postdoc or researcher in life science who directly
works with neuroimaging data - or wish to work with these data, and you
have some basic computational background, this training workshop is for
you. You should have already done either some R, or Python, or Matlab or
Shell scripting, or have used standard neuroimaging tools (SPM, FSL, Afni,
FreeSurfer, etc) and be engaged in a neuroimaging research project. You
should have already completed a neuroimaging analysis or know how to do
one.
Modules:
Module Reproducibility Basics: Friday Nov. 2. 9am-10:45am.
This module guides through three topics, which are in the heart of
establishing and efficiently using common generic resources: command line
shell, version control systems (for code and data), and distribution
package managers. Gaining additional skills in any of those topics will
help you to not only become more efficient in your day-to-day research
activities, but also would lay foundation in establishing habits to make
your work more reproducible.
Module FAIR Data: Friday Nov. 2. 11am-12:45.
This module provides an overview of strategies for making research outputs
available through the web, with an emphasis on data. It introduces
concepts such persistent identifiers, linked data, the semantic web and
the FAIR principles. It is designed for those with little to no
familiarity with these concepts. More technical discussions can be found
in the reference materials.
Module Data Processing: Friday Nov. 2. 2pm-3:45pm.
This module teaches you to perform reproducible analysis, how to preserve
the information, and how to share data and code with others. We will show
an example framework for reproducible analysis, how to annotate,
harmonize, clean, and version brain imaging data, how to create and
maintain reproducible computational environments for analysis and use
dataflow tools to capture provenance and perform efficient analyses
(docker) and other tools.
Module Statistics: Friday 4pm-5:15pm
The goal of this module is to teach brain imagers about the statistical
aspects of reproducibility. This module should give you a critical eye on
the current literature and the knowledge to do solid statistical analysis,
understand the limitations of p-values, the notion of power and of
positive predictive values and how to represent evidence for results.
Reproducible publication project - Saturday 9am-12:00
This is an hands on session: small groups will work with the instructors
on the steps to deliver a fully reproducible publication.
Logistics:
Location: University of California San Diego (detail of location will be
given by email)
Dates: November 02-03, 2018.
How to register: https://tinyurl.com/repronim-sfn18
Costs: 25$.
Schedule:
Friday November 2nd:
8:30-9am: Introduction to the course and
participants “setup”
9am-10:45: Reproducibility Basics
10:45-11am : Coffee break
11am-12:45: FAIR data
12:45-2pm : Lunch+coffee
2pm-3:45: Data Processing
3:45-4pm: coffee break
4pm-5:15pm: Statistics for reproducible analyses
Saturday November 3rd:
9am-9:30: Questions and answers and feedback session
9:30-12pm: The Re-executable Micro Publication Challenge
During this time, we will propose a small challenge around producing an entirely re-executable
neuroimaging analysis from fetching data to producing statistical results. This will also be a
time with close interactions with
neuroimaging experts in data handling and analysis.
12pm-12:30: Closing session: feedback and future: “become a trainer”.
Online office hours will be held prior to the workshop. Registered
attendees will receive information via email.
Instructors: J. Bates, S. Ghosh, J. Grethe, Y. Halchenko, M. Hanke, C.
Haselgrove, S. Hodge, D. Jarecka, D. Keator, D. Kennedy, M. Martone, N.
Nichols, S. A. Abraham, J.-B. Poline, N. Preuss, M. Travers, and others
This workshop is brought to you by ReproNim: A Center for Reproducible
Neuroimaging Computation NIH-NIBIB P41 EB019936
----- End forwarded message -----
--
Yaroslav O. Halchenko
Center for Open Neuroscience http://centerforopenneuroscience.org
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419
WWW: http://www.linkedin.com/in/yarik
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