Hands on reproducible analysis of neuroimaging data: Nov. 2-3, UCSD: Reference

A command line shell is a powerful tool and learning additional ‘tricks’ can help make its use more efficient, less error-prone, and thus more reproducible

Shell scripting is the most accessible tool to automate execution of an arbitrary set of commands. This avoids manual retyping of the same commands and in turn avoids typos and erroneous analyses

Distribution and version control systems allow for the efficient creation of tightly version-controlled computation environments

DataLad assists in creating a complete record of changes

Coffee is essential!

Food cannot be controled/distributed by Git, but recipes could/should

Slides with solutions can be found in the sfn2018-training repository: https://github.com/ReproNim/sfn2018-training/tree/master/FAIR

There are a number of practical guidelines and best practices for ensuring data supports reproducible research

This module is in line with our overall goal of making science (including scientific training) more open by ensuring that data is made FAIR (Findabile, Accessible, Interoperable, and Reusable).

There are a number of tools and standards to assist in making data FAIR.

Food is necessary for our survival

Food cannot be controled/distributed by Git, but recipes could/should

it is possible and easy to create valid BIDS datasets straight from scanner with little of planing upfront

we can implement a complete imaging study using DataLad datasets to represent units of data processing

each unit comprehensively captures all inputs and data processing leading up to it

this comprehensive capture facilitates re-use of units, and enables computational reproducibility

carefully validated intermediate results (captured as a DataLad dataset) are a candidate for publication with minimal additional effort

we can implement a complete imaging study using DataLad datasets to represent units of data processing

each unit comprehensively captures all inputs and data processing leading up to it

this comprehensive capture facilitates re-use of units, and enables computational reproducibility

carefully validated intermediate results (captured as a DataLad dataset) are a candidate for publication with minimal additional effort

Coffee is essential!

Food cannot be controled/distributed by Git, but recipes could/should

Reproducible analysis is impacted by statistical analyses.

Reproducible research requires understanding the notions of sampling, testing, power, model selection.