This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.
This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics.
This is a tutorial on using the open-source software PRSice to calculate a set of polygenic risk scores (PRS) for a study sample. Users will also learn how to read PRS into R, visualize distributions, and perform basic association analyses.
This lesson contains the slides (pptx) of a lecture discussing the necessary concepts and tools for taking into account population stratification and admixture in the context of genome-wide association studies (GWAS). The free-access software Tractor and its advantages in GWAS are also discussed.
This is a tutorial introducing participants to the basics of RNA-sequencing data and how to analyze its features using Seurat.
This tutorial demonstrates how to perform cell-type deconvolution in order to estimate how proportions of cell-types in the brain change in response to various conditions. While these techniques may be useful in addressing a wide range of scientific questions, this tutorial will focus on the cellular changes associated with major depression (MDD).
This lesson provides an overview of how to conceptualize, design, implement, and maintain neuroscientific pipelines in via the cloud-based computational reproducibility platform Code Ocean.
This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.
This hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines.
In this third and final hands-on tutorial from the Research Workflows for Collaborative Neuroscience workshop, you will learn about workflow orchestration using open source tools like DataJoint and Flyte.
This lesson provides an introduction to the DataLad, a free and open source distributed data management system that keeps track of your data, creates structure, ensures reproducibility, supports collaboration, and integrates with widely used data infrastructure.
This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments.
This lecture provides a detailed description of how to incorporate HED annotation into your neuroimaging data pipeline.
This lecture covers a wide range of aspects regarding neuroinformatics and data governance, describing both their historical developments and current trajectories. Particular tools, platforms, and standards to make your research more FAIR are also discussed.
In this tutorial, you will learn the basic features of uploading and versioning your data within OpenNeuro.org.
This tutorial shows how to share your data in OpenNeuro.org.
Following the previous two tutorials on uploading and sharing data with OpenNeuro.org, this tutorial briefly covers how to run various analyses on your datasets.
Explore how to setup an epileptic seizure simulation with the TVB graphical user interface. This lesson will show you how to program the epileptor model in the brain network to simulate a epileptic seizure originating in the hippocampus. It will also show how to upload and view mouse connectivity data, as well as give a short introduction to the python script interface of TVB.
In this lesson you will learn how to simulate seizure events and epilepsy in The Virtual Brain. We will look at the paper On the Nature of Seizure Dynamics, which describes a new local model called the Epileptor, and apply this same model in The Virtual Brain. This is part 1 of 2 in a series explaining how to use the Epileptor. In this part, we focus on setting up the parameters.
This lesson provides an overview of GeneWeaver, a web application for the integrated cross-species analysis of functional genomics data to find convergent evidence from heterogeneous sources.