This tutorial describes the dbSNP resources in the UCSC Genome Browser, including display conventions and the subdivision of the data into several useful subset tracks, especially the Common SNPs. There is also a discussion about changes to the genome assemblies from one version to another, and of two ways to navigate between different assemblies of the human genome in the Browser.
This tutorial demonstrates the Data Integrator, a tool that allows combination and intersection of data from up to five primary tables. In the example, data are extracted showing SNPs, genes and phenotypes from a genomic region.
This tutorial shows how to obtain coordinates of genes, then input those coordinates into the Genome Browser for display. The regions do not have to be continuous in the genome.
This tutorial demonstrates the Multi-Region exon-only display mode of the UCSC Genome Browser.
This tutorial demonstrates viewing alternate haplotypes with the UCSC Genome Browser.
This tutorial demonstrates how to get the coordinates and sequences of exons using the UCSC Genome Browser.
This tutorial will demonstrate how to locate amino acid numbers for coding genes using the UCSC Genome Browser.
This tutorial will demonstrate how to find the tables in the UCSC database that are associated with the data tracks in the Genome Browser graphical viewer.
This tutorial shows how to navigate between exons of a gene using the UCSC Genome Browser.
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 lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below.
This tutorial talks about how to upload and version your data in OpenNeuro.org
This tutorial shows how to share your data in OpenNeuro.org
This tutorial shows how to run analysis in OpenNeuro.org
An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.
Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (antibodies, model organisms and software projects) in the biomedical literature to improve transparency of research methods.
This session will include presentations of infrastructure that embrace the FAIR principles developed by members of the INCF Community. This lecture provides an overview and demo of the Canadian Open Neuroscience Platform (CONP).
This video gives a short introduction to the EBRAINS data sharing platform, why it was developed, and how it contributes to open data sharing.