There are no NIDAP classes scheduled for November, 2021. Classes will return in December with expanded and improved tutorial videos. However the NIDAP platform will still be available to current NIDAP users as you work through your analyses.
If you are not a current NIDAP user and would like to have access to the videos and platform in November, please sign up here: https://www.surveymonkey.com/r/9K6SPWB
An account will be created on the NIDAP platform for you within 1-2 business days. You will be contacted with log-in instructions.
NIDAP is the NIH Integrated Data Analysis Platform (formerly Palantir). It is a free resource to NCI researchers that can be used to collaborate and perform basic bioinformatic analyses. We have bulk and single-cell RNA-seq workflows implemented on the platform and will be adding more in the near future. We also offer free training on how to use the platform to perform these workflows and understand the results. The platform is a graphic user interface and does not require researchers to know how to read or write programming code. However, if you are interested in that aspect of the analysis, all analysis code is easily viewable and open source.
Important Note: Each course consists of a self-guided series of videos that will require ~4 hours to complete. A video lecture will provide the background knowledge you’ll need to understand the analysis, then a series of video tutorials will allow you to follow-along and learn how to access and use NIDAP to perform a basic analysis on a training dataset. You will also be registered for a virtual Discussion webinar to occur at the end of the course and during which you can ask our instructors any questions you have about the material covered in the video tutorials or get help with any problems you encountered during the training analysis. After you have completed the video tutorials and attended one of our Discussion classes, you will be able to access further trainings to learn how to upload and analyze your own datasets to the NIDAP platform and attend virtual workshops with trainers to help you with any problems you may encounter that are specific to your datasets.
