From b4bef4728066bc2309da6d6a5c4d29c4cb4c7e39 Mon Sep 17 00:00:00 2001 From: Saskia Hiltemann Date: Mon, 30 Sep 2024 06:59:14 +0000 Subject: [PATCH] add new recording from Google Form submission --- .../tutorials/vgp_workflow_training/tutorial.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/topics/assembly/tutorials/vgp_workflow_training/tutorial.md b/topics/assembly/tutorials/vgp_workflow_training/tutorial.md index 58f1d743e0b22a..bfb8ff94ae752f 100644 --- a/topics/assembly/tutorials/vgp_workflow_training/tutorial.md +++ b/topics/assembly/tutorials/vgp_workflow_training/tutorial.md @@ -58,12 +58,24 @@ recordings: captioners: - abueg bot-timestamp: 1726177737 +- youtube_id: TODO + length: 1H30M + galaxy_version: 24.1.3.dev0 + date: '2024-09-30' + speakers: + - mschatz + - delphine-l + captioners: + - mschatz + - delphine-l + bot-timestamp: 1727666641 --- + The {VGP}, a project of the {G10K} Consortium, aims to generate high-quality, near error-free, gap-free, chromosome-level, haplotype-phased, annotated reference genome assemblies for every vertebrate species ({% cite Rhie2021 %}). The VGP has developed a fully automated *de-novo* genome assembly pipeline, which uses a combination of three different technologies: Pacbio {HiFi}, {Hi-C} data, and (optionally) Bionano optical map data. The pipeline consists of nine distinct workflows. This tutorial provides a quick example of how to run these workflows for one particular scenario, which is, based on our experience, the most common: assembling genomes using {HiFi} Reads combined with {Hi-C} data (both generated from the same individual). >