ajodeh-juma/ilri-africa-cdc-training

--- title: README.md tags: ["SARS-CoV-2", "Genomics", "Bioinformatics", "Metadata", "Linux", "Analysis", "Activity"] --- # **Building capacity in SARS-CoV-2 genomics in Africa** --- ###### ***Trainers***: John Juma, Ouso Daniel & Gilbert Kibet --- - Introduction - Scope - Background - Prerequisite - Set-Up - Preparations - Log into the HPC - Project Organisation - Data retrieval and integrity checks - Analysis - Loading modules - Prepare the reference genome - Quality assessment - Quality and Adapter filtering - Decontamination - Alignment - Sort and Index alignment map - Primer trimming - Compute coverage - Variant calling - Variant annotation - Consensus genome assembly - Pangolin: Lineage assignment - Nextclade: Clade assignment - Summarize results - Download reports - Data Retrieval and Review - Transfer of data: MiSeq - Transfer of data: MinION - Reviewing data: Illumina - Reviewing data: ONT - Working with metadata - Galaxy workflows for SARS-CoV-2 data analysis - Activity - Galaxy Exercise ## Introduction In early January 2020, the novel coronavirus (SARS-CoV-2) responsible for a pneumonia outbreak in Wuhan, China, was identified using next-generation sequencing (NGS) and readily available bioinformatics pipelines. In addition to virus discovery, these NGS technologies and bioinformatics resources are currently being employed for ongoing genomic surveillance of SARS-CoV-2 worldwide, tracking its spread, evolution and patterns of variation on a global scale. ## Scope In this short workshop we will tackle, hands-on, the basic principles employed by the numerous bioinformatic pipelines: to generate consensus genome sequences of SARS-CoV-2 and identify variants using an actual dataset generated in our facility. > **Note** > This is part of the initiative fronted by the Africa CDC with generous support from the Rockeffeler foundation to build capacity in pathogen genomics in Africa. ## Background We will use a dataset comprising of raw sequence reads of S …