README.md

SARS-CoV-2 build definitions for African and Malagasy Council of Higher Education (CAMES)

Build configuration for CAMES SARS-CoV-2 hosted at https://nextstrain.org/community/AlbertRockG/ncov-cames.

Instructions for running CAMES builds with GISAID data

Setup environment

It's up to you to choose your environment. Whichever you choose, feel free to check the documentation of nextstrain to install the required packages.

Setup repositories

git clone https://github.com/AlbertRockG/ncov-cames.git
git clone https://github.com/nextstrain/ncov.git
cd ncov
cp -r ../ncov-cames/cames_profile .
cp ../ncov-cames/builds_cames.yaml .

SARS-CoV-2 Build Definitions for African and Malagasy Council of Higher Education (CAMES)

Welcome to the repository for the SARS-CoV-2 genomics epidemiology analysis conducted for the Also-Covid-19 Project in collaboration with the African and Malagasy Council of Higher Education (CAMES).

Introduction

This project aims to provide comprehensive build configurations for CAMES SARS-CoV-2, hosted at Nextstrain Community Builds. The analysis focuses on understanding the genomic epidemiology of SARS-CoV-2 in African and Malagasy regions.

Getting Started

Setup Environment

Choose your preferred environment for running the analysis. Refer to the Nextstrain documentation for installing the necessary packages.

Setup Repositories

git clone https://github.com/AlbertRockG/ncov-cames.git
git clone https://github.com/nextstrain/ncov.git
cd ncov
cp -r ../ncov-cames/cames_profile .
cp ../ncov-cames/builds_cames.yaml .

Download data

Login to GISAID (gisaid.com) and select the "EpiCoV" link from the navigation.

Select the Downloads link from the EpiCoV navigation bar. Scroll to the Genomic epidemiologiy section and select the nextregions button. Select the Africa button. Save the file as hcov_africa.tar.gz in the ncov/data/ workflow directory.

Click Back to return to the main Download dialog, find the Download packages section, and select the FASTA button. Save the full GISAID sequence as data/sequences_fasta.tar.xz.

Select the metadata button from that same Download packages section and download the corresponding file as data/metadata_tsv.tar.xz.

Filter data

From an existing nextstrain conda environment, install extra tools to extract data from GISAID files.

# Install tsvutils and UCSC command to extract sequences.
# You only need to do this once.
conda activate nextstrain
conda install -c conda-forge -c bioconda tsv-utils ucsc-fasomerecords

Extract African metadata and sequences from full GISAID downloads.

# Get metadata for Africa directly from tarball.
tar xOf data/metadata_tsv.tar.xz metadata.tsv \
  | tsv-filter -H --str-in-fld Location:Africa \
  | xz -c -2 > data/metadata_africa.tsv.xz

# Get strain names for genomes.
# GISAID uses virus name, collection date, and submission date.
# delimited by a pipe character.

xz -c -d data/metadata_africa.tsv.xz \
  | tsv-select -H -f 'Virus\ name','Collection\ date','Submission\ date' \
  | sed 1d \
  | awk -F "\t" '{ print $1"|"$2"|"$3 }' > data/strains_africa.txt

# Get genomes for strain names from tarball.
tar xOf data/sequences_fasta.tar.xz sequences.fasta \
  | seqkit grep -n -f data/strains_africa.txt /dev/stdout \
  | xz -c -2 > data/sequences_africa.fasta.xz

Run builds locally

Navigate to the ncov workflow directory; these instructions assume this is a sibling directory to this repository. By defaul, the following command will run builds for all CAMES' countries, CAMES, and African's regions.

nextstrain build \
    --cpus 4 \
    --memory 8Gib \
    . \
    --configfile builds_cames.yaml \
    --config active_builds=CAMES

Visualize your builds

To visualize your builds, follow the tutorial under this link to install Auspice web App. Then run from ncov directory:

nextstrain view auspice

Acknowledgments

A heartfelt thank you to the PTR-SANTE CAMES Board and Dr Luc Salako Djogbenou for their unwavering support and valuable contributions to this initiative.