Repository with basic files to reproduce SARS-CoV-2 phylogenetic analyses done by Grubaugh Lab.

This repository contains scripts for running pre-analyses to prepare sequence and metadata files for running augur and auspice, and for running the nextstrain pipeline itself.

To be able to run the pipeline determined by the Snakefile, one needs to set up an extended conda nextstrain environment, which will deploy all dependencies (modules and packages) required by the python scripts located at the scripts directory. Check each individual script in that directory to know what they do along the workflow.

Follow the steps below to set up a conda environment for running the pipeline.

Access a directory or choice in your local machine:

cd 'your/directory/of/choice'

Clone this repository ncov

git clone https://github.com/andersonbrito/ncov.git

Rename the directory ncov as you wish. Access the newly generated directory in your local machine, change directory to config, and update your existing nextstrain environment as shown below:

cd 'your/directory/of/choice/ncov/config'
conda env update --file nextstrain.yaml

This command will install all necessary dependencies to run the pipeline.

This minimal set of files and directories are expected in the working directory.

ncov/
│
├── auspice/ 			→ directory where the input for auspice will be stored
│
├── config/
│ ├── auspice_config.json	→ JSON file used to create the file used by auspice
│ ├── cache_coordinates.tsv 	→ TSV file with preexisting latitudes and longitudes
│ ├── clades.tsv 		→ TSV file with clade-defining mutations
│ ├── colour_grid.html 		→ HTML file with HEX colour matrices
│ ├── dropped_strains.txt	→ TXT file with IDs of sequences to be dropped along the run
│ ├── geoscheme.xml 		→ XML file with geographic scheme
│ ├── keep.txt 			→ TXT file with accession number of genomes to be included in the analysis
│ ├── nextstrain.yaml 		→ YAML file used to install dependencies
│ ├── reference.gb 		→ GenBank file of a reference genome
│ └── remove.txt 		→ TXT file with IDs of genomes to be removed prior to the run
│
├── pre-analyses/
│ ├── gisaid_hcov-19.fasta 	→ FASTA file with the latest genomes from GISAID
│ ├── new_genomes.fasta 		→ FASTA file with the lab's newly sequenced genomes
│ ├── metadata_nextstrain.tsv	    → nextstrain metadata file, downloaded from GISAID
│ └── COVID-19_sequencing.xlsx 		→ Custom lab metadata file
│
└── README.md

Files in the pre-analyses directory need to be downloaded from distinct sources, as shown below. Files in the pre-analyses directory need to be downloaded from distinct sources, as shown below.

Notes:
¹ FASTA file containing all genomes sequenced by the lab, including newly sequenced genomes
² The user will need credentials (login/password) to access and download this file from GISAID
³ This Excel spreadsheet must have the following columns, named as shown below:

• Sample-ID → lab samples unique identifier, as described below
• Collection-date
• Country
• State → state acronym
• Division → state full name
• Location → city, town or any other local name
• Host
• Source → lab source of the viral samples
• Update → number of the genome release, if new genomes are released in a regular basis

By running the command below, the appropriate files sequences.fasta and metadata.tsv will be created inside the data directory, and the TSV files colors.tsv and latlongs.tsv will be created inside the config directory:

snakemake preanalyses

By running the command below, the rest of the pipeline will be executed:

snakemake export

By running the command below files related to previous analyses in the working directory will be removed:

snakemake clean

Such command will remove the following files and directories:

results
auspice
data
config/colors.tsv
config/latlongs.tsv

This command will delete the directory pre-analyses and its large files:

snakemake delete

The code in scripts will be updated as needed. Re-download this repository (git clone...) whenever a new analysis has to be done, to ensure the latest scripts are being used.

• Anderson Brito - WebPage - [email protected]