This repository contains some additional analyses by Jesse Bloom related to metagenomic samples from the Huanan Seafood Market. The paper corresponding to this analysis is Bloom, Virus Evolution, vead089.

It builds on the analysis described in the earlier paper Bloom (2023) and contained in the repo for that paper at https://github.com/jbloom/Huanan_market_samples

Specifically, this repository also analyzes the number of viral reads mapping to several other coronavirus species found in animals in the market as noted by Crits-Christoph et al, bioRxiv (2023).

Interactive plots summarizing the key results about the mapping of reads to other coronaviruses are shown at https://jbloom.github.io/Huanan_market_samples_addtl_analysis

This repository contains a fully reproducible snakemake analysis in Snakefile, with the configuration in config.yaml. To run the pipeline first build the conda environment in environment.yml, and then run the pipeline.

In addition to the aforementioned interactive plots, the following output files are also tracked in this repo:

• results/fastqs_md5/check_vs_metadata.csv checks the downloaded FASTQs all have the correct checksums.
• results/viral_refgenomes/coronavirus_accessions.csv has the coronaviruses against which reads are aligned.
• results/viral_alignment_counts_and_coverage/aggregate_counts_and_coverage.csv has the read counts and coverage for the viral genomes for each sequencing run.
• results/merged_viral_and_mito_counts.csv has the per-sample viral read counts merged with the mitochondrial read counts taken from https://github.com/jbloom/Huanan_market_samples.
• results/analysis_plots has the HTML plots and the notebook that makes them.
• docs has the HTML rendering displayed on GitHub pages.

The following input data are used:

• data/CRA010170.xlsx is the GSA BioProject metadata sheet downloaded from the NGDC GSA page https://ngdc.cncb.ac.cn/gsa/browse/CRA010170 on March-29-2023.
• data/CritsChristoph_bioRxiv_2023_supp.xlsx is the supplementary material from Crits-Christoph et al, bioRxiv (2023), which contains as sheet S17 - Mammalian virus abundance all mammalian viruses that they found reads that mapped to.

Briefly, the pipeline consists of the following steps:

• Download all the metagenomic sequencing FASTQ files from the GSA and pre-process the reads

• Get the accessions of all coronaviruses with reads mapping to them in the analysis of Crits-Christoph et al, bioRxiv (2023), and trim the 3' polyA tails

• Align all the sequencing data to all the coronavirus genomes

• Tabulate the read counts for each sample against each coronavirus, using the mapping quality and read length / identity cutoffs specified in config.yaml

• Merge the coronavirus read counts with the species read counts previously reported in Bloom (2023) and contained in the repo for that paper at https://github.com/jbloom/Huanan_market_samples

• Make interactive summary plots for all samples.

• Copy the plots to the docs directory and make a HTML index for displaying on GitHub pages at https://jbloom.github.io/Huanan_market_samples_addtl_analysis