GRAND-SLAM analysis of SARS-CoV-2 data from Finkel et al., Nature 2021 (https://www.nature.com/articles/s41586-021-03610-3)

This is the processed SLAM-seq data from Finkel et al., Nature 2021 (https://www.nature.com/articles/s41586-021-03610-3). The zip file contains the full output from the processing pipeline (including the mapped reads, the scripts to run the pipeline and the output). The json file is required if you want to start from scratch. The file sars.tsv.gz is the GRAND-SLAM output table.

To generate the GRAND-SLAM output yourself, first prepare the human (ensembl v90) and the SARS-CoV-2 genome (NC_045512). Then run:

gedi -e Slam -trim5p 15 -reads sars.cit -genomic h.ens90 SARS-CoV2 -prefix grandslam_t15/sars -plot -progress

To generate the cit file you have to modify the first lines in start.bash to match the paths on your file system, and then run it.

You can also start from scratch (i.e., the json file):

1. Prepare the human genome (ensembl v90), the SARS-CoV-2 genome (NC_045512), the human rRNA sequence (U13369.1), and the Mycoplasma hominis sequence
2. Prepare the joint STAR index for the human and virus genome by calling gedi -e GenomicUtils -p -m star -g h.ens90 SARS-CoV2
3. Modify the starindex entry in the json file to match your file system
4. Run: gedi -e Pipeline -r parallel -j sars.json rnaseq_mapping.sh report.sh grandslam.sh

Software versions:

• gedi toolkit 1.0.4
• GRAND-SLAM 2.0.7
• cutadapt 3.4
• Bowtie 2 version 2.3.0
• STAR version 2.5.3a