Expansion of Armatimonadetes through marine sediment sequencing reveals three classes with unique ecological roles
Repository that contain the main data and scripts to compute the supplementary figure from:
Carlton et al.,
Last updated: Feb 2023
Steps to compute MEBS scores in 77 MAGs + references described in the study contained in the folder.
- Compute scores and metabolic completeness (Supplementary Table X)
perl mebs.pl -input <zipacna genomes faa> -type genomic -comp > zipacna.tsv
- Normalize scores, generate figures and generate MEBS files to map to itol or perform downstream clustering analyses
This script will generate a directory named zipacna.tsv_vis_out/ files and figures
python3 mebs_vis.py zipacna.tsv
Using the script from the Useful scripts github repo, we used the output derived from step 2 to generate a hetmap with the completeness of serval metabolic pathways predefined in MEBS
python3 heatmap.py -f pdf data_heatmapZipacna.tsv
- Generate the clustering visualization with the file that contains the normalized scores of a data set of 2,107 non redundant genomes internaly storage in MEBS + scores of the genomes described in this study + references found in Supplementary Table 2
python3 F_MEBS_cluster.py --all zipacna.tsv_vis_out/zipacna.tsv_2_cluster_mebs.tsv
- Using the above information, we decided to project the data using pca using kmeans as clustering method
python3 F_MEBS_cluster.py -p pca -c kmeans zipacna.tsv_vis_out/zipacna.tsv_2_cluster_mebs.tsv
