CMash-reproducibles

For reproducibility analysis of CMash related tasks:

• 1. ISMB 2022 CMash manuscrip
• 2. CMash extended analysis (TBD)

Install dependencies

1. Install conda or miniconda (version >= 4.6)
2. Clone this repo

git clone https://github.com/KoslickiLab/CMASH-reproducibles.git

3. Get required tools/resources (only need to do once)

cd CMASH-reproducibles/src
bash 0.install_all_required_dependency_run_once.sh

4. Uninstall everything if necessary

cd CMASH-reproducibles/src
bash uninstall.sh

1. ISMB 2022 CMash manuscript

This is to reproduce the results in the CMash manuscript for ISMB 2022. Please follow Install dependencies above first to install all required dependencies.

1. regenerate all the output data (may take more than 1 day)

cd CMASH-reproducibles/src
nohup bash 1.reproduce_ISMB_2022_CMash_manuscript_results.sh  &  
#accept 1 positional parameter for thread number (default 16)

2. find the results

cd CMASH-reproducibles/1_ISMB_2022/
ls -d CMash_out_*  #output folder: CMash_out_${time_tag}

3. folder structure

# final_output: stores all final output files and Fig 1f, 2, and 3
# fig2_JI_estimation: intermediate outputs for pairwise JI estimation within Brucella genus
# fig3_CI_estimation: intermediate outputs for containment estimation of 1000 random genomes in the simulated metagenomic data
# Brucella_30 / random_1000 / simulation_200: downloaded genome files
# sup_f2_cmash_profile:  intermediate outputs for CMash profiling of one real world data for supplementary figure S2
# sup_f3_compare_sourmash_mash: intermediate outputs for comparison of CMash, Sourmash, and Mash for supplementary figure S3
# sup_f4_BF_distri: intermediate outputs for bias factor measurements for supplementary figure S4

2. CMash extensions

1. Rush implementation
2. Explore metagenomic dark matter
3. JI as function of k related to evolutionary distances