EcoAtom

• https://doi.org/10.3389/fmicb.2023.1178131
• https://github.com/ph-u/biLVC
• https://github.com/ph-u/UKCFRegDataSorting
• https://github.com/ph-u/UKCFRegDNase

Overview

Analytics for pairwise ecological interactions of taxa categories (interactome) using time-series abundance records. Pipeline is built based on Bayesian Inference adaptive Markov Chain Monte Carlo with generalized Lotka-Volterra equation.

Requirements

• R >= 3.3.3
• R pkg: FME(1.3.6.2), deSolve(1.30), rootSolve(1.8.2.3), coda(0.19.4)
• GNU bash (platform tested):
• 4.2.46(2)-release (x86_64-redhat-linux-gnu)
• 5.1.16(1)-release (x86_64-pc-linux-gnu)

Updates

EcoAtom

2.0.0

• SLURM system optimization
• Backward incompatible with ver 1 (BaMGS)
• array jobs submission

BaMGS

1.0.1

• Bugs fixed
• Filnames with "p_" string now segregated with prefix "p_"; prefix "p_" is for skipping respective data from processing)
• R 4.3.1 adaptation on dataframe handling (eCology.r)
• Fix scenario when no simulations matching data (eCology.r)
• Modified CPU cluster partition (skylake retired in late Aug-2023, new nodes added into icelake in the CSD3 cluster)

1.0.0 Initial release (https://doi.org/10.3389/fmicb.2023.1178131)

Usage

1. Rscript cutTime.r [basename] [time...]
   • optional step
   • indicate the overall time-series file in [basename]
   • indicate every timepoint in data need to be separated
   • generate series of files between consecutive indicated cut times
2. bash biLVary.sh 1 [replicate] [sample (*100,000)] [raw data directory name]
   • generate prior boundaries & starting values
   • generate simulation seed numbers
   • generate population time-series values (auto-identify whether raw data need log_e transformation or not)
3. bash biLVary.sh 2 [replicate] [sample (*100,000)] [raw data directory name]
   • plot MCMC trace graphs
   • output best-fit 0.1% (min output = 100) parameter combinations as spreadsheets
4. bash biLVary.sh 3 [replicate] [sample (*100,000)] [raw data directory name]
   • group parameter combinations into pairwise ecological relationships
5. for i in `[path/2/\*-rec.txt]`;do echo -e "${i}"; bash SimDataPlot.sh ${i};done
   • optional step
   • plot simulations on top of time-series data
   • calculate proportion of simulations matching data (+/- 10% tolerance for single data point time-series, 50% data range for data with replicates)
6. Rscript ecoBars.r [path/2/data] [sampleFreq_basename] [replicate] [simulation_output_size] [log10?]
   • optional step (R >= v4.0.0)
   • plot sample size of groups (log10 or raw frequency)
   • plot overview stacked bar plot of pairwise ecological relationship distributions across all replicates