SvR

Spatial Extension of the SvR BioEssays Paper (Suppression versus Replacement)

MGDrivE Experiments Pipeline

These sets of experiments involve the transition between MGDrivE1 and MGDrivE2, so there is an additional toggle in the data analysis routines to accommodate both types of datasets.

Spatial Experiments and Preprocess

Setup the factorial experiment in the Rscript and run the following command:

./STP_simAndPreProcess.sh srv 265 SPA v1 True

This should auto-run the factorial and place the results in the RAID5 drive. After running the sims, it should startup the preProcess followed by the preTraces and preGrids (these two are optional).

Spatial Analysis Breakdown

1. Run the STP_geoCluster.py script with the desired level of aggregation for analysis
2. Run STP_preProcess.sh for ECO, HLT, WLD, TRS PREPROCESS
3. Run STP_preTraces.sh for ECO, HLT, WLD, TRS preTraces and preGrids
4. Run STP_preVideo.sh for desired videos (probably HLT)
5. Run STP_pstProcess.sh for HLT, WLD, TRS post process

Experiments Nomenclature

Folders and files follow this naming convention:

• E_rer_ren_rsg_fic_gsv
  • rer: Release ratio (x1e8)
  • ren: Number of weekly releases (x1)
  • rsg: In and out of frame resistance generation (x1e8)
  • fic: Trans-gene fitness cost (x1e8)
  • gsv: Genetic standing variation (x1e8)

For the breakdown of the AOI sets, look at the gene definitions STP.

Exported metrics (MOI) for the drive are:

• WOP: Total sum of time below the threshold
• TTI: First break below the threshold
• TTO: Last break below the threshold
• RAP: Fraction of the population with the genes at given points of time
• MNX: Minimum and maximum of genes in the population

Summary statistic files follow this naming convention:

• AOI_MOI_QNT_qnt.csv

Where the main AOI was HLT (presence of mosquitoes) and the outputs (labels) are:

• TTI, TTO, WOP: Fraction's threshold for the metric to be true
• RAP: Fraction of present genotypes at given points (days) of the simulation
• MNX: Min/Max and days at which these are achieved

Classifier

To put all the data through the ML classification pipeline, run:

chmod +x STP_clsPipeline.sh
./STP_clsPipeline.sh

which launches the following scripts in order:

1. STP_clsPreUnify
2. STP_clsPreprocess
3. STP_clsTrain

Summary datasets are named as follows:

• D_SEX_AOI_MOI_QNT_qnt.csv: Experiment set for each of sexes combinations in the releases.
• Full_AOI_MOI_QNT_qnt: Collated dataset with sexes variable added as column.
• CLN_AOI_MOI_QNT_qnt: Collated dataset with sexes variables one-hot encoded.

For the AOI definitions, look at the .

ASTMH Poster

• STP_cmprReleasesASTMH

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