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RNA-Seq|Hyperspectral Module: Partial least squares regression on transcript expression and hyperspectral data

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RNA-Seq & Hyperspectral PLSR

This script (i) splits combined RNA-Seq & hyperspectral data for each transcript into train and test datasets, (ii) runs variable selection to find the lowest MSE, and trained/calibrated using gene expression as response variable and spectral data of selected bands as explanatory variable.

Arguments

  • -c, --transcript_csv

    • CSV for a single transcript containing all spectra
  • -pod, --plot_out_dir

    • Plot/figure output directory
  • -cod, --csv_out_dir

    • CSV output directory (calibration, test, and permutation scores)
  • -o, --outdir

    • Main/root output directory
  • -m, --model_out_dir

    • PLSR model sav file output directory
  • -p, --permutation_out_dir

    • Permutation numpy array output directory
  • -t, --test_size

    • Test size for train/test split (default=0.25)

Running the script

To run the scrip, you have to specify at least the CSV:

./rnaseq_spectral_plsr.py -c ./rnaseq_spectra/Gh_A01G026200_tpm_spectra.csv

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RNA-Seq|Hyperspectral Module: Partial least squares regression on transcript expression and hyperspectral data

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