Chapter 7 Standalone analyses

7.1 BayesPrism

BayesPrism performs immune deconvolution of a TPM matrix using a single-cell reference.

iobrpy bayesprism \
  -i "$IOBRPY_DEMO/results_star/03-tpm/count2tpm.csv" \
  -o "$IOBRPY_DEMO/bayesprism" \
  --threads 8

The output directory contains:

$IOBRPY_DEMO/bayesprism/
├── theta.csv
├── theta_cv.csv
└── Z_tumor.csv

7.2 TME clustering

TME clustering groups samples according to their tumor microenvironment profiles.

iobrpy tme_cluster \
  -i "$IOBRPY_DEMO/results_star/05-tme/cibersort_results.csv" \
  -o "$IOBRPY_DEMO/tme_cluster.csv" \
  --features 1:22 \
  --id "ID" \
  --min_nc 2 \
  --max_nc 5 \
  --print_result \
  --scale

7.3 NMF clustering

NMF clustering identifies latent sample groups from a feature matrix.

iobrpy nmf \
  -i "$IOBRPY_DEMO/results_star/05-tme/cibersort_results.csv" \
  -o "$IOBRPY_DEMO/nmf" \
  --kmax 5 \
  --features 1:22

The output directory contains:

$IOBRPY_DEMO/nmf/
├── clusters.csv
├── pca_plot.png
└── top_features_per_cluster.csv

7.4 HLA typing

iobrpy hla_typing \
  -b "$IOBRPY_DEMO/results_star/02-star" \
  -r hg38 \
  -o "$IOBRPY_DEMO/hla_typing" \
  -j 8

The output directory contains:

$IOBRPY_DEMO/hla_typing/
├── ExtractHLAread/<sample>/
├── SpecHLA/<sample>/hla.result.txt
└── hla_result_merged.txt