bpb3 --help usage: bpb3 []
Tasks available for using:
differential_expression Predict differentialy expressed genes (DEG) based on
two group of samples.
gene_regions Extracts regions near transcription start sites of selected
genes based on genCode gtf.
mussd Mutation filtering based on the Space and Sample Distribution
- MuSSD.
highly_mutated_blocks Find blocks with significantly more mutations than would be expected.
bayespi_bar BayesPI-BAR delta-dbA ranking computation for TF binding affinity
affected by DNA mutation.
choose_background_parameters Selects parameters for mutation background computation.
background_affinity_changes Mutation background computation.
affinity_change_significance_test Significant test of TF binding affinity changes
between foreground and background affinity changes.
parallel Run commands from the given file in parallel.
make_cluster4pwm Make input PWM files for bpb3 based on clustered PWMs.
bpb3selectedPWM The second level analysis of bpb3 by using the top PWMs in TF ranking
after the first level analysis of bpb3 based on the clustered PWMs.
run_pipeline Run full bpb3 pipeline (e.g., the first level analysis of bpb3 if
clustered PWMs are used in the calculation).
clean_tmp Clean temporary files from output folders.
Tasks available for demo purpose:
plot_result Generate heatmaps for selected mutation blocks. (demo)
filter_results_by_gene_expression_cluster4pwm Filter those TF whose expression is too
low in clustered PWMs. (demo)
filter_results_by_gene_expression Filter those TFs whose expression is too
low (e.g., RPKM<0.03). (demo)
make_plots_cluster4pwm Make heatmap plots for all significant mutation blocks
that affecting clustered PWMs. (demo)
make_plots Make heatmap plots for all significant mutation blocks
that affecting PWMs. (demo)
check_accuracy4cluster Check accuracy for 67 SNPs that based on clustered PWMs. (demo)
check_accuracy Check accuracy for 67 SNPs that based on original PWMs. (demo)
filterDEG4bpb3 Filter bpb3 exported differential expression gene list by rratios. (demo)
preprocess_icgc_data Preprocess of ICGC data such as a folder contains files donor_*,
specimen, simple_somatic*, exp_seq.tsv et al. (demo)
BayesPI-BAR in Python3 - bpb3
positional arguments: task Pipeline task to run
optional arguments: -h, --help show this help message and exit