Run complete TSENAT analysis pipeline

Coordinates the full TSENAT workflow: diversity -> jackknife -> LM interactions -> divergence -> gene interactions -> rank-based tests -> concordance -> visualizations.

Usage

TSENAT(
  analysis,
  output_dir = "tsenat_outputs",
  save_output = TRUE,
  output_format = "tsv",
  verbose = TRUE
)

Arguments

analysis: TSENATAnalysis object created by build_analysis.
output_dir: character. Directory to save results and plots. Default: 'tsenat_outputs'. Set to NULL to disable automatic output saving.
save_output: logical. Whether to save output files (results tables). Default: TRUE. If FALSE, no TSV/CSV output files are written to disk.
output_format: character. Format for output files: 'tsv' (tab-separated), 'csv' (comma-separated), 'txt' (text), or 'rds' (R serialized). Default: 'tsv'.
verbose: logical. Print progress messages. Default: TRUE.

Value

TSENATAnalysis object containing complete analysis results, plots, and metadata.

Details

Pipeline execution order (enforced, follows TSENAT.Rmd vignette):

filter_analysis() - Filter low-abundance transcripts
calculate_diversity() - Tsallis entropy per q-value
plot_diversity_spectrum() - Visualize q-spectrum
calculate_m_estimator() - Sample influence QC analysis
calculate_lm() - LM interaction testing
plot_lm() - LM results visualization
calculate_jis() - Transcript switching detection
plot_jis_delta() - Multi-q influence heatmap (gene switching tables computed lazily via results())
plot_expression() - Top transcript visualization
calculate_divergence() - Pairwise divergence metrics
calculate_effect_sizes() - Effect size computation
plot_divergence_distribution() - Divergence distribution plot
plot_divergence_spectrum() - Divergence spectrum plot
calculate_assumptions() - Validate rank-based test assumptions
calculate_srh() - Scheirer-Ray-Hare rank-based interaction test
calculate_concordance() - Compare LM and rank test results

Examples

# \donttest{
data(readcounts, package = 'TSENAT')
metadata_df <- read.table(
  system.file('extdata', 'metadata.tsv', package = 'TSENAT'),
  header = TRUE, sep = '\t'
)
gff3_file <- system.file('extdata', 'annotation.gff3.gz', package = 'TSENAT')

config <- TSENAT_config(
  sample_col = 'sample',
  condition_col = 'condition',
  q = seq(0, 2, length.out = 10),
  generate_plots = FALSE
)
analysis <- build_analysis(
  readcounts = as.matrix(readcounts),
  tx2gene = gff3_file,
  metadata = metadata_df,
  config = config,
  tpm = tpm,
  effective_length = effective_length
)

result <- TSENAT(analysis)
#> Created output directory: tsenat_outputs
#> 
#> +============================================================+
#> |          TSENAT: Tsallis Entropy Analysis Toolbox          |
#> +============================================================+
#>                                                               
#>       Science is an essentially anarchic enterprise.          
#>                                                               
#>                        -- Paul Feyerabend, Against Method     
#>                                                               
#> [DATA] Data Summary
#>   Transcripts .......... 3,089
#>   Samples .............. 16
#>   Conditions ........... 2
#>   Q-spectrum range ..... 0 to 2 (10 values)
#> 
#> [CONFIG] Analysis Configuration
#>   Design ............... unpaired
#>   Filter stringency .... medium
#>   Normalization ........ enabled [0-1]
#>   Normalization method . range (default)
#>   Pseudocount .......... disabled
#>   Shrinkage ............ disabled
#>   Significance ......... p < 0.050 | FDR < 0.050
#>   LM method ............ GAM
#>   LM p-corr method ..... BH
#>   Jackknife use_lm_fdr . TRUE
#> 
#> =============================================================
#> [>] [ 1/14] Filtering low-abundance transcripts
#>           [OK] Complete
#> [>] [ 2/14] Computing Tsallis diversity
#>           [OK] 10 q-values processed
#> [>] [ 3/14] Plotting q-spectrum curve
#>           [OK] Plot generated
#> [>] [ 4/14] Running sample influence QC analysis (m-estimator)
#>           [OK] M-estimate QC complete
#> [>] [ 5/14] Testing LM interactions with GAM
#> Warning: nlminb problem, convergence error code = 1
#>   message = singular convergence (7)
#>           [OK] LM interaction analysis complete
#> [>] [ 6/14] Plotting LM interaction GAM smoother
#>           [OK] LM interaction plot generated
#> [>] [ 7/14] Computing jackknife isoform switching analysis
#>           [OK] Jackknife isoform switching complete
#> [>] [ 9/14] Plotting multi-q influence heatmap
#>           [OK] Influence heatmap generated
#> [>] [10/14] Plotting top transcript counts
#>           [OK] Top transcripts plot generated
#> [>] [11/14] Computing divergence metrics
#>           [OK] Divergence computed
#> [>] [12/17] Computing effect sizes for divergence
#>           [OK] Effect sizes computed
#> [>] [13/17] Plotting divergence distribution
#>           [OK] Divergence distribution plot generated
#> [>] [14/17] Plotting divergence spectrum
#>           [OK] Global divergence spectrum plot generated
#>           [OK] Multi-gene divergence spectrum plot generated
#> [>] [15/17] Validating rank-based test assumptions
#>           [OK] Assumptions validated
#> [>] [16/17] Running Scheirer-Ray-Hare rank-based test
#>           [OK] Scheirer-Ray-Hare test completed
#> [>] [17/17] Computing concordance between LM and rank test results
#>           [OK] Concordance analysis completed
#> =============================================================
#> 
#> +============================================================+
#> |               [OK] ANALYSIS COMPLETE                       |
#> +============================================================+
#> 
#> [RESULTS] Results Summary
#> 
#> [PERF] Performance
#>   Total time ........... 24.3s
#>   Slowest steps:
#>     1. lm_interaction       13.0s (53.4%)
#>     2. lm_plot              2.4s (10.0%)
#>     3. jackknife            2.3s (9.5%)
#> 
#> [OUTPUT] Output
#>   Directory ........... tsenat_outputs
#>   Files saved ......... 18
#> 
#> [TIPS] Extract Results - Common Examples:
#>   # View object structure
#>   show(result)
#> 
#>   # View detailed statistics summary
#>   summary(result)
#> 
#>   # Tsallis Entropy Diversity
#>   # Get results for specific sample at q=1.0
#>   div <- results(result, type = 'diversity',
#>                  n_genes = 4, sample = 'SRR14800481')
#> 
#>   # Linear Model Interaction Results
#>   # Top 10 genes by p-value
#>   lm <- results(result, type = 'lm',
#>                 rankBy = 'pvalue', n = 10)
#> 
#>   # Visualizations
#>   plot_diversity <- results(result, type = 'diversity', plot = TRUE)
#>   plot_lm <- results(result, type = 'lm', plot = TRUE)
#> 
# }