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DE module Pipeline Specification

Pipeline Details

  • Name: DE module
  • Pipeline UUID: 7107a162a03a4d1fa8a9ae45335e96dd
  • Version: 2.1.5
  • View Pipeline:

Overview

DE module pipeline is designed for performing differential expression analysis on RNA-sequencing (RNA-seq) data using DESeq2 or Limma Voom software. It automates data preprocessing, quality control, statistical analysis, and visualization to ensure reliable and reproducible differential expression results.

Key Use cases:

  • Differential Gene Expression Analysis: Identify significantly up- and down-regulated genes between experimental conditions using DESeq2 or Limma Voom algorithms.
  • Multi-factor Design Support: Handle complex experimental designs including batch effects and multiple covariates with customizable design formulas.
  • Quality Control and Visualization: Generate comprehensive QC reports including PCA plots, count distributions, and sample correlation analyses.

Features

  • Support for Multiple DE Methods: Includes DESeq2 and Limma Voom algorithms for robust differential expression analysis.
  • Batch Effect Correction: Optional batch correction using CombatSeq package for improved data quality.
  • Comprehensive Quality Control: Implements distribution plots, PCA analysis, and reproducibility assessments with detailed visualizations.
  • Flexible Input Modes: Supports 'All' samples or 'Comparison-only' modes for DESeqDataSet creation to optimize dispersion estimation.
  • Multi-factor Design Support: Handles complex experimental designs with custom design formulas and interaction terms.
  • Automated Visualization: Generates summary reports, MA plots, volcano plots, and heatmaps for easy interpretation of results.

Input/Output Specification

Inputs

Required

Counts File

  • Description: A tab or comma separated file containing gene or transcript counts with samples as columns and features as rows.
  • Format: .tsv, .csv
  • Requirements: First column must contain unique feature names, header must contain sample names matching the groups file.

Groups File

  • Description: Sample metadata file specifying experimental conditions and covariates.
  • Format: .tsv, .csv
  • Required Columns: sample_name, group
  • Additional Columns: Optional metadata columns for multi-factor designs and batch correction.

Comparison File

  • Description: Specifies which groups to compare in differential expression analysis.
  • Format: .tsv, .csv
  • Required Columns: controls, treats, names
  • Optional Column: design (for custom design formulas)

Outputs

Reported Outputs

  • Differential Expression Results:
  • Description: Statistical results tables with fold changes, p-values, and adjusted p-values
  • Format: .csv
  • Visualization App: DE Browser, Excel

  • Location: Results folder

  • Quality Control Reports:

  • Description: PCA plots, count distribution plots, and sample correlation matrices
  • Format: .html, .png
  • Visualization App: Web browser, Image viewer

  • Location: QC folder

  • MA and Volcano Plots:

  • Description: Statistical visualization plots showing significance and fold change relationships
  • Format: .png, .pdf
  • Visualization App: Image viewer, PDF viewer
  • Location: Plots folder

Supporting Outputs

  • Normalized Count Matrices:
  • Description: DESeq2 or Limma Voom normalized expression values
  • Format: .csv

  • Location: Intermediate folder

  • Batch Corrected Data:

  • Description: CombatSeq batch-corrected count matrices when batch correction is enabled
  • Format: .csv
  • Location: BatchCorrection folder

Associated Processes

References & Additional Documentation