statTarget

statTarget performs quality control, shift signal correction, multi-batch data integration, and statistical analysis of targeted and non-targeted metabolomics datasets.

Key Features:

• Quality Control and Shift Signal Correction: Implements mechanisms to identify and correct signal shifts and batch effects across metabolomics datasets.
• Integration of Multi-Batch Data: Supports integration of metabolomic measurements from multiple experimental batches to reduce inter-run variability.
• Comprehensive Statistical Analysis: Provides statistical workflows for both non-targeted and targeted metabolomics enabling exploratory and confirmatory analyses.
• Bioconductor Integration: Leverages the Bioconductor ecosystem for interoperable bioinformatics and statistical packages.
• Implementation in R: Executes analyses within the R statistical programming environment.

Scientific Applications:

• Metabolomics preprocessing and QC: Preprocesses and performs quality control on high-throughput metabolomics data.
• Batch-effect correction in large-scale studies: Corrects batch-related biases in multi-batch metabolomics experiments.
• Targeted and non-targeted analysis: Supports statistical analysis for both targeted metabolite quantification and non-targeted metabolite profiling.
• Integration with genomics and molecular biology workflows: Integrates metabolomics analyses into broader Bioconductor-based genomics and molecular biology pipelines.

Methodology:

Implements analyses in the R programming language by leveraging Bioconductor and its >934 interoperable packages, which are subject to initial review and continuous automated testing.