Key Concepts¶
Understanding the core concepts behind mokume helps you choose the right methods for your proteomics experiment.
Quantification¶
Protein quantification transforms peptide-level mass spectrometry measurements into protein-level abundance estimates. mokume supports multiple approaches, each with different trade-offs.
Normalization¶
Normalization corrects systematic biases between runs and samples so that intensity differences reflect true biological variation rather than technical artifacts.
Batch Correction¶
When samples are processed in multiple batches (different days, instruments, or labs), batch effects can dominate biological signal. ComBat-based correction removes these while preserving biology.
IRS Normalization¶
For multi-plex TMT experiments, Internal Reference Scaling uses shared reference channels across plexes to make protein intensities comparable.
Differential Expression¶
Differential expression analysis identifies proteins whose abundance changes significantly between conditions. mokume offers LimROTS, DEqMS, and proDA — each suited to different priorities.
Preprocessing Filters¶
Quality control filters remove low-quality features before quantification. mokume provides a comprehensive, configurable filter system.