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Discipline 16 of 18 38 Tools Stage 16: Extended Multi-Omics & Targeted Protocols

🎯 16. Specialized NGS Applications & Emerging Frontiers

Genome-wide CRISPR pooled screens, viral surveillance and wastewater tracing, mass spectrometry bottom-up proteomics, LC-MS metabolomics, and ancient DNA paleogenomics.

Essential Software: MAGeCK CRISPResso2 iVar MaxQuant DIA-NN MZmine 3
Comparative Analysis Production Benchmarks

Algorithm Architecture & Decision Matrices

Detailed comparison cards highlighting algorithmic trade-offs, strengths, weaknesses, and recommended production setups.

CRISPR Screening & Immune Repertoire
MAGeCK CRISPResso2 PinAPL-Py BAGEL2 DrugZ MiXCR IgBLAST TRUST4 IMGT/HighV-QUEST scRepertoire Immunarch
Genome-wide CRISPR-Cas9/Cas12 screens, guide RNA depletion/enrichment, NHEJ/HDR editing efficiency, and bulk/single-cell TCR/BCR clonality tracking.
Viral Surveillance & Liquid Biopsy MRD
iVar LoFreq V-pipe nf-core/viralrecon Pangolin Nextclade Freyja ichorCNA CAPP-Seq fgbio MRDetect Mutascope
Primer trimming and amplicon viral variant calling (SARS-CoV-2/RSV/Influenza), wastewater lineage deconvolution, and circulating tumor DNA MRD monitoring.
Small RNA, Epitranscriptomics & Fusions
miRDeep2 ShortStack sRNAbench REDItools RNAEditor riboWaltz RiboTaper rMATS MAJIQ SUPPA2 STAR-Fusion Arriba FusionCatcher Trinity
miRNA discovery, direct A-to-I RNA editing detection, Ribo-seq active translation decoding, complex local splicing variations, and oncogenic gene fusion detection.
Hardware & Execution Profiles

Primary Software & Algorithms in Specialized Applications & Multi-Omics

Direct command-line recipes, Conda environment specifications, memory footprints, and license metadata.

Quantitative Proteomics
🚀 32GB+ RAM C# / .NET • Andromeda Engine

MaxQuant

Docs ↗ By Jürgen Cox & Matthias Mann (Max Planck)
(License: Freeware (Academic))

Comprehensive proteomics software package for high-resolution mass spectrometry. Features Andromeda peptide search, label-free quantification (MaxLFQ), SILAC, and TMT multiplexing.

Formats: Input: Thermo RAW, Bruker .d, AB SCIEX • Output: proteinGroups.txt, peptides.txt
💻 16-32 CPU Cores • 32-64 GB RAM • Fast SSD
conda install -c bioconda maxquant
Deep Learning DIA Proteomics
💻 16-32GB RAM C++ • Neural Networks

DIA-NN

Docs ↗ By Vadim Demichev Lab (Charité / Francis Crick)
(License: CC-BY 4.0)

Universal deep learning software for Data-Independent Acquisition (DIA) and high-throughput proteomics. Performs spectral library-free DIA processing with exceptional speed and depth.

Formats: Input: Thermo RAW, .dia, .wiff, mzML • Output: report.tsv, pg_matrix.tsv
💻 16 CPU Cores • 32-64 GB RAM
conda install -c bioconda dia-nn
Ultrafast Peptide Search
🚀 32GB+ RAM Java • Fragment-Index Algorithm

MSFragger / FragPipe

Docs ↗ By Alexey Nesvizhskii Lab (UMich)
(License: Academic Free License)

Ultrafast peptide identification search engine based on fragment-ion indexing. Enables unconstrained open mass searches to discover hundreds of unknown post-translational modifications (PTMs).

Formats: Input: mzML, RAW • Output: psm.tsv, pepXML, mzIdentML
💻 8-16 CPU Cores • 32-64 GB RAM
conda install -c bioconda msfragger
Targeted Mass Spectrometry
💻 < 8GB RAM C# • Windows .NET Client

Skyline

Docs ↗ By Michael MacCoss Lab (UW)
(License: Apache-2.0)

Premier open-source document-oriented application for building Selected Reaction Monitoring (SRM / MRM), PRM, and DIA quantitative methods and analyzing resulting chromatographic traces.

Formats: Input: RAW, mzML, WIFF • Output: Peak areas, Transition lists, Reports
💻 4-8 CPU Cores • 16 GB RAM
msiexec /i SkylineInstaller.msi
Modern Python Mass Spec
💻 16-32GB RAM Python • Numba JIT • Cloud Ready

AlphaPept

Docs ↗ By Matthias Mann Lab (Max Planck)
(License: Apache-2.0)

Open-source Python mass spectrometry framework developed for modern hardware, high-throughput pipelines, and transparent cloud deployment. Precompiled JIT matching with HDF5 tables.

Formats: Input: RAW, Bruker .d, mzML • Output: HDF5, Parquet, CSV
💻 8-16 CPU Cores • 16-32 GB RAM
pip install alphapept
LC-MS Algorithmic Suite
💻 16-32GB RAM C++ / pyOpenMS

OpenMS

Docs ↗ By Oliver Kohlbacher Lab (Tübingen)
(License: BSD-3-Clause)

Open-source C++ library and workflow tool for LC-MS mass spectrometry data management and quantification algorithms. Native integration into KNIME, Nextflow, and Python.

Formats: Input: mzML, mzXML, TraML • Output: consensusXML, featureXML
💻 8 CPU Cores • 16-32 GB RAM
conda install -c bioconda openms
LC-MS Feature Detection
💻 16-32GB RAM Java • High-throughput Multi-core

MZmine 3

Docs ↗ By Tomáš Pluskal & Robin Schmid (IOCB)
(License: GPL-2.0)

Modern framework for untargeted LC-MS and GC-MS data processing. Features automated peak picking (ADAP), retention time alignment, isotope pattern grouping, and GNPS spectral export.

Formats: Input: mzML, mzXML, netCDF • Output: MGF, CSV, GNPS feature tables
💻 8-16 CPU Cores • 16-32 GB RAM
conda install -c bioconda mzmine3
Chromatography Profiling
💻 16-32GB RAM R • Bioconductor • CentWave

XCMS

Docs ↗ By Colin Smith & Gary Siuzdak (Scripps)
(License: GPL-2.0)

Foundational mass spectrometry metabolomics framework. Performs centWave peak picking, non-linear retention time alignment (obiwarp), feature grouping, and CAMERA adduct annotation.

Formats: Input: mzML, NetCDF • Output: XCMSnExp Object, Feature Table
💻 8 CPU Cores • 16-32 GB RAM
R -e 'BiocManager::install("xcms")'
Untargeted Metabolomics & Lipids
💻 16-32GB RAM C# / .NET Core • Cross-Platform

MS-DIAL

Docs ↗ By Hiroshi Tsugawa & Oliver Fiehn (RIKEN / UC Davis)
(License: BSD-3-Clause)

Universal data processing software for untargeted metabolomics and lipidomics. Supports Data-Independent Acquisition (DIA/SWATH), DDA, and Ion Mobility MS with lipid blast libraries.

Formats: Input: AB Sciex, Waters, Thermo, mzML • Output: MSP, Alignment Tables
💻 8-16 CPU Cores • 16-32 GB RAM
dotnet run MSDIAL
Metabolomics Statistics & Pathways
💻 < 8GB RAM R • Statistical Pipelines

MetaboAnalystR

Docs ↗ By Jianguo Xia Lab (McGill)
(License: GPL-3.0)

Statistical and pathway analysis suite for metabolomics. Conducts normalization, PCA/PLS-DA, biomarker ROC curve modeling, MSEA pathway enrichment, and multi-omics integration.

Formats: Input: CSV Feature Matrix • Output: Pathway Maps, PLS-DA VIP scores
💻 4 CPU Cores • 8 GB RAM
R -e 'devtools::install_github("xia-lab/MetaboAnalystR")'
De Novo Molecule Identification
💻 16-32GB RAM Java / C++ • Tree Fragmentation

SIRIUS 5

Docs ↗ By Sebastian Böcker Lab (Jena)
(License: AGPL-3.0)

De novo identification of metabolites and molecular structures from tandem MS/MS. Integrates CSI:FingerID for database search, CANOPUS for chemical class prediction, and fragmentation trees.

Formats: Input: .mgf, .ms, mzML • Output: Chemical Structure SMILES, InChIKey
💻 8-16 CPU Cores • 16-32 GB RAM
conda install -c bioconda sirius-ms
Molecular Networking
💻 < 8GB RAM Cloud / REST API / Python

GNPS

Docs ↗ By Nuno Bandeira & Pieter Dorrestein (UCSD)
(License: CC-BY 4.0)

Global Natural Products Social Molecular Networking platform for community-wide sharing, clustering, and dereplication of untargeted tandem mass spectrometry (MS/MS) datasets.

Formats: Input: mzXML, mzML, MGF • Output: Molecular Network Graph (.graphml)
🌐 Web-Based Cloud Execution • Minimal Local RAM
pip install gnps-downloader
Recommended Workflow Progression

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