Multi-omics data integration
DLMM: Integrative analysis of DNA copy number and mRNA expression data.
PECA: Protein expression control analysis for gene expression regulation.
Latest development at https://github.com/PECAplus
Old version of PECA at http://sourceforge.net/projects/pecanalysis/
iOmicsPASS: Integrative -omics approach for predictive analysis of cancer subtypes with sub-network signatures.
iOmicsPASS+: Integrative analysis of multi-omics data with data-driven network identification.
PARPROX: Computationally scalable regression modeling with flexible group-wise variable selection
Computational metabolomics and lipidomics
MetaboKIT: comprehensive toolkit for data processing of DDA and DIA mass spectrometry analysis for metabolomics (upgrade of MetaboDIA)
MRMkit: fast and accurate data extraction and normalization for quantitative metabolomics with targeted mass spectrometry
DIMSkit: a new data extraction workflow for direct infusion mass spectrometry
GitHub page:
Metaboscan:
GitHub page:
LipidEF:
GitHub page:
midar:
GitHub page:
Computational proteomics
LuciPHOr: Probabilistic algorithm to control false localization rates of generic PTM from mass spectrometry-based proteomics data.
MSblender: Integration of database search results in peptide identification (led by TJ Kwon, UNIST, Korea) .
PTMscape: an open source tool to predict generic post-translational modifications and map hotspots of modification crosstalk.
PRMkit: fast and accurate data extraction and normalization of parallel reaction monitoring (PRM) data
GitHub page: to be released
Differential expression analysis for proteomics data
EBprot: Statistical analysis of labeling-based proteomics data.
mapDIA: Data processing and statistical analysis of data independent acquisition MS data.
QSPEC/QPROT: Statistical protein differential expression analysis for spectral count data.
KSA-2D: 1D and 2D empirical Bayes analysis of differential phosphoproteome analysis
https://github.com/ginnyintifa/KSA2D
Analysis of interaction proteomics data
nestedCluster: Biclustering algorithm for affinity purification – quantitative proteomics data.
SAINT suite: Significance analysis of affinity purification-MS data.
Data visualization
SLIDE: Systems-level Interactive Data Exploration.
Multi-SLIDE: Visualization of single or multi-omics data with user-driven query
GitHub page: https://github.com/soumitag/multiSLIDE
Genomic data analysis
ChIPmeta: Integration of multiple ChIP experiments.
scHMM: Sparsely correlated HMM algorithm for ChIP data analysis.
GPD (Gene-to-Protein-to-Disease framework): a protein-centric data summary approach for association analysis from whole exome sequencing data