List of software packages for multi-omics data analysis.
While many of the packages here are marketed for "omics" data (transcriptomics, proteomics, etc.), other more general terms for this type of data analysis are:
- multi-modal
- multi-table
- multi-way
The common thread among the methods listed here is that the same samples are measured across different assays. The data can be described as multiple matrices/tables with the same number of samples and varying number of features.
The repo is in the style of Sean Davis' awesome-single-cell repo for single-cell analysis methods.
For brevity, below lists only the first author of multi-omics methods.
- 2007 - SCCA - Parkhomenko - sparse CCA - paper 1, paper 2
- 2008 - PCCA - Waaijenborg - penalized CCA / CCA-EN - paper
- 2009 - PMA - Witten - Sparse Multi CCA - paper 1, paper 2
- 2009 - sPLS - Lê Cao - sparse PLS - paper
- 2009 - gesca - Hwang - RGSCA regularized generalized structured component analysis - paper
- 2010 - Regularized dual CCA - Soneson - paper
- 2011 - RGCCA - Tenenhaus - Regularized Generalized CCA and Sparse Generalized CCA - paper 1, paper 2
- 2011 - SNMNMF - Zhang - Sparse Network-regularized Multiple Non-negative Matrix Factorization - paper
- 2012 - STATIS/DiSTATIS - Abdi - structuring three-way statistical tables - paper
- 2012 - joint NMF - Zhang - extension of NMF to multiple datasets - paper
- 2012 - sMBPLS - Li - sparse MultiBlock Partial Least Squares - paper
- 2012 - Bayesian group factor analysis - Virtanen - paper
- 2012 - RIMBANET - Zhu - Reconstructing Integrative Molecular Bayesian Networks - paper
- 2013 - FactoMineR - Abdi - MFA: multiple factor analysis - paper
- 2013 - JIVE - Lock - joint & individual variance explained - paper
- 2013 - PANDA - Glass - Passing Attributes between Networks for Data Assimilation
- 2014 - omicade4 - Meng - MCIA: multiple co-interia analysis - paper
- 2014 - STATegRa - Gomez-Cabrero - DISCO, JIVE, & O2PLS (several papers)
- 2014 - Joint factor model - Ray - paper
- 2014 - GFAsparse - Khan - group factor analysis sparse paper 1, paper 2
- 2015 - Sparse CCA - Gao (3rd paper first author is Chen) - paper 1, paper 2, paper 3
- 2015 - CCAGFA - Klami - Bayesian Canonical Correlation Analysis and Group Factor Analysis - paper 1, paper 2
- 2016 - CMF - Klami - collective matrix factorization
- 2016 - moGSA - Meng - multi-omics gene set analysis - paper
- 2016 - iNMF - Yang - integrative NMF - paper
- 2016 - BASS - Zhao - Bayesian group factor analysis - paper
- 2017 - mixOmics
- 2017 - mixedCCA - Gaynanova - sparse CCA for data of mixed types - paper
- 2017 - SLIDE - Gaynanova - Structural Learning and Integrative Decomposition of Multi-View Data - paper
- 2017 - fCCAC - Madrigal - functional canonical correlation analysis to evaluate covariance - paper
- 2017 - TSKCCA - Yoshida - Sparse kernel canonical correlation analysis - paper
- 2017 - SMSMA - Kawaguchi - Supervised multiblock sparse multivariable analysis - paper
- 2018 - AJIVE - Feng - angle-based JIVE - paper
- 2018 - MOFA - Argelaguet - multi-omics factor analysis - paper, application
- 2018 - PCA+CCA - Brown - paper
- 2018 - maui - Ronen - multi-omics autoencoder integration - paper
- 2018 - JACA - Zhang - Joint Association and Classification Analysis - paper
- 2018 - iPCA - Tang - Integrated Principal Components Analysis - paper
- 2018 - pCIA - Min - penalized COI - paper
- 2018 - sSCCA - Safo - structured sparse CCA - paper
- 1994 - COI - Doledec - Co‐inertia analysis - paper
- 2007 - ade4 - Dray - Implementing the Duality Diagram for Ecologists - paper
- 1987 - Wold - Multi‐way principal components‐and PLS‐analysis - paper
- 1996 - Wold - Hierarchical multiblock PLS - paper
- 2003 - Trygg - O2‐PLS, a two‐block (X–Y) latent variable regression (LVR) - paper
- 2011 - Hanafi - Connections between multiple COI and consensus PCA - paper
- 2015 - THEME - Verron - THEmatic Model Exploration - paper
- 2013 - Schouteden - DISCO SCA - distinctive and common components with simultaneous-component analysis- paper 1, paper 2
Note: I think that prediction of genomic tracks, e.g. ChIP-seq, from other genomic tracks is a large area of research that may deserve a separate repository. Below are methods for clustering / classification of samples into sub-types or prediction of outcomes.
- 2009 - iCluster - Shen - paper
- 2013 - iClusterPlus - Mo - paper
- 2013 - BCC - Lock - Bayesian consensus clustering - paper
- 2013 - iBAG - Wang - Integrative Bayesian Analysis of Genomics - paper
- 2014 - SNF - Wang - paper
- 2019 - IBOOST - Wong - paper
- 2018 - cardelino - gene expression states to clones (SNVs from scRNA-seq + bulk exome data)
- 2018 - clonealign - gene expression states to clones (scRNA-seq + scDNA-seq (CNV)) - paper
- 2014 - Kohl - A practical data processing workflow for multi-OMICS projects
- 2016 - Josse - Measuring multivariate association and beyond
- 2016 - Ebrahim - Multi-omic data integration enables discovery of hidden biological regularities
- 2016 - Meng - Dimension reduction techniques for the integrative analysis of multi-omics data
- 2017 - Huang - More Is Better: Recent Progress in Multi-Omics Data Integration Methods
- 2017 - Hasin - Multi-omics approaches to disease
- 2017 - Allen - Statistical data integration: Challenges and opportunities
- 2018 - Rappoport - Multi-omic and multi-view clustering algorithms: review and cancer benchmark
- 2018 - Bougeard - Current multiblock methods: Competition or complementarity? A comparative study in a unified framework
- 2019 - McCabe - Consistency and overfitting of multi-omics methods on experimental data - code
- 2007 - Fagan - A multivariate analysis approach to the integration of proteomic and gene expression data
- 2011 - De la Cruz - The duality diagram in data analysis: Examples of modern applications - R notebook
- 2014 - Tomescu - Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data
- 2014 - Costello (NCI/DREAM) - A community effort to assess and improve drug sensitivity prediction algorithms
- 2016 - Wan - TCGA2STAT: simple TCGA data access for integrated statistical analysis in R - R notebook
- 2017 - Butler - Integrating single-cell transcriptomic data across different conditions, technologies, and species.
- 2018 - Skelly - Reference trait analysis reveals correlations between gene expression and quantitative traits in disjoint samples - R notebook
- 2018 - Stuart - Comprehensive integration of single cell data
- 2017 - MultiAssayExperiment - Software for the integration of multi-omics experiments in Bioconductor - paper.