scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis
Fig 2
Visualization and performance evaluation of dimension reduction task of scMoMtF compared with other comparison algorithms.
A-C Visualization of dimension reduction data generated by scMoMtF, Matilda, scMDC, and MultiVI on SNARE-seq, PBMC, and SHARE-seq datasets. D Visualization of dimension reduction data generated by scMoMtF, Matilda, scMDC and totalVI on the CITE-seq dataset. E-G Evaluate the clustering performance of dimension reduction data generated by scMoMtF, Matilda, scMDC, and MultiVI on SNARE-seq, PBMC, and SHARE-seq datasets using AMI, NMI, and ARI. H The clustering performance of dimension reduction data generated by scMoMtF, Matilda, scMDC and totalVI on CITE-seq dataset.