We note that MOMA is a joint integration and classification method and as such does not require further training a classification method such as SVM, after training MOMA. However, per reviewer comment, we add a comparison where we use the important features chosen by MOMA to train and test ...
Namely, bulk RNA-seq profiles allowed us to produce upper bounds on the accuracy of deconvolution methods that rely on the corresponding scnRNA-seq assays, and the integration of concurrent bulk RNA-seq in the deconvolution process with SQUID improved deconvolution accuracy for all datasets. In ...
To remove batch effects across different samples, identification of the anchor correspondences of the merged data was performed with the “FindIntegrationAnchors” function, and the first 50 dimensions were used for calculation. Subsequently, these computed anchors were used for integration of the ...
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Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, multi-omics and spatiotemporal omics integration, bioinformatics analysis, etc. By presenting a unique combination of comprehensive disease coverage, in-depth exploration of ...
Reduced functional integration and segregation of distributed neural systems underlying social and emotional information processing in autism spectrum disorders. Cereb Cortex. 2012;22(5):1025–37. Article Google Scholar Shih P, Keehn B, Oram JK, Leyden KM, Keown CL, Muller RA. Functional ...
Comprehensive integration of single-cell data. Cell. 2019;177:1888-1902.e1821. Article PubMed PubMed Central CAS Google Scholar Efremova M, Vento-Tormo M, Teichmann SA, Vento-Tormo R. Cell PhoneDB: inferring cell-cell communication from combined expression of multi-subunit ligand-receptor ...
Then, we calculated feature importance of all input features based on these models and filtered out features whose contribution to the models is less than1{e}^{-3}. The number of features was reduced to 60 and below. We will describe these features in detail (Additional file1: Table S4-...
Behaviour change in humans is frequently difficult to achieve and the impact of phenotypic or genetic risk score information is no exception [71]. While more follow-up will ultimately determine whether changes in behaviour are persistent and corresponding disease events reduced, recent large-scale stud...
Multi-omics integration analysis and phenotypic omics contribution assessment Connections between phenotypes, microbial species, functions, metabolites, and/or host gene expression were determined by performing an association study (using Spearman correlation coefficient). Firstly, Spearman’s correlations among...