We developed a pseudotargeted metabolomics method, ion-pairs used for MRM are extracted from untargeted mass spectrometry data by using mixtures of samples to be analyzed, semi-quantitative information of each sample is obtained by the MRM without identification of the metabolites.
We describe SCCAF a computational approach to identify putative cell clusters from single-cell RNA-seq data. SCCAF automatically identifies the “ground truth” cell assignments with high accuracy in various benchmark datasets and captures the discriminative feature genes of the cell types.
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