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• The detailed information including the accession codes and publication citations for all datasets can be seen in Supplementary Information.
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• For read count data generated by full-length sequencing technique, we calculated Transcript Per Million (TPM)20, added pseudo value one to handle 0 values and performed log-normalization.

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Our results demonstrated that SciBet out-performed scmap and Seurat v3 by orders of magnitude, with a classification speed of ~100,000 cells per second (Fig. 2e). We tested the performance of SciBet on two datasets, with Scibet both even and uneven cell type distributions. In addition, for a human pancreatic dataset11 with imbalanced proportions of cell types, SciBet could still provide the most discriminating power. By contrast, both Seurat v3 and scmap had lower accuracies in classifying delta cells, which accounted for only 3.8% of cells (Fig. 2g). Scibet Casino is a modern online casino of 2024, owned by L.C.S Limited and licensed by the Malta Gaming Authority (MGA). Players can take advantage of a generous welcome bonus of up to €1,200, including a 125% bonus up to €400 on the first deposit.

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For example, Tabula Muris1 comprises more than 100,000 cells from 20 organs and tissues. MOCA2, mouse organogenesis cell atlas, characterizes the single-cell map of mouse whole embryos with a newly developed technique sci-seq-3, which can measure millions of cells at a time. In addition, the Human Cell Project3 (HCA) aims to characterize the single-cell map of all human cells, and its order of magnitude will reach billions. Facing such explosive data growth, one major challenge is the reliable and rapid cell type identification given a newly sequenced cell. Such practice can become inefficient if aforementioned huge datasets are used as reference.
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Our results showed that E-test consistently achieved the highest classification accuracy. In principle, E-test only needs linear operations and the computational time increases linearly with the numbers of cells and genes, in contrast to the quadratic increase for other gene selection methods. The time consumption and cell number relationship (Fig. 2b) confirmed this point, demonstrating the scalability of E-test for large datasets.
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