OmicVerse: A single pipeline for exploring the entire transcriptome universe
Zehua ZengiD, Yuqing Ma, Lei HuiD, Bowen TaniD, Peng LiuiD, Yixuan WangiD, Cencan XingiD, Yuanyan XiongiD, Hongwu DuiD
Abstract
Single-cell sequencing is frequently marred by "interruptions" due to limitations in sequencing throughput, yet bulk RNA-seq may harbor these ostensibly "interrupted" cells. In response, we introduce the single cell trajectory blending from Bulk RNA-seq (BulkTrajBlend) algorithm, a component of the OmicVerse suite that leverages a Beta-Variational AutoEncoder for data deconvolution and graph neural networks for the discovery of overlapping community. This approach proficiently interpolates and restores the continuity of "interrupted" cells within single-cell RNA sequencing dataset. Furthermore, OmicVerse provides an extensive toolkit for bulk and single cell RNA-seq analysis, offering uniform access to diverse methodologies, streamlining computational processes, fostering exquisite data visualization, and facilitating the extraction of novel biological insights to advance scientific research.
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