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Effective Detection of Variation in Single Cell Transcriptome using MATQ-seq

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NIAID Data Ecosystem2026-03-10 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP071245
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We report here a new single-cell RNA-seq assay, Multiple Annealing and dC-Tailing based Quantitative single-cell RNA-seq (MATQ-seq), which provides the accuracy and sensitivity that enable the detection of transcriptional variations existing in single cells of the same type. We performed a systematic characterization of the technical noise using pool-and-split averaged single-cell samples and showed that the biological variations in single cells were observed with statistical significance. Overall design: 10 HEK293T single cells and 10 HEK293T pool-and-split averaged single cell samples were sequenced with MATQ-seq. We also sequenced 6 MCF10A single cells and 6MCF10A pool-and-split averaged single cell samples. To characterize the capture efficiency, we also sequenced 6 averaged one-fifth MCF10A single-cell samples with ERCC spike-in. Additional 38 HEK293T single cells (HEK293T_clone1_SC*) and 10 HEK293T pool-and-split averaged single cell samples (HEK293T_clone1_SC_average*) were sequenced with MATQ-seq.
创建时间:
2017-09-17
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