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Status |
Public on Dec 31, 2016 |
Title |
Effective Detection of Variation in Single Cell Transcriptome using MATQ-seq |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
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.
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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.
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Contributor(s) |
Sheng K, Zong C |
Citation(s) |
28092691 |
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Submission date |
Mar 07, 2016 |
Last update date |
May 15, 2019 |
Contact name |
Kuanwei Sheng |
E-mail(s) |
sheng@bcm.edu
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Organization name |
Baylor College of Medicine
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Department |
Molecular and Human Genetics
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Lab |
Zong Lab
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Street address |
ONE BAYLOR PALAZA
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City |
HOUSTON |
State/province |
TX |
ZIP/Postal code |
77030 |
Country |
USA |
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Platforms (1) |
GPL18573 |
Illumina NextSeq 500 (Homo sapiens) |
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Samples (91)
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Relations |
BioProject |
PRJNA314523 |
SRA |
SRP071245 |