Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 17 times.
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National Institutes of Health
Grant: 1R35GM140888-01
Statistical methods for elucidating regulatory mechanisms and functional impacts of transcriptome variation at population and single-cell scales
National Institutes of Health
Grant: 5R01GM120507-04
Robust Identification and accurate quantification of RNA transcripts on a system wide scale
National Science Foundation
Grant: 2113754
Collaborative Research: Development of Classification Theory and Methods for Objective Asymmetry, Sample Size Limitation, Labeling Ambiguity, and Feature Importance
National Science Foundation
Grant: 1846216
CAREER: Advancing the Bioinformatic Infrastructure and Methodology for Single-cell RNA Sequencing
Fields of Study
Keywords
Sustainable Development Goals
Semi-synthetic Negative & Positive Control Enhancing the Reliability and Power in Single-cell and Spatial Omics Data Analysis
Semi-synthetic Negative & Positive Control Enhancing the Reliability and Power in Single-cell and Spatial Omics Data Analysis
Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses