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| Status |
Public on Aug 04, 2022 |
| Title |
Resolution of the curse of dimensionality in single-cell RNA-sequencing data analysis |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Single-cell RNA sequencing (scRNA-seq) can determine gene expression in numerous individual cells simultaneously, promoting progress in the biomedical sciences. However, scRNA-seq data are high-dimensional with substantial technical noise, including dropouts. During analysis of scRNA-seq data, such noise engenders a statistical problem known as the curse of dimensionality (COD). Based on high-dimensional statistics, we herein formulate a noise reduction method, RECODE (resolution of the curse of dimensionality), for high-dimensional data with random sampling noise. We show that RECODE consistently resolves COD in relevant scRNA-seq data with unique molecular identifiers. RECODE does not involve dimension reduction and recovers expression values for all genes, including lowly expressed genes, realizing precise delineation of cell-fate transitions and identification of rare cells with all gene information. Compared to representative imputation methods, RECODE employs different principles and exhibits superior overall performance in cell-clustering, expression-value recovery, and single-cell level analysis. The RECODE algorithm is parameter-free, data-driven, deterministic, and high-speed, and its applicability can be predicted based on the variance normalization performance. We propose RECODE as a powerful strategy for preprocessing noisy high-dimensional data.
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| Overall design |
Single cell transcriptome analysis of human primodial germ cell like cell (PGCLC) induction process using 10x chromium Single Cell Gene expression system.
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| Contributor(s) |
Imoto Y, Nakamura T, Escolar EG, Yoshiwaki M, Kojima Y, Yabuta Y, Katou Y, Yamamoto T, Hiraoka Y, Saitou M |
| Citation(s) |
35944930 |
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| Submission date |
May 25, 2021 |
| Last update date |
Nov 03, 2022 |
| Contact name |
Yukihiro Yabuta |
| E-mail(s) |
yabyab@anat2.med.kyoto-u.ac.jp
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| Organization name |
Kyoto University, Graduate school of medicine
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| Department |
Anatomy and Cell Biology
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| Street address |
Yoshida-Konoe-cho, Sakyo-ku
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| City |
Kyoto |
| State/province |
Kyoto |
| ZIP/Postal code |
606-8501 |
| Country |
Japan |
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| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (1) |
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| Relations |
| BioProject |
PRJNA732704 |
| SRA |
SRP321418 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE175525_RAW.tar |
143.2 Mb |
(http)(custom) |
TAR (of MTX, TSV) |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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