Redefining the high variable genes by optimized LOESS regression with positive ratio

By preserving key biological information through feature selection, GLP provides informative features to enhance the accuracy and effectiveness of downstream analyses.

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Publication Details

Journal
BMC Bioinformatics
Published
2025-04-15
DOI
https://doi.org/10.1186/s12859-025-06112-5
Citations
25
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
20.15

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article

Redefining the high variable genes by optimized LOESS regression with positive ratio

Zehua Jing, Xun William Xu, Yue Xie, Fang Qi et al.
25 citations
BMC Bioinformatics
Single-cell and spatial transcriptomics
20.15
article

Redefining the high variable genes by optimized LOESS regression with positive ratio

Zehua Jing, Xun William Xu, Yue Xie, Fang Qi, Haiqiao Pan
article en
25 citations

Abstract

By preserving key biological information through feature selection, GLP provides informative features to enhance the accuracy and effectiveness of downstream analyses.

BMC BioinformaticsVol. 26(1)
BGI Group (China) (CN), University of Chinese Academy of Sciences (CN), BGI Research (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 0%
Single-cell and spatial transcriptomics
20.15
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