The effect of data transformation on low-dimensional integration of single-cell RNA-seq by Youngjun Park, Anne-Christin Hauschild

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Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters by Sergii Domanskyi, Anthony Szedlak, Nathaniel T Hawkins, Jiayin Wang, Giovanni Paternostro, Carlo Piermarocchi

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scFTAT: a novel cell annotation method integrating FFT and transformer by Binhua Tang, Yiyao Chen

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SCSit: A high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq by Mei-Wei Luan, Jia-Lun Lin, Ye-Fan Wang, Yu-Xiao Liu, Chuan-Le Xiao, Rongling Wu, Shang-Qian Xie

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Editorial: Multiomics and multiparametric analyses to characterize myeloid cell subsets by Thien-Phong Vu Manh, Marc Dalod, Diana Dudziak, Diana Dudziak, Diana Dudziak, Diana Dudziak, Diana Dudziak

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A computational method to aid the design and analysis of single cell RNA-seq experiments for cell type identification by Douglas Abrams, Parveen Kumar, R. Krishna Murthy Karuturi, Joshy George

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LIDER: cell embedding based deep neural network classifier for supervised cell type identification by Yachen Tang, Xuefeng Li, Mingguang Shi

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CellSim: a novel software to calculate cell similarity and identify their co-regulation networks by Leijie Li, Dongxue Che, Xiaodan Wang, Peng Zhang, Siddiq Ur Rahman, Jianbang Zhao, Jiantao Yu, Shiheng Tao, Hui Lu, Mingzhi Liao

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TransCluster: A Cell-Type Identification Method for single-cell RNA-Seq data using deep learning based on transformer by Tao Song, Tao Song, Huanhuan Dai, Shuang Wang, Gan Wang, Xudong Zhang, Ying Zhang, Linfang Jiao

Subjects: “…cell-type identification…”
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scClassify: sample size estimation and multiscale classification of cells using single and multiple reference by Yingxin Lin, Yue Cao, Hani Jieun Kim, Agus Salim, Terence P Speed, David M Lin, Pengyi Yang, Jean Yee Hwa Yang

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SigPrimedNet: A Signaling-Informed Neural Network for scRNA-seq Annotation of Known and Unknown Cell Types by Pelin Gundogdu, Inmaculada Alamo, Isabel A. Nepomuceno-Chamorro, Joaquin Dopazo, Carlos Loucera

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GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues by Tianjiao Zhang, Ziheng Zhang, Liangyu Li, Jixiang Ren, Zhenao Wu, Bo Gao, Guohua Wang

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Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis by Thomas A. Geddes, Taiyun Kim, Lihao Nan, James G. Burchfield, Jean Y. H. Yang, Dacheng Tao, Pengyi Yang

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DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection by Fabian Hausmann, Can Ergen, Robin Khatri, Mohamed Marouf, Sonja Hänzelmann, Nicola Gagliani, Samuel Huber, Pierre Machart, Stefan Bonn

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Dysregulation of the Immune Microenvironment Contributes to Malignant Progression and Has Prognostic Value in Bladder Cancer by Zongtai Zheng, Shiyu Mao, Wentao Zhang, Ji Liu, Cheng Li, Ruiliang Wang, Xudong Yao

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Single Cell Transcriptome Data Analysis Defines the Heterogeneity of Peripheral Nerve Cells in Homeostasis and Regeneration by Bing Chen, Matthew C. Banton, Lolita Singh, David B. Parkinson, Xin-peng Dun, Xin-peng Dun

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Non-negative low-rank representation based on dictionary learning for single-cell RNA-sequencing data analysis by Juan Wang, Nana Zhang, Shasha Yuan, Junliang Shang, Lingyun Dai, Feng Li, Jinxing Liu

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MulCNN: An efficient and accurate deep learning method based on gene embedding for cell type identification in single-cell RNA-seq data by Linfang Jiao, Yongqi Ren, Lulu Wang, Changnan Gao, Shuang Wang, Tao Song, Tao Song

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MarkerCount: A stable, count-based cell type identifier for single-cell RNA-seq experiments by HanByeol Kim, Joongho Lee, Keunsoo Kang, Seokhyun Yoon

Subjects: “…Cell type identification…”
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Analysis and Visualization of Spatial Transcriptomic Data by Boxiang Liu, Yanjun Li, Liang Zhang

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