A rank-based marker selection method for high throughput scRNA-seq data

被引:0
|
作者
Alexander H. S. Vargo
Anna C. Gilbert
机构
[1] University of Michigan,Department of Mathematics
[2] Department of Mathematics,undefined
[3] Yale University,undefined
来源
关键词
Single cell RNA-seq; Marker selection; Machine learning; Data analysis; Algorithms; Benchmarking;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [31] langevitour: Smooth Interactive Touring of High Dimensions, Demonstrated with scRNA-Seq Data
    Harrison, Paul
    R JOURNAL, 2023, 15 (02): : 206 - 219
  • [32] TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq
    Shigeyuki Shichino
    Satoshi Ueha
    Shinichi Hashimoto
    Tatsuro Ogawa
    Hiroyasu Aoki
    Bin Wu
    Chang-Yu Chen
    Masahiro Kitabatake
    Noriko Ouji-Sageshima
    Noriyoshi Sawabata
    Takeshi Kawaguchi
    Toshitugu Okayama
    Eiji Sugihara
    Shigeto Hontsu
    Toshihiro Ito
    Yasunori Iwata
    Takashi Wada
    Kazuho Ikeo
    Taka-Aki Sato
    Kouji Matsushima
    Communications Biology, 5
  • [33] TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq
    Shichino, Shigeyuki
    Ueha, Satoshi
    Hashimoto, Shinichi
    Ogawa, Tatsuro
    Aoki, Hiroyasu
    Wu, Bin
    Chen, Chang-Yu
    Kitabatake, Masahiro
    Ouji-Sageshima, Noriko
    Sawabata, Noriyoshi
    Kawaguchi, Takeshi
    Okayama, Toshitugu
    Sugihara, Eiji
    Hontsu, Shigeto
    Ito, Toshihiro
    Iwata, Yasunori
    Wada, Takashi
    Ikeo, Kazuho
    Sato, Taka-Aki
    Matsushima, Kouji
    COMMUNICATIONS BIOLOGY, 2022, 5 (01)
  • [34] SCDRHA: A scRNA-Seq Data Dimensionality Reduction Algorithm Based on Hierarchical Autoencoder
    Zhao, Jianping
    Wang, Na
    Wang, Haiyun
    Zheng, Chunhou
    Su, Yansen
    FRONTIERS IN GENETICS, 2021, 12
  • [35] Rank-based variable selection with censored data
    Jinfeng Xu
    Chenlei Leng
    Zhiliang Ying
    Statistics and Computing, 2010, 20 : 165 - 176
  • [36] COTAN: scRNA-seq data analysis based on gene co-expression
    Galfre, Silvia Giulia
    Morandin, Francesco
    Pietrosanto, Marco
    Cremisi, Federico
    Helmer-Citterich, Manuela
    NAR GENOMICS AND BIOINFORMATICS, 2021, 3 (03)
  • [37] RFCell: A Gene Selection Approach for scRNA-seq Clustering Based on Permutation and Random Forest
    Zhao, Yuan
    Fang, Zhao-Yu
    Lin, Cui-Xiang
    Deng, Chao
    Xu, Yun-Pei
    Li, Hong-Dong
    FRONTIERS IN GENETICS, 2021, 12
  • [38] Rank-based variable selection with censored data
    Xu, Jinfeng
    Leng, Chenlei
    Ying, Zhiliang
    STATISTICS AND COMPUTING, 2010, 20 (02) : 165 - 176
  • [39] SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model
    Zheng, Yan
    Zhong, Yuanke
    Hu, Jialu
    Shang, Xuequn
    BMC BIOINFORMATICS, 2021, 22 (01)
  • [40] A novel batch-effect correction method for scRNA-seq data based on Adversarial Information Factorization
    Monnier, Lily
    Cournede, Paul-Henry
    PLOS COMPUTATIONAL BIOLOGY, 2024, 20 (02)