cran: SAVER | Projects | Ecosyste.ms: Papers

10.15252/msb.20188746

Current best practices in single‐cell RNA‐seq analysis: a tutorial
Cited by: 1,173
Author(s): Malte D. Luecken, Fabian J. Theis
Software Mentions: 20
Published: over 5 years ago

Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq
Cited by: 2
Author(s): Brandon Lieberman, Meena Kusi, Chia-Nung Hung, Chih-Wei Chou, Ning He, Yen‐Yi Ho, Josephine A. Taverna, Tim Hui-Ming Huang, Chun-Liang Chen
Software Mentions: 18
Published: almost 5 years ago

10.1186/s13059-020-02132-x

A systematic evaluation of single-cell RNA-sequencing imputation methods
Cited by: 156
Author(s): Wenpin Hou, Zhicheng Ji, Hongkai Ji, Stephanie Hicks
Software Mentions: 15
Published: about 4 years ago

10.1186/s13059-017-1305-0

Splatter: simulation of single-cell RNA sequencing data
Cited by: 575
Author(s): Luke Zappia, Belinda Phipson, Alicia Oshlack
Software Mentions: 13
Published: about 7 years ago

10.3389/fgene.2019.00317

Single-Cell RNA-Seq Technologies and Related Computational Data Analysis
Cited by: 549
Author(s): Geng Chen, Baitang Ning, Tieliu Shi
Software Mentions: 13
Published: over 5 years ago

10.3389/fgene.2021.655536

Machine Intelligence in Single-Cell Data Analysis: Advances and New Challenges
Cited by: 30
Author(s): Jiajia Li, Zusen Fan, Weiling Zhao, Xiaobo Zhou
Software Mentions: 12
Published: over 3 years ago

10.1186/s13059-021-02480-2

Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference construction
Cited by: 16
Author(s): Wenjing Ma, Kenong Su, Hao Wu
Software Mentions: 12
Published: about 3 years ago

10.3390/genes11050532

Sparsity-Penalized Stacked Denoising Autoencoders for Imputing Single-Cell RNA-seq Data
Cited by: 9
Author(s): Weilai Chi, Minghua Deng
Software Mentions: 9
Published: over 4 years ago

10.1371/journal.pcbi.1009029

G2S3: A gene graph-based imputation method for single-cell RNA sequencing data
Cited by: 7
Author(s): Weimiao Wu, Yunqing Liu, Qile Dai, Xiting Yan, Zuoheng Wang
Software Mentions: 9
Published: over 3 years ago

10.1186/s13059-020-02096-y

Demystifying “drop-outs” in single-cell UMI data
Cited by: 66
Author(s): Tae Hyun Kim, Xiang Zhou, Mengjie Chen
Software Mentions: 9
Published: over 4 years ago

10.1093/jmcb/mjaa052

Imputing single-cell RNA-seq data by considering cell heterogeneity and prior expression of dropouts
Cited by: 18
Author(s): Lihua Zhang, Shihua Zhang
Software Mentions: 9
Published: about 4 years ago

10.1186/s12864-019-5747-5

scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data
Cited by: 10
Author(s): Michael Fraser, Guoli Ji, Pengchao Ye, Yuqi Long, Xuesong Xiao, Shuchao Li, Yangfeng Su, Xiaohui Wu
Software Mentions: 8
Published: over 5 years ago

10.7554/eLife.65654

Quantitative control of noise in mammalian gene expression by dynamic histone regulation
Cited by: 2
Author(s): Tan D, Rui Chen, Yuejian Mo, Shu Gu, Jiao Ma, Wei Xu, Xibin Lu, Hongtao He, Fan Jiang, Weimin Fan, Yili Wang, Xi Chen, Wei Huang
Software Mentions: 8
Published: about 3 years ago

10.1186/s13059-019-1806-0

scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data
Cited by: 15
Author(s): Ruoxin Li, Gerald Quon
Software Mentions: 6
Published: about 5 years ago

10.1186/s13059-021-02400-4

mbImpute: an accurate and robust imputation method for microbiome data
Cited by: 23
Author(s): Ruochen Jiang, Wei Vivian Li, Jingyi Jessica Li
Software Mentions: 6
Published: over 3 years ago

10.1371/journal.pcbi.1009118

SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data
Cited by: 6
Author(s): Jing Qi, Yang Zhou, Zhao Zhang, Shuilin Jin
Software Mentions: 6
Published: over 3 years ago

10.1371/journal.pcbi.1008569

Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data
Cited by: 16
Author(s): Andreas Tjärnberg, Omar Mahmood, Christopher Jackson, Giuseppe-Antonio Saldi, Kyunghyun Cho, Lionel Christiaen, Richard Bonneau
Software Mentions: 6
Published: almost 4 years ago

10.1093/bioinformatics/btz726

bayNorm: Bayesian gene expression recovery, imputation and normalization for single-cell RNA-sequencing data
Cited by: 59
Author(s): Wenhao Tang, François Bertaux, Philipp Thomas, Claire Stefanelli, Malika Saint, Samuel Marguerat, Vahid Shahrezaei
Software Mentions: 6
Published: about 5 years ago

10.1186/s13059-019-1837-6

DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data
Cited by: 162
Author(s): Cédric Arisdakessian, Olivier Poirion, Breck Yunits, Xun Zhu, Lana X. Garmire
Software Mentions: 6
Published: about 5 years ago

10.1186/s13045-020-01005-x

RNA sequencing: new technologies and applications in cancer research
Cited by: 187
Author(s): Mingye Hong, Shuangping Tao, Ling Zhang, Li-Ting Diao, Xuanmei Huang, Shaohui Huang, Shu‐Juan Xie, Zhilong Xiao, Hua Zhang
Software Mentions: 5
Published: almost 4 years ago

10.1038/s41421-020-00236-z

Single-cell profiling of the human decidual immune microenvironment in patients with recurrent pregnancy loss
Cited by: 74
Author(s): Chuang Guo, Pengfei Cai, Lina Jin, Qing Sha, Qiaoni Yu, Wen Zhang, Chen Jiang, Qian Liu, Dandan Zong, Kun Li, Jingwen Fang, Fangting Lu, Yanshi Wang, Daojing Li, Jun Lin, Lü Li, Zhutian Zeng, Xianhong Tong, Haiming Wei, Kun Qu
Software Mentions: 5
Published: almost 4 years ago

10.1371/journal.pcbi.1007794

Scedar: A scalable Python package for single-cell RNA-seq exploratory data analysis
Cited by: 10
Author(s): Yuanchao Zhang, Man S. Kim, Erin R. Reichenberger, Benjamin Stear, Deanne Taylor
Software Mentions: 5
Published: over 4 years ago

10.1038/s12276-020-00499-2

Single-cell sequencing techniques from individual to multiomics analyses
Cited by: 116
Author(s): Yukie Kashima, Yoshitaka Sakamoto, Keiya Kaneko, Masahide Seki, Yutaka Suzuki, Ayako Suzuki
Software Mentions: 4
Published: about 4 years ago

10.1534/g3.120.401160

Evaluation of STAR and Kallisto on Single Cell RNA-Seq Data Alignment
Cited by: 31
Author(s): Yuheng Du, Qizhao Huang, Cédric Arisdakessian, Lana X. Garmire
Software Mentions: 4
Published: over 4 years ago

10.3390/genes11040377

Network-Based Single-Cell RNA-Seq Data Imputation Enhances Cell Type Identification
Cited by: 15
Author(s): Maryam Zand, Jianhua Ruan
Software Mentions: 4
Published: over 4 years ago

10.1186/s13059-018-1575-1

VIPER: variability-preserving imputation for accurate gene expression recovery in single-cell RNA sequencing studies
Cited by: 92
Author(s): Mengjie Chen, Xiang Zhou
Software Mentions: 4
Published: almost 6 years ago

10.3389/fmolb.2020.00209

Pinpointing Cell Identity in Time and Space
Cited by: 15
Author(s): Anca F. Savulescu, Caron Jacobs, Yutaka Negishi, L. Davignon, Musa M. Mhlanga
Software Mentions: 3
Published: about 4 years ago

10.12688/f1000research.16613.2

False signals induced by single-cell imputation
Cited by: 99
Author(s): Tallulah Andrews, Martin Hemberg
Software Mentions: 3
Published: over 5 years ago

10.1186/s12859-020-03878-8

SCC: an accurate imputation method for scRNA-seq dropouts based on a mixture model
Cited by: 11
Author(s): Yan Zheng, Yuanke Zhong, Jialu Hu, Xuequn Shang
Software Mentions: 3
Published: almost 4 years ago

10.1186/s12859-020-03547-w

A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data
Cited by: 2
Author(s): Qi Yang, Yang Guo, Huixin Jiao, Xuequn Shang
Software Mentions: 2
Published: over 4 years ago

10.1186/s12859-021-04022-w

PIKE-R2P: Protein–protein interaction network-based knowledge embedding with graph neural network for single-cell RNA to protein prediction
Cited by: 7
Author(s): Xinnan Dai, Fan Xu, Shike Wang, Piyushkumar A. Mundra, Jie Zheng
Software Mentions: 2
Published: over 3 years ago

10.1016/j.csbj.2020.10.016

Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives
Cited by: 26
Author(s): Geyang Luo, Qian Gao, Shuye Zhang, Bo Yan
Software Mentions: 2
Published: almost 5 years ago

10.12688/f1000research.24163.2

Spatial mapping of single cells in the Drosophila embryo from transcriptomic data based on topological consistency
Cited by: 0
Author(s): Maryam Zand, Jianhua Ruan
Software Mentions: 2
Published: over 3 years ago

10.3389/fgene.2020.511286

Patterns, Profiles, and Parsimony: Dissecting Transcriptional Signatures From Minimal Single-Cell RNA-Seq Output With SALSA
Cited by: 0
Author(s): Oswaldo A. Lozoya, Kathryn S. McClelland, Brian N. Papas, Jianliang Li, Hisayuki Yao
Software Mentions: 2
Published: about 4 years ago

10.1186/s13059-019-1681-8

SCRABBLE: single-cell RNA-seq imputation constrained by bulk RNA-seq data
Cited by: 83
Author(s): Tao Peng, Qin Zhu, Pengbin Yin, Kai Tan
Software Mentions: 2
Published: over 5 years ago

10.1186/s13063-021-05373-8

SAVER: sodium valproate for the epigenetic reprogramming of high-risk oral epithelial dysplasia—a phase II randomised control trial study protocol
Cited by: 4
Author(s): Caroline McCarthy, Joseph J. Sacco, Stefano Fedele, Michael Ho, Stephen Porter, Triantafillos Liloglou, Bill Greenhalf, Max Robinson, Bridget Young, Silvia Cicconi, Seema Chauhan, Binyam Tesfaye, Richard A. Jackson, Frances C Sherratt, Richard Shaw
Software Mentions: 1
Published: over 3 years ago

10.1038/s41598-019-56911-z

Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data
Cited by: 24
Author(s): Bettina Mieth, James R.F. Hockley, Nico Görnitz, Marina M.-C. Vidovic, Klaus Robert Müller, Alex Gutteridge, Daniel Ziemek
Software Mentions: 1
Published: almost 5 years ago

10.3389/fphys.2017.00277

Efficient Fetal-Maternal ECG Signal Separation from Two Channel Maternal Abdominal ECG via Diffusion-Based Channel Selection
Cited by: 37
Author(s): Ruilin Li, Martin G. Frasch, Hau‐Tieng Wu
Software Mentions: 1
Published: over 7 years ago

10.3389/fonc.2021.676948

Current Insights and Advancements in Head and Neck Cancer: Emerging Biomarkers and Therapeutics with Cues from Single Cell and 3D Model Omics Profiling
Cited by: 3
Author(s): Yashika Jawa, Pooja Yadav, Shruti Gupta, Sivapar V. Mathan, Jyoti Pandey, Ajay K. Saxena, Suneel Kateriya, Ashu Bhan Tiku, Neelima Mondal, Jaydeep Bhattacharya, Shandar Ahmad, Rupesh Chaturvedi, Rakesh K. Tyagi, Vibha Tandon, Rana P. Singh
Software Mentions: 1
Published: about 3 years ago

10.1186/s12864-020-07007-w

I-Impute: a self-consistent method to impute single cell RNA sequencing data
Cited by: 4
Author(s): Xikang Feng, Lingxi Chen, Zishuai Wang, Shuai Cheng Li
Software Mentions: 1
Published: about 4 years ago

Projects: cran: SAVER

Papers Mentioning SAVER 40