Article
Biochemistry & Molecular Biology
Mengting Huang, Yixuan Yang, Xingzhao Wen, Weiqiang Xu, Na Lu, Xiao Sun, Jing Tu, Zuhong Lu
Summary: Although single cell RNA sequencing technologies are well developed, acquiring large-scale single cell expression data can still be costly. The study proposes a method of compressing expression profiles from the sample dimension by assigning each cell into multiple pools and demonstrates that expression profiles can be inferred from pool expression data with a overlapping pooling design and compressed sensing strategy. This approach, when combined with plate-based scRNA-seq measurement, maintains superior gene detection sensitivity and individual identity while reducing library costs by half.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemical Research Methods
Siqi Chen, Xuhua Yan, Ruiqing Zheng, Min Li
Summary: Single-cell RNA sequencing technology (scRNA-seq) has the drawback of large sparsity, which leads to dropout events and affects downstream analyses. To address this, we propose Bubble, which identifies and imputes dropout events using expression rate and coefficient of variation, and leverages bulk RNA-seq data as a constraint. Bubble improves recovery of missing values, correlations, and reduces false positive signals. It enhances differential expression analysis, clustering, visualization, and aids cellular trajectory inference. Moreover, Bubble provides fast and scalable imputation with minimal memory usage.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Siqi Chen, Xuhua Yan, Ruiqing Zheng, Min Li
Summary: Bubble is a method for identifying and imputing 'dropout events' in scRNA-seq data, using gene expression rate and coefficient of variation to identify zeros, and then utilizing an autoencoder for imputation. Bubble enhances the recovery of missing values, reduces the introduction of false positive signals, and improves the identification of differentially expressed genes and cell clustering and visualization.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Alexander Gerniers, Orian Bricard, Pierre Dupont
Summary: This study presents a data mining method, MicroCellClust, to identify small subpopulations of cells with highly specific expression profiles. Through controlled experiments, it is shown to achieve a high F-1 score in identifying rare subpopulations of human T cells, specific CD4 T cells from breast cancer samples, and a subpopulation related to a specific stage in the cell cycle. Additionally, three rare subpopulations in mouse embryonic stem cells are successfully identified with MicroCellClust, demonstrating its effectiveness in identifying small subsets of cells with highly specific expression profiles.
Article
Multidisciplinary Sciences
Kai Battenberg, S. Thomas Kelly, Radu Abu Ras, Nicola A. Hetherington, Makoto Hayashi, Aki Minoda
Summary: Single-cell RNA-sequencing analysis has gained popularity, and UniverSC is a universal tool for processing single-cell RNA-seq data on any platform. It provides a command-line tool, docker image, and containerized graphical application for consistent and comprehensive integration, comparison, and evaluation of data from various platforms. Additionally, a cross-platform application with a graphical user interface is available to address the bottleneck of data processing for researchers without bioinformatics expertise.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Malte D. Luecken, M. Buettner, K. Chaichoompu, A. Danese, M. Interlandi, M. F. Mueller, D. C. Strobl, L. Zappia, M. Dugas, M. Colome-Tatche, Fabian J. Theis
Summary: This study benchmarked 68 method and preprocessing combinations on 85 batches of gene expression data, highlighting the importance of highly variable gene selection in improving method performance. When dealing with complex integration tasks, scANVI, Scanorama, scVI, and scGen consistently performed well, while the performance of single-cell ATAC-sequencing integration was strongly influenced by the choice of feature space.
Article
Biochemistry & Molecular Biology
Eric R. Reed, Stefano Monti
Summary: High-throughput genomics assays are standard in large-scale biomedical projects, and K2Taxonomer is a novel unsupervised recursive partitioning algorithm designed to identify robust subgroups in data. It is versatile for different data paradigms and has demonstrated its power in discovering known relationships and transcriptional programs associated with better prognosis in breast cancer research.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Eric R. Reed, Stefano Monti
Summary: With the standardization of high-throughput genomics assays in large-scale biomedical projects, the novel algorithm K2Taxonomer has been introduced to identify robust subgroups and discover transcriptional programs associated with better prognosis in breast cancer tissue. This algorithm is designed to accommodate different data paradigms and has demonstrated its power in analyzing various omics datasets.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Multidisciplinary Sciences
Lieke Michielsen, Marcel J. T. Reinders, Ahmed Mahfouz
Summary: scHPL is a hierarchical progressive learning method that can learn cellular hierarchies from multiple datasets while preserving the original annotations.
NATURE COMMUNICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Mengwei Li, Xiaomeng Zhang, Kok Siong Ang, Jingjing Ling, Raman Sethi, Nicole Yee Shin Lee, Florent Ginhoux, Jinmiao Chen
Summary: DISCO is an integrated database of single-cell omics data, offering an integrated cell atlas and harmonized metadata that users can utilize for comprehensive single-cell data analysis and exploration.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Genetics & Heredity
Juber Herrera-Uribe, Jayne E. Wiarda, Sathesh K. Sivasankaran, Lance Daharsh, Haibo Liu, Kristen A. Byrne, Timothy P. L. Smith, Joan K. Lunney, Crystal L. Loving, Christopher K. Tuggle
Summary: The study conducted transcriptome analysis of pig peripheral blood immune cells at both bulk and single-cell levels, identifying different cell types and their associated gene expression features. The research demonstrated significant correlations in gene expression between pig cells and human PBMC data, providing insights into the similarities between pig and human immune systems.
FRONTIERS IN GENETICS
(2021)
Article
Biochemical Research Methods
Yueqi Sheng, Boaz Barak, Mor Nitzan
Summary: Single-cell RNA-sequencing technologies have greatly enhanced our understanding of heterogeneous cell populations and underlying regulatory processes. However, the structural relations between cells are lost during cell dissociation, which is crucial for identifying associated biological processes. This study proposes an algorithm that iteratively identifies manifold-informative genes, improving the quality of tissue reconstruction.
Article
Biotechnology & Applied Microbiology
Simon Mages, Noa Moriel, Inbal Avraham-Davidi, Evan Murray, Jan Watter, Fei Chen, Orit Rozenblatt-Rosen, Johanna Klughammer, Aviv Regev, Mor Nitzan
Summary: Transferring annotations of single-cell-, spatial- and multi-omics data is challenging due to technical limitations and biological variations. We present TACCO, a computational framework for annotation transfer, which utilizes continuous mixtures of cells or molecules to annotate a wide variety of data. TACCO achieves high accuracy while reducing computational requirements and scales to larger datasets.
NATURE BIOTECHNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Yuansheng Zhang, Dong Zou, Tongtong Zhu, Tianyi Xu, Ming Chen, Guangyi Niu, Wenting Zong, Rong Pan, Wei Jing, Jian Sang, Chang Liu, Yujia Xiong, Yubin Sun, Shuang Zhai, Huanxin Chen, Wenming Zhao, Jingfa Xiao, Yiming Bao, Lili Hao, Zhang Zhang
Summary: GEN is an open-access data portal that integrates a vast amount of transcriptomic profiles, including bulk and single-cell RNA sequencing datasets, with abundant gene annotations and online data analysis services. The website also provides opportunities for integrative analysis at both transcriptional and post-transcriptional levels.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Multidisciplinary Sciences
Peijie Zhou, Shuxiong Wang, Tiejun Li, Qing Nie
Summary: MuTrans is a method based on multiscale reduction technique that can identify the underlying stochastic dynamics governing cell-fate transitions, construct cell-fate dynamical manifold, distinguish stable and transition cells, and quantify transition probabilities between cell states. The method is consistent with Langevin equation and transition rate theory, and has been shown to robustly unravel complex cell fate dynamics induced by transition cells in various systems. It bridges data-driven and model-based approaches for single-cell resolution analysis of cell-fate transitions.
NATURE COMMUNICATIONS
(2021)
Article
Oncology
Li Song, Zhangyi Ouyang, David Cohen, Yang Cao, Jennifer Altreuter, Gali Bai, Xihao Hu, Kenneth J. Livak, Heng Li, Ming Tang, Bo Li, X. Shirley Liu
Summary: This study utilized the TRUST4 algorithm to analyze thousands of RNA sequencing samples, revealing a strong correlation between CCL5 and MZB1 with T-cell and B-cell clonal expansion. The research also uncovered tyrosine as the preferred residue during B-cell receptor somatic hypermutation, as well as the association of IgG1+IgG3 antibodies with FcRn. Additionally, B-cell clonal expansion and IgG1+IgG3 antibodies were found to be correlated with better patient outcomes.
CANCER IMMUNOLOGY RESEARCH
(2022)
