Cargando…

scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

BACKGROUND: Cell clustering is a prerequisite for identifying differentially expressed genes (DEGs) in single-cell RNA sequencing (scRNA-seq) data. Obtaining a perfect clustering result is of central importance for subsequent analyses, but not easy. Additionally, the increase in cell throughput due...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zhu, Jiadi, Yang, Youlong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210493/ https://www.ncbi.nlm.nih.gov/pubmed/37231345 http://dx.doi.org/10.1186/s12864-023-09374-6

Ejemplares similares

iSC.MEB: an R package for multi-sample spatial clustering analysis of spatial transcriptomics data
por: Zhang, Xiao, et al.
Publicado: (2023)

Fast and memory-efficient scRNA-seq k-means clustering with various distances
por: Baker, Daniel N., et al.
Publicado: (2021)

Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data
por: Teschendorff, Andrew E, et al.
Publicado: (2020)

SC3 - consensus clustering of single-cell RNA-Seq data
por: Kiselev, Vladimir Yu., et al.
Publicado: (2017)

Beam position mismatching and correction of LEB-MEB transfer line
por: Mao, N, et al.
Publicado: (1994)

scDSSC: Deep Sparse Subspace Clustering for scRNA-seq Data
por: Wang, HaiYun, et al.
Publicado: (2022)

Two Cassava Basic Leucine Zipper (bZIP) Transcription Factors (MebZIP3 and MebZIP5) Confer Disease Resistance against Cassava Bacterial Blight
por: Li, Xiaolin, et al.
Publicado: (2017)

scFseCluster: a feature selection-enhanced clustering for single-cell RNA-seq data
por: Wang, Zongqin, et al.
Publicado: (2023)

scShaper: an ensemble method for fast and accurate linear trajectory inference from single-cell RNA-seq data
por: Smolander, Johannes, et al.
Publicado: (2021)

Contrastive self-supervised clustering of scRNA-seq data
por: Ciortan, Madalina, et al.
Publicado: (2021)

Boosting scRNA-seq data clustering by cluster-aware feature weighting
por: Li, Rui-Yi, et al.
Publicado: (2021)

LRT: Integrative analysis of scRNA-seq and scTCR-seq data to investigate clonal differentiation heterogeneity
por: Xie, Juan, et al.
Publicado: (2023)

A clustering method for small scRNA-seq data based on subspace and weighted distance
por: Ning, Zilan, et al.
Publicado: (2023)

A scaling-free minimum enclosing ball method to detect differentially expressed genes for RNA-seq data
por: Zhou, Yan, et al.
Publicado: (2021)

scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data
por: Wang, Zile, et al.
Publicado: (2023)

Detection of cell markers from single cell RNA-seq with sc2marker
por: Li, Ronghui, et al.
Publicado: (2022)

Vacuolar Iron Transporter BnMEB2 Is Involved in Enhancing Iron Tolerance of Brassica napus
por: Zhu, Wei, et al.
Publicado: (2016)

An accurate and robust imputation method scImpute for single-cell RNA-seq data
por: Li, Wei Vivian, et al.
Publicado: (2018)

Supervised capacity preserving mapping: a clustering guided visualization method for scRNA-seq data
por: Zhai, Zhiqian, et al.
Publicado: (2022)

dropClust: efficient clustering of ultra-large scRNA-seq data
por: Sinha, Debajyoti, et al.
Publicado: (2018)

MLG: multilayer graph clustering for multi-condition scRNA-seq data
por: Lu, Shan, et al.
Publicado: (2021)

Detecting differential alternative splicing events in scRNA-seq with or without Unique Molecular Identifiers
por: Hu, Yu, et al.
Publicado: (2020)

Single-cell mapper (scMappR): using scRNA-seq to infer the cell-type specificities of differentially expressed genes
por: Sokolowski, Dustin J, et al.
Publicado: (2021)

scNCL: transferring labels from scRNA-seq to scATAC-seq data with neighborhood contrastive regularization
por: Yan, Xuhua, et al.
Publicado: (2023)

ScRNA-seq and ST-seq in liver research
por: He, Jia, et al.
Publicado: (2023)

scGCL: an imputation method for scRNA-seq data based on graph contrastive learning
por: Xiong, Zehao, et al.
Publicado: (2023)

Promoting Children's Mental, Emotional, and Behavioral (MEB) Health in All Public Systems, Post-COVID-19
por: Hoagwood, Kimberly Eaton, et al.
Publicado: (2021)

Protocol for fast scRNA-seq raw data processing using scKB and non-arbitrary quality control with COPILOT
por: Hsu, Che-Wei, et al.
Publicado: (2022)

scReadSim: a single-cell RNA-seq and ATAC-seq read simulator
por: Yan, Guanao, et al.
Publicado: (2023)

scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
por: Zhang, Ziqi, et al.
Publicado: (2022)

Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets
por: Shainer, Inbal, et al.
Publicado: (2021)

TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq
por: Shichino, Shigeyuki, et al.
Publicado: (2022)

scDIOR: single cell RNA-seq data IO software
por: Feng, Huijian, et al.
Publicado: (2022)

scGR-seq: Integrated analysis of glycan and RNA in single cells
por: Odaka, Haruki, et al.
Publicado: (2022)

Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
por: Ntranos, Vasilis, et al.
Publicado: (2016)

scAIDE: clustering of large-scale single-cell RNA-seq data reveals putative and rare cell types
por: Xie, Kaikun, et al.
Publicado: (2020)

CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data
por: Kozlov, Alexey, et al.
Publicado: (2022)

Using topic modeling to detect cellular crosstalk in scRNA-seq
por: Pancheva, Alexandrina, et al.
Publicado: (2022)

scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing
por: Li, Kejie, et al.
Publicado: (2023)

Automated methods for cell type annotation on scRNA-seq data
por: Pasquini, Giovanni, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_7ofmjhhu14oo39h8svs8h7u4lm