Cargando…

DTWscore: differential expression and cell clustering analysis for time-series single-cell RNA-seq data

BACKGROUND: The development of single-cell RNA sequencing has enabled profound discoveries in biology, ranging from the dissection of the composition of complex tissues to the identification of novel cell types and dynamics in some specialized cellular environments. However, the large-scale generati...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wang, Zhuo, Jin, Shuilin, Liu, Guiyou, Zhang, Xiurui, Wang, Nan, Wu, Deliang, Hu, Yang, Zhang, Chiping, Jiang, Qinghua, Xu, Li, Wang, Yadong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2017
Materias:	Methodology Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5442705/ https://www.ncbi.nlm.nih.gov/pubmed/28535748 http://dx.doi.org/10.1186/s12859-017-1647-3

Ejemplares similares

A Method Based on Differential Entropy-Like Function for Detecting Differentially Expressed Genes Across Multiple Conditions in RNA-Seq Studies
por: Wang, Zhuo, et al.
Publicado: (2019)

scMTD: a statistical multidimensional imputation method for single-cell RNA-seq data leveraging transcriptome dynamic information
por: Qi, Jing, et al.
Publicado: (2022)

Impact of data preprocessing on cell-type clustering based on single-cell RNA-seq data
por: Wang, Chunxiang, et al.
Publicado: (2020)

An iteration normalization and test method for differential expression analysis of RNA-seq data
por: Zhou, Yan, et al.
Publicado: (2014)

LncRNA2Target: a database for differentially expressed genes after lncRNA knockdown or overexpression
por: Jiang, Qinghua, et al.
Publicado: (2014)

On Differential Gene Expression Using RNA-Seq Data
por: Lee, Juhee, et al.
Publicado: (2011)

Single_cell_GRN: gene regulatory network identification based on supervised learning method and Single-cell RNA-seq data
por: Yang, Bin, et al.
Publicado: (2022)

Nonparametric Tests for Differential Histone Enrichment with ChIP-Seq Data
por: Wu, Qian, et al.
Publicado: (2015)

Using DenseFly algorithm for cell searching on massive scRNA-seq datasets
por: Chen, Yixin, et al.
Publicado: (2020)

Comparative performance of the BGISEQ-500 and Illumina HiSeq4000 sequencing platforms for transcriptome analysis in plants
por: Zhu, Fu-Yuan, et al.
Publicado: (2018)

Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data
por: Gundogdu, Pelin, et al.
Publicado: (2022)

ATAC-seq normalization method can significantly affect differential accessibility analysis and interpretation
por: Reske, Jake J., et al.
Publicado: (2020)

LncRNA2Function: a comprehensive resource for functional investigation of human lncRNAs based on RNA-seq data
por: Jiang, Qinghua, et al.
Publicado: (2015)

A statistical normalization method and differential expression analysis for RNA-seq data between different species
por: Zhou, Yan, et al.
Publicado: (2019)

Wellington-bootstrap: differential DNase-seq footprinting identifies cell-type determining transcription factors
por: Piper, Jason, et al.
Publicado: (2015)

Identification of cell subpopulations associated with disease phenotypes from scRNA-seq data using PACSI
por: Liu, Chonghui, et al.
Publicado: (2023)

Time Series Expression Analyses Using RNA-seq: A Statistical Approach
por: Oh, Sunghee, et al.
Publicado: (2013)

Differential expression analysis for paired RNA-seq data
por: Chung, Lisa M, et al.
Publicado: (2013)

Power analysis for RNA-Seq differential expression studies
por: Yu, Lianbo, et al.
Publicado: (2017)

INC-Seq: accurate single molecule reads using nanopore sequencing
por: Li, Chenhao, et al.
Publicado: (2016)

DeLTa-Seq: direct-lysate targeted RNA-Seq from crude tissue lysate
por: Kashima, Makoto, et al.
Publicado: (2022)

Gene set analysis controlling for length bias in RNA-seq experiments
por: Ren, Xing, et al.
Publicado: (2017)

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

Stability of methods for differential expression analysis of RNA-seq data
por: Lin, Bingqing, et al.
Publicado: (2019)

Improved volume variable cluster model method for crystal-lattice optimization: effect on isotope fractionation factor
por: Wang, Yan-Fang, et al.
Publicado: (2022)

The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq
por: Wills, Quin F., et al.
Publicado: (2017)

A robust nonlinear low-dimensional manifold for single cell RNA-seq data
por: Verma, Archit, et al.
Publicado: (2020)

The role of immunohistochemistry in medullomyoblastoma – a case series highlighting divergent differentiation
por: Sachdeva, Man Updesh S, et al.
Publicado: (2008)

Approximate inference of gene regulatory network models from RNA-Seq time series data
por: Thorne, Thomas
Publicado: (2018)

ProbPFP: a multiple sequence alignment algorithm combining hidden Markov model optimized by particle swarm optimization with partition function
por: Zhan, Qing, et al.
Publicado: (2019)

An optimized approach for multiplexing single-nuclear ATAC-seq using oligonucleotide-conjugated antibodies
por: Bera, Betelehem Solomon, et al.
Publicado: (2023)

Lag penalized weighted correlation for time series clustering
por: Chandereng, Thevaa, et al.
Publicado: (2020)

Differential motif enrichment analysis of paired ChIP-seq experiments
por: Lesluyes, Tom, et al.
Publicado: (2014)

Differential meta-analysis of RNA-seq data from multiple studies
por: Rau, Andrea, et al.
Publicado: (2014)

Small-scale sequencing enables quality assessment of Ribo-Seq data: an example from Arabidopsis cell culture
por: Mahboubi, Amir, et al.
Publicado: (2021)

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

Purification of nanogram-range immunoprecipitated DNA in ChIP-seq application
por: Zhong, Jian, et al.
Publicado: (2017)

EBS-seq: enrichment-based method for accurate analysis of 5-hydroxymethylcytosine at single-base resolution
por: Lee, Jaywon, et al.
Publicado: (2023)

Polled Digital Cell Sorter (p-DCS): Automatic identification of hematological cell types from single cell RNA-sequencing clusters
por: Domanskyi, Sergii, et al.
Publicado: (2019)

JOINT for large-scale single-cell RNA-sequencing analysis via soft-clustering and parallel computing
por: Cui, Tao, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_nsd129bqb91bqfm5qu773hcl5s