[HTML][HTML] A hitchhiker's guide to single-cell transcriptomics and data analysis pipelines
Single-cell transcriptomics (SCT) is a tour de force in the era of big omics data that has led to
the accumulation of massive cellular transcription data at an astounding resolution of single …
the accumulation of massive cellular transcription data at an astounding resolution of single …
A review of computational strategies for denoising and imputation of single-cell transcriptomic data
Motivation The advancements of single-cell sequencing methods have paved the way for
the characterization of cellular states at unprecedented resolution, revolutionizing the …
the characterization of cellular states at unprecedented resolution, revolutionizing the …
Clustering ensemble in scRNA-seq data analysis: Methods, applications and challenges
With the rapid development of single-cell RNA-sequencing techniques, various
computational methods and tools were proposed to analyze these high-throughput data …
computational methods and tools were proposed to analyze these high-throughput data …
Improving bulk RNA-seq classification by transferring gene signature from single cells in acute myeloid leukemia
The advances in single-cell RNA sequencing (scRNA-seq) technologies enable the
characterization of transcriptomic profiles at the cellular level and demonstrate great promise …
characterization of transcriptomic profiles at the cellular level and demonstrate great promise …
Evaluating the performance of dropout imputation and clustering methods for single-cell RNA sequencing data
Recent advances in single-cell RNA sequencing (scRNA-seq) provide exciting opportunities
for transcriptome analysis at single-cell resolution. Clustering individual cells is a key step to …
for transcriptome analysis at single-cell resolution. Clustering individual cells is a key step to …
Inferring cell-type-specific genes of lung cancer based on deep learning
N Cheng, C Chen, C Li, J Huang - Current Gene Therapy, 2022 - ingentaconnect.com
Background: Lung cancer is cancer with the highest incidence in the world, and there is
obvious heterogeneity within its tumor. The emergence of single-cell sequencing technology …
obvious heterogeneity within its tumor. The emergence of single-cell sequencing technology …
Imputation methods for scRNA sequencing data
More and more researchers use single-cell RNA sequencing (scRNA-seq) technology to
characterize the transcriptional map at the single-cell level. They use it to study the …
characterize the transcriptional map at the single-cell level. They use it to study the …
Imputing dropouts for single-cell RNA sequencing based on multi-objective optimization
Motivation Single-cell RNA sequencing (scRNA-seq) technologies have been testified
revolutionary for their promotion on the profiling of single-cell transcriptomes at single-cell …
revolutionary for their promotion on the profiling of single-cell transcriptomes at single-cell …
CDSImpute: An ensemble similarity imputation method for single-cell RNA sequence dropouts
Background Single-cell RNA-sequencing enables the opportunity to investigate cell
heterogeneity, discover new types of cells and to perform transcriptomic reconstruction at a …
heterogeneity, discover new types of cells and to perform transcriptomic reconstruction at a …
DSAE-Impute: Learning discriminative stacked autoencoders for imputing single-cell rna-seq data
S Gan, H Deng, Y Qiu, M Alshahrani… - Current …, 2022 - ingentaconnect.com
Background: Due to the limited amount of mRNA in single-cell, there are always many
missing values in scRNA-seq data, making it impossible to accurately quantify the …
missing values in scRNA-seq data, making it impossible to accurately quantify the …