Improving replicability in single-cell RNA-Seq cell type discovery with Dune
Background Single-cell transcriptome sequencing (scRNA-Seq) has allowed new types of
investigations at unprecedented levels of resolution. Among the primary goals of scRNA …
investigations at unprecedented levels of resolution. Among the primary goals of scRNA …
SCIPAC: quantitative estimation of cell-phenotype associations
Numerous algorithms have been proposed to identify cell types in single-cell RNA
sequencing data, yet a fundamental problem remains: determining associations between …
sequencing data, yet a fundamental problem remains: determining associations between …
scBoolSeq: Linking scRNA-seq statistics and Boolean dynamics
G Magaña-López, L Calzone, A Zinovyev… - PLOS Computational …, 2024 - journals.plos.org
Boolean networks are largely employed to model the qualitative dynamics of cell fate
processes by describing the change of binary activation states of genes and transcription …
processes by describing the change of binary activation states of genes and transcription …
[PDF][PDF] scMaSigPro: differential expression analysis along single-cell trajectories
Motivation Understanding the dynamics of gene expression across different cellular states is
crucial for discerning the mechanisms underneath cellular differentiation. Genes that exhibit …
crucial for discerning the mechanisms underneath cellular differentiation. Genes that exhibit …
AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification
X Zhu, S Meng, G Li, J Wang, X Peng - Bioinformatics, 2024 - academic.oup.com
Motivation Dropout events bring challenges in analyzing single-cell RNA sequencing data
as they introduce noise and distort the true distributions of gene expression profiles. Recent …
as they introduce noise and distort the true distributions of gene expression profiles. Recent …
scCRT: a contrastive-based dimensionality reduction model for scRNA-seq trajectory inference
Trajectory inference is a crucial task in single-cell RNA-sequencing downstream analysis,
which can reveal the dynamic processes of biological development, including cell …
which can reveal the dynamic processes of biological development, including cell …
scINRB: single-cell gene expression imputation with network regularization and bulk RNA-seq data
Y Kang, H Zhang, J Guan - Briefings in Bioinformatics, 2024 - academic.oup.com
Single-cell RNA sequencing (scRNA-seq) facilitates the study of cell type heterogeneity and
the construction of cell atlas. However, due to its limitations, many genes may be detected to …
the construction of cell atlas. However, due to its limitations, many genes may be detected to …
BERMAD: batch effect removal for single-cell RNA-seq data using a multi-layer adaptation autoencoder with dual-channel framework
X Zhan, Y Yin, H Zhang - Bioinformatics, 2024 - academic.oup.com
Motivation Removal of batch effect between multiple datasets from different experimental
platforms has become an urgent problem, since single-cell RNA sequencing (scRNA-seq) …
platforms has become an urgent problem, since single-cell RNA sequencing (scRNA-seq) …
Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference
Single-cell RNA sequencing (scRNA-seq) experiments have become instrumental in
developmental and differentiation studies, enabling the profiling of cells at a single or …
developmental and differentiation studies, enabling the profiling of cells at a single or …
Distribution‐Agnostic Deep Learning Enables Accurate Single‐Cell Data Recovery and Transcriptional Regulation Interpretation
Single‐cell RNA sequencing (scRNA‐seq) is a robust method for studying gene expression
at the single‐cell level, but accurately quantifying genetic material is often hindered by …
at the single‐cell level, but accurately quantifying genetic material is often hindered by …