Single-cell and spatial transcriptomics

scXpand: Pan-cancer detection of T-cell clonal expansion from single-cell RNA sequencing without paired single-cell TCR sequencing

scXpand detects T-cell clonal expansion in cancer from scRNA-seq without TCR sequencing, showing accuracy across tissues and subtypes.

Differential correlation across subpopulations of single cells in subtypes of acute myeloid leukemia

The paper introduces a method to detect differential correlations between protein pairs across subpopulations in AML samples, revealing nonlinear relationships in cytometry data.

Binary-SPA: A Reference-Free Method for Cell Annotation in High-Resolution Spatial Transcriptomics

Binary-SPA improves cell type annotation in spatial transcriptomics by using a two-stage approach without requiring external reference data.

Interpretable Integration of CITE-seq RNA and ADT Profiles Without Explicit Modality-Weight Tuning via Tensor Decomposition-Based Unsupervised Feature Extraction

The paper introduces a tensor decomposition method for integrating CITE-seq RNA and ADT data without modality-weight tuning, showing competitive but not superior performance compared to existing methods.

A single-cell transcriptomic atlas of the periventricular proliferative zone in the late gestation fetal brain in the pigtail macaque

The paper constructs a single-cell RNA-Seq atlas of the periventricular proliferative zone in late-gestation pigtail macaque fetal brain, revealing cell states similar to human fetal brain.

Tissue-level division of labor is coordinated across organs through universal programs and context-specific adaptations

The paper identifies universal and tissue-specific transcriptional programs in human and mouse tissues using single-cell RNA sequencing and shows how they coordinate function across organs.

PROFET Predicts Continuous Gene Expression Dynamics from scRNA-seq Data to Elucidate Heterogeneity of Cancer Treatment Responses

hoodscanR: profiling single-cell neighborhoods in spatial transcriptomics data

hoodscanR identifies and analyzes cell neighborhoods in spatial transcriptomics data, revealing transcriptional differences in tumor cells across neighborhoods.

A unified analysis of cell-type and trajectory-associated pathways in single-cell data using Phoenix

Phoenix identifies cell-type and trajectory-associated pathways in single-cell data using random forest models and non-parametric testing, outperforming existing tools in capturing small pathway activities and revealing cross-species overlaps.

Improving RNA-seq protocols

The paper optimizes RNA-seq protocols to increase usable reads by 60% using a funnel strategy, improving cost-efficiency in bulk RNA-seq.

Multi-Sample and Multi-Group Spatial Colocalization Analysis Using PANORAMIC

PANORAMIC improves spatial colocalization analysis by accounting for within-sample uncertainty, revealing stronger immune cell colocalization in specific colorectal cancer subtypes.

SpaMTP: Integrative Statistical Analysis and Visualisation of Spatial Metabolomics and Transcriptomics data.

SpaMTP integrates spatial metabolomics and transcriptomics data through a comprehensive analysis pipeline and visualization tools.

CellTune: An integrative software for accurate cell classification in spatial proteomics

CellTune is a software tool for cell classification in spatial proteomics that outperforms existing methods with high accuracy and resolution.

Continual integration of single-cell multimodal data with MIRACLE

MIRACLE enables efficient continual integration of single-cell multimodal data, updating cell atlases with new data without reintegration, and identifies novel cell types and transfers labels across datasets.

SpatialFormer: Universal Spatial Representation Learning from Subcellular Molecular to Multicellular Landscapes

SpatialFormer integrates spatial and gene expression data to improve tasks like batch correction and cell-type annotation in spatial transcriptomics.

Finding stable clusterings of single-cell RNA-seq data

The paper introduces a method to assess clustering stability in single-cell RNA-seq data by comparing clusterings of subsets with the full dataset, finding that some clusterings are stable even with large datasets.

Assessing Scale and Predictive Diversity in Models for Single-Cell Transcriptomics based on Geneformer

This study evaluates transformer-based models for single-cell transcriptomics, finding that larger datasets don't consistently improve downstream tasks and rank-based models struggle with batch effect correction.

simPIC: flexible simulation of single-cell ATAC-seq paired-insertion counts from individuals to populations

simPIC simulates single-cell ATAC-seq count data across individuals and populations to enable controlled evaluation of chromatin accessibility QTL mapping methods.

Deciphering Cell Cycle Dynamics and Cell States in Single-cell RNA-seq data with SPAE

This paper introduces SPAE, a model for analyzing cell cycle dynamics and states in scRNA-seq data, showing improved accuracy and robustness in cell cycle characterization and cancer cell cycle transition prediction.

CellCover Defines Marker Gene Panels Capturing Developmental Progression in Neocortical Neural Stem Cell Identity

CellCover identifies marker gene panels for cell types by solving a set-covering problem, outperforming differential expression methods in capturing cell-specific signals and developmental progression.

Essential Resources for Curated Immune Markers and Antibody Panels in Cytometry Analysis

The paper introduces ImapDB, a database for immune markers and antibody panels, to streamline immune profiling assays and enhance research efficiency.

Trajectory-informed gene feature selection in single-cell analysis with SEEK-VFI

The paper introduces SEEK-VFI, a method for selecting trajectory-relevant genes in single-cell analysis, which improves trajectory inference and downstream analyses.

IDEAL-Age: an interpretable deep learning framework for single-cell resolution profiling of immunological aging

IDEAL-Age is a deep learning framework that profiles immunological aging at single-cell resolution, showing improved predictive performance and revealing cellular contributions to aging processes.

RETROFIT: REFERENCE-FREE DECONVOLUTION OF CELL-TYPE MIXTURES IN SPATIAL TRANSCRIPTOMICS

RETROFIT deconvolves cell-type mixtures in spatial transcriptomics without requiring references, outperforming existing methods and matching reference-based approaches when references are imperfect.

cellGeometry: ultra-fast single-cell deconvolution of bulk RNA-Seq using a geometric solution

cellGeometry deconvolutes bulk RNA-Seq using geometric methods, offering faster and more accurate results than existing approaches.

Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features

This study constructs a pan-cancer single-cell multi-omic atlas to uncover gene regulatory principles in cancer cell states and environmental features across diverse cancer types.

Spatial Total RNA Sequencing of Formalin-Fixed Paraffin Embedded Tissues by spRandom-seq

This paper introduces spRandom-seq, a spatial RNA sequencing method for FFPE tissues, which captures both host and microbial RNAs with higher efficiency than oligo(dT)-based methods.

Global StationaryOT: Trajectory inference for aging time courses of single-cell snapshots

This paper introduces a method to infer cell trajectories from aging time courses, improving accuracy in noisy data by leveraging temporal information.

Flexible and high-throughput simultaneous profiling of gene expression and chromatin accessibility in single cells

The paper introduces easySHARE-seq, a method for simultaneous single-cell ATAC-seq and RNA-seq, showing improved transcript recovery and scalability in murine liver nuclei.

Are Different Populations Fairly Represented in Single-Cell Omic Atlases?

The paper evaluates demographic representation in single-cell omic atlases and finds significant over-representation of European populations and under-representation of Asian and Latino individuals.