deconvolution

PRISM simultaneously decontaminates ambient RNA and corrects doublets in spatial transcriptomics data, achieving high accuracy and purity in a mouse cerebellum dataset.

Two weeks of post-weaning isolation in male mice altered expression of 106 CA1 genes, enriched for myelination, while chromatin accessibility shifted only at nominal significance and tracked expression weakly.

OTTER improves bisulfite deconvolution in tumor xenograft sequencing by restoring recall to 52%-54% while preserving transcriptomic accuracy.

RhizAeon deconvolves reticulate evolution by analyzing sequence mosaics and detecting recombination breakpoints with high accuracy and efficiency.

This paper decodes natural scenes from optogenetic responses in mouse visual cortex and shows that patterned stimulation can reproduce visual representations with high fidelity.

CellMAGE deconvolves gene expression in multi-parent populations by leveraging known parental genetic contributions, outperforming existing methods in accuracy and efficiency.

Leverage-weighted sketching plus sparse spatial regularization deconvolves 1.6 million Visium HD bins in 153 seconds on commodity hardware, revealing tissue-specific resolution limits where cell-type co-localization can reverse sign.

This study benchmarks decontamination methods for intratumoral microbiome analysis in PDAC, finding the Nj pipeline outperforms others in reducing contamination while preserving tumor signals.

Loss of extracellular matrix-integrin signaling switches off YAP/TEAD and lets prostate adenocarcinoma organoids turn neuroendocrine; LATS inhibition reverses it, and combined YAP, NOTCH and AR inhibition fully reprograms them.

This paper introduces a de novo method to identify transposable elements and inexact repeats from RNA-seq data without a reference genome, showing effectiveness in both model and non-model species.

This study shows early apelin receptor activation reduces emphysema in mice by limiting inflammation and airspace enlargement, but has no effect after disease onset.

DeSpotX improves spatial transcriptomics by decontaminating transcript data using a deep generative model that identifies contamination and enhances biological coherence.

Human arrhythmogenic cardiomyopathy hearts harbor a lesion niche of POSTN fibroblasts and NLRP3+ inflammatory macrophages; IL-1β neutralization in Dsg2-mutant mice reduced fibrosis, dysfunction, and ventricular ectopy.

The paper identifies ADARB1 as a marker for spiral ganglion neurons and validates its use for automated counting across species.

FX-seq improves snRNA-seq from FFPE and PFA-fixed tissues by removing crosslinks and preventing RNA leakage, enabling analysis of 321,710 nuclei from mouse and human samples.

The paper investigates whether DNA extraction methods co-purify prions, finding that commercial kits do not eliminate prion seeding activity, posing biosafety risks.

Thermostable RNaseH release of barcoded cDNA keeps sections intact for CODEX imaging, yielding same-section whole-transcriptome and protein maps plus CODEX-guided spot deconvolution in FFPE tissues.

This paper benchmarks cell type deconvolution methods in spatial transcriptomics, finding that a simple marker gene scoring approach performs well, especially for rare cell types, and applies it to study anti-PD1 immunotherapy in a mouse model.

Endogenous immunoglobulin G (IgG) immunostaining quantitatively labels apoptotic and necrotic hepatocytes across acute and chronic murine liver injury models, outperforming serum transaminases and histopathological Ishak scoring.

The paper introduces STRATA, a machine learning framework that estimates cell type proportions from MRI data, validated across disease models and species.

This paper improves neural decoding by exploiting correlations across trials and sessions, showing better accuracy for four behaviors in mice using interpretable models.

xCell 2.0 improves cell type proportion estimation from bulk RNA-seq data and predicts immune checkpoint blockade response more accurately than existing methods.

The paper introduces ZT Scan DIA, a metabolomics method improving annotation rates and isomer quantification in complex mixtures, with results validated in human plasma and mouse liver tissues.

This paper develops a gated recurrent variational autoencoder to decode decision-making from neuronal data in monkeys, showing comparable accuracy in multidimensional feature space.

This study uses multi-omic profiling to show that senescent cells, particularly late myofibroblasts, transiently contribute to cardiac remodeling after myocardial infarction.

spOT-NMF improves spatial transcriptomics deconvolution by using optimal transport, outperforming existing methods in accuracy and scalability across various resolutions and species.

StrainR2 accurately deconvolutes strain-level abundances in synthetic microbial communities using shotgun metagenomic sequencing and k-mer normalization.

This paper develops a multimodal imaging platform to track human cortical organoids in mice after stroke, showing their survival and maturation in specific brain regions.

MassNet provides a large-scale mass spectral corpus for proteomics, enabling AI-driven de novo peptide sequencing with improved performance over existing methods.

JMod improves sequence identification and quantification in multiplexed DIA proteomics by jointly modeling overlapping mass spectra, enabling higher throughput with maintained accuracy.