deconvolution

Proteomics-constrained deconvolution reveals spatial cell-type programs in tumours

PISTACHIO improves spatial cell-type deconvolution in tumours using proteomics constraints and non-negative matrix factorization.

When Less Is Not More: DICEPro Mitigates the Impact of Incomplete Reference Matrices on Cellular Frequency Deconvolution.

The paper evaluates deconvolution methods' robustness to incomplete reference matrices and introduces DICEPro to improve performance by adjusting reference signatures.

3dcon: tomogram denoising by deconvolution

This paper introduces 3dcon, a deconvolution algorithm for cryo-electron tomography to reduce structural artifacts in reconstructed 3D volumes.

Rapid GeneXpert surveillance of influenza A virus in seabirds and the environment provides early warning for wildlife health in Aotearoa New Zealand

This study evaluates the GeneXpert II platform for rapid influenza A virus detection in environmental and wildlife samples at a New Zealand seabird colony, demonstrating its feasibility for early warning surveillance.

Functional Templates in fMRI: Building Accurate and Interpretable Group-Level Decoders

This paper compares functional alignment methods and template construction strategies in fMRI to improve group-level decoding accuracy and interpretability.

HOMED enables hierarchical and multimodal optimization of DNA methylation deconvolution across tissues

HOMED improves DNA methylation deconvolution by integrating cell-lineage hierarchies and single-cell data, achieving higher accuracy across tissues.

Anthocyanin-associated cellular programs underlying terroir variation in Cabernet Sauvignon grape berry revealed by SEED-based deconvolution

The paper introduces SEED, a plant-specific deconvolution framework for bulk RNA-seq data, and applies it to identify terroir-associated cell subtypes in Cabernet Sauvignon grapes.

UnBlender: validating individual analyses in respiratory bulk RNA-seq cell type deconvolution

UnBlender enables cell type deconvolution in respiratory bulk RNA-seq data and provides routine validation of deconvolution accuracy.

Instant Prior-Free Resolution Enhancement for Cross-Modality Microscopy

This paper introduces NFR, a prior-free algorithm that enhances microscopy resolution without requiring PSF estimation, achieving results beyond the Sparrow limit and improving super-resolution techniques.

PRISMA: A tensor-based framework for deconstructing the genetic architecture of complex diseases, with application to diabetic retinopathy

PRISMA decomposes GWAS signals into tissue-specific genetic axes for diabetic retinopathy, revealing novel targets and regulatory patterns.

BINSEQ: A Family of High-Performance Binary Formats for Nucleotide Sequences

BINSEQ introduces binary formats for sequencing data to enable faster parallel processing, reducing analysis time for genome and transcriptome studies.

Spatial-DC: a robust deep learning-based method for deconvolution of spatial proteomics

Spatial-DC improves spatial proteomics deconvolution by using deep learning to infer cell-type composition and reconstruct proteomic profiles from low-resolution data.

Ratio Percentile Deviation (RPD): A nonparametric, compositionally robust method for measuring the divergence of a microbial sample from a reference dataset

This paper introduces RPD, a nonparametric method to measure microbial sample divergence from reference datasets, showing it outperforms existing methods in several analyses.

SpatialClaw: A Memory-Augmented Autonomous Ecosystem for Spatial Omics Analysis

SpatialClaw provides a memory-augmented system for spatial omics analysis, enabling end-to-end workflows through natural language interaction and outperforming standard models in benchmarking.

Two Novel Genes, Stb23 and Stb24, Conferring Multi-stage Resistance to Zymoseptoria tritici: Rapid Deployment in Marker-Assisted Wheat Breeding

This study identifies two new resistance loci, Stb23 and Stb24, against Zymoseptoria tritici and develops KASP markers for their use in wheat breeding.

The ATLAS Penalty: Auxiliary-Transformed Location-Aware Smoothing with Applications to Spatial Transcriptomics

The paper introduces the ATLAS penalty for spatially smooth deconvolution in spatial transcriptomics, showing improved spatial domain detection using auxiliary covariates.

Early apelin receptor activation attenuates elastase-induced emphysema and preserves endothelial apelin receptor signaling in mice

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: Identifiability-Based Decontamination for Spatial Transcriptomics

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

Transferable spatial omics deconvolution with SpaRank

SpaRank is a transferable spatial deconvolution framework that uses rank-based encodings to robustly infer cell-type compositions across diverse biological contexts and omics modalities.

A Conditional Random Field approach for de novo reconstruction of bacterial haplotypes from a de Bruijn graph representation

This paper introduces HaploDetox, a method for de novo bacterial haplotype reconstruction using a Conditional Random Field approach on de Bruijn graphs, achieving improved SNP phasing accuracy.

Interleukin-1β Drives Disease Progression in Arrhythmogenic Cardiomyopathy

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.

Metacontam: A Negative Control-Free Decontamination Method for Metagenomic Analysis

Metacontam is a decontamination method for metagenomic data that improves detection of low-abundance contaminants without needing negative controls.

CSsingle: A Unified Tool for Robust Decomposition of Bulk and Spatial Transcriptomic Data Across Diverse Single-Cell References

CSsingle improves bulk and spatial transcriptomic data decomposition by integrating with scRNA-seq, showing better accuracy and revealing MCCs as potential biomarkers in EAC.

Hormonally responsive bovine oviductal organoids recapitulate native oviductal secretions and enhance sperm capacitation

Bovine oviductal organoids treated with estradiol or a progesterone analog reproduce follicular and luteal transcriptomes and secretomes; estradiol-stimulated secretions boost bull sperm capacitation and acrosome reaction.

Improved deconvolution of circulating tumor DNA from ultra-low-pass whole-genome methylation sequencing using CelFiE-ISH

This study improves ctDNA deconvolution in ULP-WGS data using CelFiE-ISH, achieving lower cancer fraction detection limits than CNA benchmarks.

Enhancing Biomedical Optical Volumetric Imaging via Self-Supervised Orthogonal Learning

This paper introduces VALID, a self-supervised denoising method for volumetric biomedical imaging that improves structural fidelity across multiple modalities.

HeteroRC: Decoding latent information from dynamic neural responses with interpretable heterogeneous reservoir computing

HeteroRC improves neural decoding by capturing nonlinear and non-phase-locked dynamics, outperforming linear methods and revealing latent neural representations in EEG data.

Automated refinement of metagenomic bins and estimation of binning success using itBins

itBins refines metagenomic bins and estimates binning success using %GC content, coverage, and taxonomy, outperforming existing tools in speed and accuracy.

The RNA editing enzyme ADARB1 is readily detectable in primary auditory neurons and provides a means for automated counting

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

Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution

This study improves bulk RNA-seq deconvolution by integrating single-cell and single-nucleus datasets through filtering and transformation strategies, achieving near-scRNA-seq accuracy.