deconvolution

HBMITool: a user-friendly software for labeling Human Brain Microscopy Images

HBMITool is a software for editing cell detection/classification results in IF microscopy of human postmortem brains to improve accuracy and reproducibility.

Bridging micro and macro: accurate registration of the BigBrain dataset with the MNI PD25 and ICBM152 atlases

The paper registers the BigBrain atlas with MNI PD25 and ICBM152 atlases to bridge histological and MRI data for neurological research and surgery.

Field application of an eDNA assay for the endangered white-clawed crayfish Austropotamobius pallipes

This paper develops an eDNA assay using COI gene primers and MGB probe for detecting the endangered white-clawed crayfish in water samples, showing its effectiveness in lotic systems.

The repertoire of serous ovarian cancer non-genetic heterogeneity revealed by single-cell sequencing of normal fallopian tube epithelial cells

The paper uses single-cell sequencing to identify non-genetic heterogeneity in serous ovarian cancer by analyzing normal fallopian tube epithelial cells and their subtype signatures.

Decoding of selective attention to continuous speech from the human auditory brainstem response

This paper decodes selective attention to speech from human auditory brainstem responses using statistical models, showing accurate attention focus decoding from short EEG recordings.

Robin Hood: non-fitting, non-smoothing image detrending for bleaching correction

The paper introduces Robin Hood, an automatic detrending algorithm for fluorescence microscopy that performs well at low intensities, and evaluates it using simulated and low photon budget live cell images.

Deconvolution of Nucleic-acid Length Distributions: A Gel Electrophoresis Analysis Tool and Applications

The paper introduces a software tool for analyzing DNA fragment size distributions using gel electrophoresis images, offering a cost-effective alternative to commercial systems.

CRISPR/Cas9-targeted removal of unwanted sequences from small-RNA sequencing libraries

The paper introduces MAD-DASH, a CRISPR/Cas9-based method to remove adapter dimers and highly expressed smRNAs from small RNA sequencing libraries, improving quantification of low-abundance species.

CRISPRCloud2: A cloud-based platform for deconvoluting CRISPR screen data

CRISPRCloud2 provides a cloud-based platform for deconvoluting CRISPR screen data with tools for read mapping, statistical analysis, visualization, and integration with other resources.

Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data

quanTIseq estimates absolute fractions of ten immune cell types from bulk RNA-seq; across TCGA, CXCL9/CXCR3 expression, not mutational load, tracks CD8+ T cell infiltration.

Accelerating iterative deconvolution and multiview fusion by orders of magnitude

This paper introduces faster deconvolution and multiview fusion methods, achieving speedups of 10 to several thousand-fold over previous approaches.

Variational Autoencoder: An Unsupervised Model for Modeling and Decoding fMRI Activity in Visual Cortex

This paper uses a variational autoencoder to model and decode fMRI activity in the visual cortex, finding lower prediction accuracy compared to CNNs but successful decoding of latent variables.

Fast and Robust Deconvolution of Tumor Infiltrating Lymphocyte from Expression Profiles using Least Trimmed Squares

FARDEEP improves tumor-infiltrating lymphocyte deconvolution by using least trimmed squares to reduce outliers, providing more accurate immune cell composition estimates.

Efficient long single molecule sequencing for cost effective and accurate sequencing, haplotyping, and de novo assembly

This paper introduces stLFR, a low-cost method for long DNA sequencing that enables accurate variant calling, haplotyping, and de novo assembly.

DNA methylation-based immune cell deconvolution in solid tumors

This study uses DNA methylation data to accurately predict immune cell infiltration in solid tumors, particularly in melanoma, and provides a simple model for clinical application.

Insights from deconvolution of cell subtype proportions enhance the interpretation of functional genomic data.

The paper shows that estimating cell subtype proportions from functional genomic data improves interpretation of human phenotypic associations by revealing cellular events.

Decoding Complex Sounds Using Broadband Population Recordings from Secondary Auditory Cortex of Macaques

This study decodes English words from neural activity in macaques' secondary auditory cortex using spike-based machine learning, showing the auditory cortex processes complex sounds as a distributed network.

The Arrival of Steppe and Iranian Related Ancestry in the Islands of the Western Mediterranean

The paper analyzes ancient DNA from the Balearic Islands, Sicily, and Sardinia to trace the arrival and spread of Steppe and Iranian-related ancestries in the western Mediterranean, revealing complex admixture histories.

An R Implementation of Tumor-Stroma-Immune Transcriptome Deconvolution Pipeline using DeMixT

The paper presents an R pipeline using DeMixT for tumor-stroma-immune transcriptome deconvolution, showing immune proportion variations in COAD and PRAD datasets.

Reconstruction of clone- and haplotype-specific cancer genome karyotypes from bulk tumor samples

This paper introduces RCK, an algorithm to reconstruct clone- and haplotype-specific cancer karyotypes from bulk tumor samples, showing improved accuracy over existing methods.

Estimating Individual Contributions to Complex DNA SNP Mixtures

The paper introduces three methods to estimate individual DNA contributions in forensic SNP mixtures using HTS/MPS data.

CRISPRs for strain tracking and its application to microbiota transplantation data analysis

The paper develops CRISPRtrack, a pipeline using CRISPR spacer content to track donor strains in fecal microbiota transplantation and quantify microbiome similarity.

Bulk Tissue Cell Type Deconvolution with Multi-Subject Single-Cell Expression Reference

MuSiC deconvolves bulk RNA-seq data using single-cell RNA-seq reference to estimate cell type composition, outperforming existing methods in tissues with closely related cell types.

Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data

~2-4x SNR gains and 20-300x compression on calcium and voltage imaging, from a patch-wise penalized matrix decomposition that splits signal from temporally uncorrelated noise without hyperparameter tuning.

Minerva: An Alignment and Reference Free Approach to Deconvolve Linked-Reads for Metagenomics

Minerva deconvolves barcoded reads in metagenomics to improve taxonomic assignments and sequence clustering without a reference genome.

A novel computational complete deconvolution method using RNA-seq data

This paper introduces CDSeq, a computational method that estimates both cell type proportions and gene expression profiles from bulk RNA-seq data, outperforming existing methods in accuracy.

Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data

decontam, an R package, classifies contaminant sequences in marker-gene and metagenomic data by their inverse frequency-DNA concentration relationship and higher prevalence in negative controls.

Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease

The paper develops a method to determine the tissue origins of circulating cell-free DNA using a methylation atlas and validates it in healthy and disease states.

Evaluating Clinical Benefit in I-SPY 2

The paper introduces a clinical benefit index (CBI) to quantify and integrate drug efficacy and toxicity using patient-reported outcomes for adaptive randomization and regulatory evaluation.

dtangle: accurate and fast cell-type deconvolution

dtangle deconvolves cell-type proportions from bulk RNA-seq data, showing competitiveness with existing methods and utility in analyzing immune responses to Lyme disease.