deconvolution

Time-Dependent Image Restoration of Low-SNR Live Cell Ca2+ Fluorescence Microscopy Data

This paper introduces a variational image restoration method for low-SNR live cell Ca2+ fluorescence microscopy data, demonstrating its effectiveness across synthetic and biological datasets.

anonymizeBAM: Versatile anonymization of human sequence data for open data sharing

anonymizeBAM removes donor-related genetic information from sequence data, enabling secure open data sharing in genomics.

Natural isotope correction improves analysis of protein modification dynamics

The paper introduces PICor, a tool for isotopologue correction in proteomics and metabolomics, demonstrating its importance for accurate analysis of protein modification dynamics.

Decoding of cortex-wide brain activity from local recordings of neural potentials

This study decodes large-scale cortical activity from local surface potentials using a recurrent neural network, showing that surface potentials contain rich information about neural activity across multiple regions.

De novo virus inference and host prediction from metagenome using CRISPR spacers

The paper develops a CRISPR-based method to infer viral sequences and predict hosts from metagenomic data, identifying numerous viral genomes and analyzing the evolution of a retroelement locus.

How many markers are needed to robustly determine a cell's type?

The paper investigates how many markers are needed to robustly determine cell types using data from the BICCN, finding that 10 to 200 meta-analytic markers provide optimal performance.

Medical genetics workforce in Brazil: practitioners, services, and disease distribution

The paper assesses the distribution of medical geneticists and rare genetic diseases in Brazil, finding significant regional disparities in access to genetic services.

Copy-scAT: Deconvoluting single-cell chromatin accessibility of genetic subclones in cancer

Copy-scAT deconvolutes single-cell chromatin accessibility to infer genetic subclones in cancer, revealing how genetics influence chromatin profiles and subclonal phenotypes.

Can DNA help trace the local trade of pangolins? A genetic assessment of white-bellied pangolins from the Dahomey Gap (West Africa)

The paper uses genetic data to trace pangolin trade in the Dahomey Gap, finding population declines and limited ability to track individuals due to low genetic structure.

Assessing microbial growth of six pure cultures grown anaerobically using optical density, ATP measurements, DNA concentrations and 16S rRNA targeted qPCR to compare commonly used techniques in lab and industry settings

The paper compares four methods for monitoring microbial growth in pure cultures, finding DNA concentration as the most reliable and versatile technique.

A likelihood-based deconvolution of bulk gene expression data using single-cell references

This paper introduces RNA-Sieve, a likelihood-based method to deconvolve bulk RNA-seq data using single-cell references, providing accurate cell type proportion estimates and confidence intervals.

FrogCap: A modular sequence capture probe set for phylogenomics and population genetics for all frogs, assessed across multiple phylogenetic scales

FrogCap provides a modular probe set for phylogenomics and population genetics in frogs, tested across multiple scales and showing improved probe design success.

A comparative study between state-of-the-art MRI deidentification and AnonyMI, a new method combining re-identification risk reduction and geometrical preservation

This paper compares AnonyMI, a new MRI deidentification method, with state-of-the-art methods to evaluate their effectiveness in reducing re-identification risk while preserving geometrical information.

Identification of sample mix-ups and mixtures in microbiome data in Diversity Outbred mice

The paper identifies sample mix-ups and mixtures in microbiome data from Diversity Outbred mice using shotgun sequencing reads.

Accounting for 16S rRNA copy number prediction uncertainty and its implications in microbial diversity analyses

The paper develops RasperGade16S to model 16S rRNA gene copy number uncertainty, showing it improves GCN prediction and supports correction in most microbial communities.

StrainFLAIR: Strain-level profiling of metagenomic samples using variation graphs

StrainFLAIR uses variation graphs to estimate strain-level abundances in metagenomic samples, showing effectiveness on both simulated and real datasets.

CytoPro: A computational platform for accurate and robust assessment of cell contributions in bulk expression from diverse tissues and conditions

CytoPro is a deconvolution platform that accurately estimates cell-type composition from bulk gene expression, outperforming existing tools in accuracy and robustness.

Microbial loop of a Proterozoic ocean analogue

This study investigates the microbial loop in Lake Cadagno, revealing the distribution of microbial communities and their roles in nutrient cycling and organic matter recycling in a stratified, anoxic environment.

ARIC: Accurate and robust inference of cell type proportions from bulk gene expression or DNA methylation data

ARIC estimates cell type proportions from bulk gene expression or DNA methylation data, showing accuracy in both data types.

Estimating Intraclonal Heterogeneity and Subpopulation Changes from Perturbational Bulk Gene Expression Profiles in LINCS L1000 CMap by Premnas

Premnas estimates subpopulation changes from bulk L1000 profiles in CMap by learning subpopulation representations from single-cell RNA-seq data, enabling new insights into drug responses and resistance.

RepairSig: Deconvolution of DNA damage and repaircontributions to the mutational landscape of cancer

RepairSig identifies DNA repair deficiency mutational signatures in cancer by modeling interactions between mutagenic processes, replacing multiple signatures with a single representative one in breast cancer.

Strategies for cellular deconvolution in human brain RNA sequencing data

The paper shows that incorporating cell size parameters improves deconvolution of brain RNA-seq data, but using external cell size estimates can introduce bias.

Interpreting wide-band neural activity using convolutional neural networks

This paper develops a deep-learning framework to decode sensory and behavioural variables from wide-band neural data with minimal user input and generalization across stimuli and brain regions.

Placental gene expression-based cell type deconvolution: Cell proportions drive preeclampsia gene expression differences

The paper deconvolves placental gene expression data to show cell type proportions drive preeclampsia gene expression differences, reducing differentially expressed genes after adjustment.

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

This study benchmarks six plasmid prediction tools for E. coli short-read data, finding that none reliably reconstruct all plasmids, especially those carrying antibiotic resistance genes.

Representational learning of brain responses in executive function and higher-order cognition using deep graph convolutions

This paper uses deep graph convolutions to decode brain activity across cognitive domains, finding that integration boosts high-order cognition decoding while segregation suffices for motor tasks.

Ribocutter: Cas9-mediated rRNA depletion from multiplexed riboseq libraries

The paper introduces a Cas9-based method and software tool to efficiently deplete rRNA/ncRNA contaminants from Ribo-seq libraries, significantly increasing useful reads while minimizing off-target effects.

Determining molecular archetype composition and expression from bulk tissues with unsupervised deconvolution

This paper introduces an unsupervised deconvolution method, CAM3.0, to determine molecular archetype composition and expression from bulk tissues, showing its effectiveness through simulations and case studies.

Tracing the evolution of aneuploid cancers from multiregional sequencing

This paper develops a semi-supervised algorithm to deconvolve clonal variants in tumors, accounting for tumor cell fraction and copy number changes across samples.

LocalZProjector and DeProj: A toolbox for local 2D projection and accurate morphometrics of large 3D microscopy images.

The paper introduces LocalZProjector and DeProj, tools for accurate 2D projection and morphometric analysis of 3D microscopy images, showing they handle complex data and correct projection distortions.