Article
|
Open Access
Featured
-
-
Article
| Open AccessIntegrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks
Papillary thyroid cancers (PTC) generally have good prognosis, but their recurrence rate remains high. Here, the authors use proteogenomics and metabolomics to identify molecular features in PTC tumours and determine PTC subtypes that are associated with prognosis and potential targeted therapies.
- Ning Qu
- , Di Chen
- & Rongliang Shi
-
Article
| Open AccessComparative characterization of the infant gut microbiome and their maternal lineage by a multi-omics approach
Here, the authors employ multi-omics on a cohort comprising three generations of family members, showing that fecal microbiota populations, functions, and metabolome of infants vary greatly from their maternal lineage, exhibiting a less diverse microbiota and differences in various metabolite classes including short- and branched-chain fatty acids.
- Tomás Clive Barker-Tejeda
- , Elisa Zubeldia-Varela
- & Alma Villaseñor
-
Article
| Open AccessscButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Technical limitations of simultaneously multi-omics profiling lead to highly noisy multi-modal data and substantial costs. Here, authors proposed a versatile framework and data augmentation schemes, capable of single-cell cross-modality translation and multiple extensive applications.
- Yichuan Cao
- , Xiamiao Zhao
- & Shengquan Chen
-
Article
| Open AccessMulti-omic integration of microbiome data for identifying disease-associated modules
Here, Muller et al. introduce MintTea, a method for analyzing multi-omic microbiome data and identifying disease-associated modules comprising mixed sets of features that collectively shift in disease, offering insights into microbiome-disease interactions.
- Efrat Muller
- , Itamar Shiryan
- & Elhanan Borenstein
-
Article
| Open AccessSystematic review and meta-analysis for a Global Patient co-Owned Cloud (GPOC)
Use of cloud-based personal health records are increasing globally. Here, authors introduce the Global Patient co-Owned Cloud (GPOC) concept. The systematic review and meta-analysis examine factors like data security, efficiency, privacy, and cost. It aims to establish a scientific basis for a GPOC, which may disseminate global artificial intelligence for healthcare.
- Niklas Lidströmer
- , Joe Davids
- & Eric Herlenius
-
Article
| Open AccessWidespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features
By developing computational algorithms, the authors annotated translated open reading frames in five eukaryotes and found many stable peptides are encoded by putative ‘noncoding’ regions of genomes.
- Haiwang Yang
- , Qianru Li
- & Zhe Ji
-
Article
| Open AccessRare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes
Congenital myasthenic syndromes are rare inherited neuromuscular disorders. Here, the authors attempt to explain diverse disease severity seen in 20 patients with shared CHRNE gene mutations with a multilayer network analysis that identifies individual-level impairments at the neuromuscular junction.
- Iker Núñez-Carpintero
- , Maria Rigau
- & Alfonso Valencia
-
Article
| Open AccessImputation of plasma lipid species to facilitate integration of lipidomic datasets
Advancements in plasma lipidomic profiling increase specificity of measurements but pose challenges in aligning datasets created at different times or platforms. Here the authors present a predictive framework for harmonising such datasets with different levels of granularity in their lipid measurements.
- Aleksandar Dakic
- , Jingqin Wu
- & Peter J. Meikle
-
Article
| Open AccessscDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data
Here the authors propose a deep learning model that integrates multi-condition, multi-batch single-cell RNA-sequencing datasets. The model disentangles biological variation (condition effect) from technical confounders (batch effect) and overcomes some limitations of existing approaches.
- Ziqi Zhang
- , Xinye Zhao
- & Xiuwei Zhang
-
Article
| Open AccessHuman whole-exome genotype data for Alzheimer’s disease
The heterogeneity of whole-exome sequencing (WES) data generation methods presents a challenge to joint analysis. Here, the authors present a bioinformatics strategy to generate high-quality data from processing diversely generated WES samples, as applied in the Alzheimer’s Disease Sequencing Project.
- Yuk Yee Leung
- , Adam C. Naj
- & Li-San Wang
-
Article
| Open AccessMolecular quantitative trait loci in reproductive tissues impact male fertility in cattle
Investigating the genetics of male fertility requires comprehensive genotype and phenotype data. Here, the authors characterize the transcriptional complexity of bovine male reproductive tissues to identify loci associated with male fertility.
- Xena Marie Mapel
- , Naveen Kumar Kadri
- & Hubert Pausch
-
Article
| Open AccessLongitudinal single cell atlas identifies complex temporal relationship between type I interferon response and COVID-19 severity
Single cell transcriptomics can reveal at high resolution the body’s response to infection. Here the authors have applied this technology to a longitudinal SARS-CoV-2 infected cohort and identified gene expression changes that may predict disease severity and reveal the underlying molecular mechanisms.
- Quy Xiao Xuan Lin
- , Deepa Rajagopalan
- & Shyam Prabhakar
-
Article
| Open AccessPROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics
Understanding biological mechanisms requires a thorough exploration of spatiotemporal transcriptional patterns in complex tissues. Here, authors present PROST to quantify spatial gene expression patterns and detect spatial domains using spatial transcriptomics data of varying resolutions.
- Yuchen Liang
- , Guowei Shi
- & Zhonghui Tang
-
Article
| Open AccessBIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data
Subcellular in situ spatial transcriptomics offers the promise to address biological problems that were previously inaccessible but requires accurate cell segmentation to uncover insights. Here, authors present BIDCell, a biologically informed, deep learning-based cell segmentation framework.
- Xiaohang Fu
- , Yingxin Lin
- & Jean Y. H. Yang
-
Article
| Open AccessMENDER: fast and scalable tissue structure identification in spatial omics data
Identifying tissue structure in large-scale spatial omics datasets from multiple slices is challenging. Here, authors present MENDER, an optimisation-free spatial clustering method that can scale to million-level spatial data, enabling efficient analysis of spatial cell atlases.
- Zhiyuan Yuan
-
Article
| Open AccessIntegrative genotyping of cancer and immune phenotypes by long-read sequencing
Single-cell transcriptomics excel in cell subset classification and can be augmented by suitable genotype information. Here the authors devise a long-read sequencing workflow, termed nanoranger, for detection of molecular barcodes from single-cell cDNA and apply this to clonal tracking of acute myeloid leukemia and identification of complex immune phenotypes.
- Livius Penter
- , Mehdi Borji
- & Catherine J. Wu
-
Article
| Open AccessJOINTLY: interpretable joint clustering of single-cell transcriptomes
Batch integration is a critical yet challenging step in many single-cell RNA-seq analysis workflows. Here, authors present JOINTLY, a hybrid linear and non-linear NMF-based algorithm, providing interpretable and robust cell clustering against over-integration.
- Andreas Fønss Møller
- & Jesper Grud Skat Madsen
-
Article
| Open AccessLinRace: cell division history reconstruction of single cells using paired lineage barcode and gene expression data
Inferring lineage trees while incorporating gene expressions and lineage barcodes is a challenging task. Here, authors present LinRace, which infers improved cell lineage trees and ancestral cell states using the proposed asymmetric division model.
- Xinhai Pan
- , Hechen Li
- & Xiuwei Zhang
-
Article
| Open AccessMapping protein states and interactions across the tree of life with co-fractionation mass spectrometry
Co-fractionation mass spectrometry (CF-MS) is a powerful technique for mapping protein interactions under physiological conditions. Here, the authors uniformly re-process 411 CF-MS experiments and carry out meta-analyses of protein abundance, protein-protein interactions, and phosphorylation sites in the resulting resource.
- Michael A. Skinnider
- , Mopelola O. Akinlaja
- & Leonard J. Foster
-
Article
| Open AccessAccurate integration of single-cell DNA and RNA for analyzing intratumor heterogeneity using MaCroDNA
Here, the authors develop MaCroDNA, an algorithm to integrate single-cell DNA and RNA sequencing data from the same tissue. They use MaCroDNA to show—in agreement with previous studies—that copy number changes can predict progression from Barrett’s esophagus to esophageal adenocarcinoma.
- Mohammadamin Edrisi
- , Xiru Huang
- & Luay Nakhleh
-
Article
| Open AccessSTalign: Alignment of spatial transcriptomics data using diffeomorphic metric mapping
Spatial transcriptomics (ST) enables gene expression characterisation within tissue sections, but comparing across sections and technologies remains challenging. Here, authors develop STalign to spatially align ST data and demonstrate applications including aligning to common coordinate frameworks.
- Kalen Clifton
- , Manjari Anant
- & Jean Fan
-
Article
| Open AccessscDREAMER for atlas-level integration of single-cell datasets using deep generative model paired with adversarial classifier
Integration of single-cell datasets is essential to gain a comprehensive understanding of complex biological systems. Here, the authors develop scDREAMER, a deep generative framework for performing unsupervised and supervised atlas-level integration, demonstrating improved bio-conservation and batch-correction.
- Ajita Shree
- , Musale Krushna Pavan
- & Hamim Zafar
-
Article
| Open AccessPaired single-cell multi-omics data integration with Mowgli
Mowgli is a novel paired single-cell multi-omics integration method leveraging matrix factorization and Optimal Transport. In-depth benchmarking demonstrates promising cell clustering results and improved biological interpretability.
- Geert-Jan Huizing
- , Ina Maria Deutschmann
- & Laura Cantini
-
Article
| Open AccessDistinct transcriptomic profiles in children prior to the appearance of type 1 diabetes-linked islet autoantibodies and following enterovirus infection
Although type-1 diabetes has a clear genetic component, not all children who are at risk eventually develop autoimmunity, suggesting the existence of environmental triggers. In this longitudinal transcriptomic study, the authors find that children who later develop autoimmunity have a distinct profile before the appearance of autoantibodies and may have impaired responses to enterovirus infection.
- Jake Lin
- , Elaheh Moradi
- & Matti Nykter
-
Article
| Open AccessIntegrative genome-wide analyses identify novel loci associated with kidney stones and provide insights into its genetic architecture
Kidney stone disease is a complex disorder with high heritability and prevalence. Here, the authors perform a large genome-wide association study meta-analysis, identifying 28 new loci and genes potentially involved in disease etiology.
- Xingjie Hao
- , Zhonghe Shao
- & Chaolong Wang
-
Article
| Open AccessSpatial-linked alignment tool (SLAT) for aligning heterogenous slices
Spatial omics technologies reveal the organisation of cells in various biological systems. Here, authors propose SLAT, a graph-based algorithm for aligning heterogenous data across technologies, modalities and timepoints, enabling spatiotemporal reconstruction of complex developmental processes.
- Chen-Rui Xia
- , Zhi-Jie Cao
- & Ge Gao
-
Article
| Open AccessNIPMAP: niche-phenotype mapping of multiplex histology data by community ecology
Multiplex histology faces the challenge of integrating tissue architecture with the identification of relevant spatial cellular phenotypes. Using community ecology principles, the authors propose NIPMAP, a tool for niche-phenotype mapping of multiplex histology data.
- Anissa El Marrahi
- , Fabio Lipreri
- & Jean Hausser
-
Article
| Open AccessIsoform-resolved transcriptome of the human preimplantation embryo
Human embryo development involves extensive transcriptional remodeling. In this study, the authors apply long- and short-read RNA-Seq to profile the transcriptomes of 73 human preimplantation embryos spanning zygotic to blastocyst stages, identifying tens of thousands of additional isoforms transcribed from both known and unannotated gene loci.
- Denis Torre
- , Nancy J. Francoeur
- & Robert Sebra
-
Article
| Open AccessXMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias
Fine-mapping prioritizes risk variants identified by genome-wide association studies to uncover biological mechanisms underlying complex traits. Here, the authors develop a reliable fine-mapping method (XMAP) by leveraging genetic diversity and accounting for confounding bias.
- Mingxuan Cai
- , Zhiwei Wang
- & Can Yang
-
Article
| Open AccessBenchmarking strategies for cross-species integration of single-cell RNA sequencing data
The growing number of available single-cell RNA-sequencing datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Here, the authors compare different strategies for cross-species integration of these data and offer guidelines for effective integration.
- Yuyao Song
- , Zhichao Miao
- & Irene Papatheodorou
-
Article
| Open AccessSimulation of undiagnosed patients with novel genetic conditions
Rare Mendelian disorders pose a major diagnostic challenge, but evaluation of automated tools that aim to uncover causal genes tools is limited. Here, the authors present a computational pipeline that simulates realistic clinical datasets to address this deficit.
- Emily Alsentzer
- , Samuel G. Finlayson
- & Isaac S. Kohane
-
Article
| Open AccessSpectroscape enables real-time query and visualization of a spectral archive in proteomics
Proteomics data repositories are deluged with data that is scarcely reused. Here, the authors developed Spectroscape, an interactive web-based tool for efficient similarity search of a query spectrum against a repository-scale spectral archive, and real-time visualization of its neighborhood.
- Long Wu
- , Ayman Hoque
- & Henry Lam
-
Article
| Open AccessMultifaceted analysis of cross-tissue transcriptomes reveals phenotype–endotype associations in atopic dermatitis
Atopic dermatitis is an inflammatory skin disease featuring systemic involvement. Here authors show that the two major clinical manifestations of the disease, erythema and papulation, are distinguished by differential interplay between local skin and systemic immunity, uncovered by integrated transcriptomics.
- Aiko Sekita
- , Hiroshi Kawasaki
- & Haruhiko Koseki
-
Article
| Open AccessscBridge embraces cell heterogeneity in single-cell RNA-seq and ATAC-seq data integration
Multi-omics data integration can be challenging in the event of cell heterogeneity. Here, the authors present scBridge, a method that exploits heterogeneous omics differences, to progressively integrate cells and narrows omics gap, leading to promising integration and label transfer results.
- Yunfan Li
- , Dan Zhang
- & Xi Peng
-
Article
| Open AccessDivergent single cell transcriptome and epigenome alterations in ALS and FTD patients with C9orf72 mutation
Non-coding repeat expansion in the C9ORF72 gene is the most frequent cause of ALS and frontotemporal dementia. Here, the authors performed single cell analyses of gene expression and epigenetic regulation in these patients’ brains and emphasized the role of astrocytes and neurons in neurodegeneration.
- Junhao Li
- , Manoj K. Jaiswal
- & Stella Dracheva
-
Article
| Open AccessSingle cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A
The mechanism and disease-relevance of pancreatic b-cell heterogeneity remains elusive. Here the authors show that variable HNF1A-FXYD2 activity drives single b-cell heterogeneity at transcriptomic, epigenomic, and electro-physiological levels, which strongly mark the progression of type 2 diabetes.
- Chen Weng
- , Anniya Gu
- & Yan Li
-
Article
| Open AccessDemonstrating paths for unlocking the value of cloud genomics through cross cohort analysis
The emergence of large-scale genomics projects has led to genetic studies across cohorts. Here, the authors conduct genome-wide association studies meta-analyzing in trusted research environments or pooling together and find similar, but not identical results.
- Nicole Deflaux
- , Margaret Sunitha Selvaraj
- & Alexander G. Bick
-
Article
| Open AccessProjecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection
Many expression deconvolution approaches have been developed to estimate % RNA contributions of diverse cell types to mixed RNA measurements. Here, the authors have developed a complementary approach called scProjection to recover cell type-specific expression profiles from mixed RNA measurements.
- Nelson Johansen
- , Hongru Hu
- & Gerald Quon
-
Article
| Open AccessGenetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits
Many genetic variants have been associated with human traits, but the mechanism is often unknown. Here, the authors integrate local and distal genetic associations with multi-omics datasets to provide a roadmap to understand the underlying mechanisms of GWAS variants on complex traits.
- Andrew A. Brown
- , Juan J. Fernandez-Tajes
- & Ana Viñuela
-
Article
| Open AccessRobust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering
Multiplexed imaging studies are typically focused on cell-level phenotypes. Here, the authors propose Pixie, a cross-platform and open-source pipeline that achieves robust and quantitative annotation of both pixel-level and cell-level features in multiplexed imaging data.
- Candace C. Liu
- , Noah F. Greenwald
- & Michael Angelo
-
Article
| Open AccessThree-dimensional molecular architecture of mouse organogenesis
Qu et al. present a detailed three-dimensional spatial transcriptome atlas of all major organs in the mouse embryo at E13.5, providing a better understanding of organ development and cellular interactions during mammalian development.
- Fangfang Qu
- , Wenjia Li
- & Guangdun Peng
-
Article
| Open AccessGuided construction of single cell reference for human and mouse lung
Accurate cell-type identification is vital for single-cell analysis. Here, the authors develop a computational pipeline called “LungMAP CellRef” for efficient, automated cell-type annotation of normal and disease human and mouse lung single-cell datasets.
- Minzhe Guo
- , Michael P. Morley
- & Yan Xu
-
Article
| Open AccessAtlas-scale single-cell multi-sample multi-condition data integration using scMerge2
Recent advances in multi-condition single-cell multi-cohort studies enable exploration of diverse cell states. Here, authors present scMerge2, an algorithm that allows integration of a large COVID-19 data collection with over five million cells to uncover distinct signatures of disease progression.
- Yingxin Lin
- , Yue Cao
- & Jean Y. H. Yang
-
Article
| Open AccessMulti-batch single-cell comparative atlas construction by deep learning disentanglement
Comparing single-cell RNA-seq and ATAC-seq data from multiple batches is challenging due to technical artifacts. Here, the authors propose a method that disentangles technical and biological effects, facilitating batch-confounded chromatin and gene expression state discovery and enhancing the analysis of perturbation effects on cell populations.
- Allen W. Lynch
- , Myles Brown
- & Clifford A. Meyer
-
Article
| Open AccessMOBILE pipeline enables identification of context-specific networks and regulatory mechanisms
A problem in network biology is identification of context-specific networks. Here the authors report Multi-Omics Binary Integration via Lasso Ensembles (MOBILE) to nominate molecular features associated with cellular phenotypes and pathways, and use this to assess interferon-γ regulated PD-L1 expression.
- Cemal Erdem
- , Sean M. Gross
- & Marc R. Birtwistle
-
Article
| Open AccessPacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma
Rapid and effective molecular subtyping of pancreatic adenocarcinoma (PDAC) is important for prognosis and treatment. Here, the authors develop PACpAInt, a deep learning model for PDAC molecular subtyping from whole-slide histological imaging that enables the analysis of heterogeneity and prognostic predictions.
- Charlie Saillard
- , Flore Delecourt
- & Jerome Cros
-
Article
| Open AccessInference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets
Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Here, the authors present single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer cell type-specific GRN dynamics from scRNA-seq and scATAC-seq datasets collected for diverse cell fate specification trajectories.
- Shilu Zhang
- , Saptarshi Pyne
- & Sushmita Roy
-
Article
| Open AccessCandida expansion in the gut of lung cancer patients associates with an ecological signature that supports growth under dysbiotic conditions
Here, Seelbinder et al. show high Candida levels in cancer patients’ stool to correlate with greater metabolically flexibility but less robust bacterial communities and, combined with machine learning models to predict Candida levels from bacterial data, suggest that lactate producing bacteria may fuel Candida overgrowth in the gut during dysbiosis.
- Bastian Seelbinder
- , Zoltan Lohinai
- & Gianni Panagiotou
-
Article
| Open AccessMetaTiME integrates single-cell gene expression to characterize the meta-components of the tumor immune microenvironment
Integration and comparison of multiple single cell sequencing datasets can be used to compare different studies. Here the authors propose MetaTiME which compares the gene expression of single cells from the tumour microenvironment across different tumours and uses transportable labels and metacomponents to annotate cell types and states.
- Yi Zhang
- , Guanjue Xiang
- & Clifford A. Meyer