Cell Reports Methods最新文献_第3页

Robust and adaptive non-parametric tests for detecting general distributional shifts in gene expression. 用于检测基因表达一般分布变化的鲁棒和自适应非参数测试。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-09-02 DOI: 10.1016/j.crmeth.2025.101147

Fanding Zhou, Alan J Aw, Dan D Erdmann-Pham, Jonathan Fischer, Yun S Song

{"title":"Robust and adaptive non-parametric tests for detecting general distributional shifts in gene expression.","authors":"Fanding Zhou, Alan J Aw, Dan D Erdmann-Pham, Jonathan Fischer, Yun S Song","doi":"10.1016/j.crmeth.2025.101147","DOIUrl":"10.1016/j.crmeth.2025.101147","url":null,"abstract":"Differential expression analysis is crucial in genomics, yet most methods focus only on mean shifts. Variance shifts in gene expression-especially in cellular signaling and aging-are increasingly recognized as being biologically important. We present QRscore (quantile rank score), a general non-parametric framework that extends the Mann-Whitney test to detect both mean and variance shifts through model-informed weights derived from negative binomial (NB) and zero-inflated NB (ZINB) distributions. QRscore offers high statistical power with false discovery rate (FDR) control, surpassing existing methods in detecting both types of distributional changes. When applied to bulk RNA sequencing (RNA-seq) data from Genotype-Tissue Expression (GTEx), QRscore uncovers numerous genes with dispersion shifts that are missed by mean-shift analysis. In pseudo-bulked single-cell RNA-seq data from the Asian Immune Diversity Atlas (AIDA), QRscore further reveals cell-type-specific variance shifts across age groups that remain undetectable in bulk analyses. QRscore augments the genome bioinformatics toolkit by offering a powerful and flexible approach for differential expression analysis.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101147"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144993515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-modal image analysis for large-scale cancer tissue studies within IMMUcan. IMMUcan中大规模癌症组织研究的多模态图像分析。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-09-09 DOI: 10.1016/j.crmeth.2025.101170

Nils Eling, Julien Dorier, Sylvie Rusakiewicz, Robin Liechti, Preethi Devanand, Michelle Daniel, Jonas Windhager, Bruno Palau Fernandez, Sophie Déglise, Lucie Despland, Abdelkader Benyagoub, Marcin Możejko, Dawid Uchal, Ewa Szczurek, Alexander Loboda, Daaf Sandkuijl, Nikesh Parsotam, Henoch S Hong, Marie Morfouace, Nicolas Guex, George Coukos, Bernd Bodenmiller, Stephanie Tissot, Daniel Schulz

{"title":"Multi-modal image analysis for large-scale cancer tissue studies within IMMUcan.","authors":"Nils Eling, Julien Dorier, Sylvie Rusakiewicz, Robin Liechti, Preethi Devanand, Michelle Daniel, Jonas Windhager, Bruno Palau Fernandez, Sophie Déglise, Lucie Despland, Abdelkader Benyagoub, Marcin Możejko, Dawid Uchal, Ewa Szczurek, Alexander Loboda, Daaf Sandkuijl, Nikesh Parsotam, Henoch S Hong, Marie Morfouace, Nicolas Guex, George Coukos, Bernd Bodenmiller, Stephanie Tissot, Daniel Schulz","doi":"10.1016/j.crmeth.2025.101170","DOIUrl":"10.1016/j.crmeth.2025.101170","url":null,"abstract":"In cancer research, multiplexed imaging allows detailed characterization of the tumor microenvironment (TME) and its link to patient prognosis. The integrated immunoprofiling of large adaptive cancer patient cohorts (IMMUcan) consortium collects multi-modal imaging data from thousands of patients with cancer to perform broad molecular and cellular spatial profiling. Here, we describe and compare two workflows for multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) developed within IMMUcan to enable the generation of standardized data for cancer tissue analysis. The IFQuant software supports web-based, user-friendly, and reproducible analysis of mIF data. High sample throughput for IMC is achieved by optimizing experimental protocols, developing a robotic arm for automated slide loading, and classification-based cell typing. Using our manually labeled single-cell data, we show that tree-based methods outperform other cell-phenotyping tools. These pipelines form the basis for multiplexed image analysis within IMMUcan, and we summarize our learnings from 5 years of development and optimization.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101170"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A structural machine learning approach for rapid prediction of thermodynamically destabilizing tyrosine phosphorylations. 一种用于快速预测热力学不稳定酪氨酸磷酸化的结构机器学习方法。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 DOI: 10.1016/j.crmeth.2025.101169

Jaie Woodard, Zhengqing Liu, Atena Malemir Chegini, Jian Tian, Rupa Bhowmick, Subramaniam Pennathur, Alireza Mashaghi, Jeffrey R Brender, Sriram Chandrasekaran

{"title":"A structural machine learning approach for rapid prediction of thermodynamically destabilizing tyrosine phosphorylations.","authors":"Jaie Woodard, Zhengqing Liu, Atena Malemir Chegini, Jian Tian, Rupa Bhowmick, Subramaniam Pennathur, Alireza Mashaghi, Jeffrey R Brender, Sriram Chandrasekaran","doi":"10.1016/j.crmeth.2025.101169","DOIUrl":"10.1016/j.crmeth.2025.101169","url":null,"abstract":"Tyrosine phosphorylations are a prominent characteristic of numerous diseases, yet it is challenging to identify potentially (dys)functional phosphorylations among thousands of phospho-proteins. Here, we propose a machine learning method to predict the thermodynamic stability change resulting from tyrosine phosphorylation. Our approach, based on the prediction of phosphomimetic stability (ΔΔG) from structural features, strongly correlates with experimental phosphorylation stability and mutational scanning cDNA proteolysis data (R = 0.55-0.67). We apply our approach to predict the potential destabilizing effects of all 384,858 tyrosine residues from the Alphafold2 database, the PhosphoSitePlus database, and on a pan-cancer phosphoproteomics dataset with 11 cancer subtypes. We predict destabilizing phosphorylations in both oncogenes and tumor suppressors, and ΔΔG values and local protein circuit topology features are able to distinguish phospho-proteins that are known to be dysregulated in cancer. Our approach can enable rapid screening of destabilizing phosphorylations and phosphomimetic mutations.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"5 9","pages":"101169"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145076185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced detection of RNA modifications in Escherichia coli utilizing direct RNA sequencing. 利用直接RNA测序增强对大肠杆菌RNA修饰的检测。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-09-09 DOI: 10.1016/j.crmeth.2025.101168

Zhihao Guo, Yanwen Shao, Lu Tan, Beifang Lu, Xin Deng, Sheng Chen, Runsheng Li

引用次数: 0

Profiling mouse behavior with computational tools to assess age-dependent differences in associative learning. 用计算工具分析小鼠行为以评估联想学习的年龄依赖性差异。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-08-28 DOI: 10.1016/j.crmeth.2025.101144

Marc Canela-Grimau, Julia S Pinho, Arnau Busquets-Garcia

{"title":"Profiling mouse behavior with computational tools to assess age-dependent differences in associative learning.","authors":"Marc Canela-Grimau, Julia S Pinho, Arnau Busquets-Garcia","doi":"10.1016/j.crmeth.2025.101144","DOIUrl":"10.1016/j.crmeth.2025.101144","url":null,"abstract":"Second-order conditioning (SOC) enables animals to form associations between stimuli without direct reinforcement. In this study, we present a behavioral analysis pipeline that combines a light-tone SOC paradigm in mice with tools such as DeepLabCut, Keypoint-MoSeq, and DeepOF to evaluate responses across sex and age. Our results show that responses to the second-order stimulus (CS2) specifically stem from its association with the first-order stimulus (CS1). While CS1 triggers behavioral syllables related to immobility, CS2 elicits distinct behavioral responses, including immobility- and escape-related actions, suggesting SOC reorganizes, rather than replicates, first-order responses. These data-driven insights surpass the resolution of simple traditional measures (e.g., immobility). Lastly, we identified age-related deficits: older mice maintained responses to CS1 but exhibited impaired responses to CS2, regardless of sex. These findings uncover the complexity of SOC, its susceptibility to aging, and the value of data-driven tools in behavioral neuroscience.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101144"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144971554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultrastructural analysis of synapses after induction of spike-timing-dependent plasticity. 针刺时间依赖性可塑性诱导后突触超微结构分析。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-08-25 DOI: 10.1016/j.crmeth.2025.101142

Rui Wang, Michaela Schweizer, Margarita Anisimova, Christine E Gee, Thomas G Oertner

{"title":"Ultrastructural analysis of synapses after induction of spike-timing-dependent plasticity.","authors":"Rui Wang, Michaela Schweizer, Margarita Anisimova, Christine E Gee, Thomas G Oertner","doi":"10.1016/j.crmeth.2025.101142","DOIUrl":"10.1016/j.crmeth.2025.101142","url":null,"abstract":"Repeated sequential activation of connected neurons causes lasting changes in synaptic strength, a process known as spike-timing-dependent plasticity (STDP). Recently, sequential spike patterns have been induced without electrodes, using two spectrally separated channelrhodopsins. However, due to the difficulty of labeling and localizing the few connecting synapses between the stimulated pre- and postsynaptic neurons (∼1-5 per neuron pair), ultrastructural analysis after STDP has not been reported. Here, we optogenetically induce STDP at CA3-CA1 hippocampal synapses and identify stimulated boutons and spines in CA1 using transmission electron microscopy (TEM). Presynaptic CA3 neurons express vesicle-targeted horseradish peroxidase, cre recombinase, and cre-dependent ChrimsonR, a red light-activatable channelrhodopsin. Postsynaptic neurons express violet light-activatable CheRiff and dAPEX2, an enhanced ascorbate peroxidase. In TEM, presynaptic boutons and postsynaptic spines are readily identifiable with well-preserved ultrastructural features. Our labeling strategy allows ultrastructural analysis of optogenetically manipulated neurons and their synapses.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101142"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144971827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toward owner governance in genomic data privacy with Governome. 用Governome研究基因组数据隐私中的所有者治理。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-09-09 DOI: 10.1016/j.crmeth.2025.101171

Jingcheng Zhang, Yekai Zhou, Yingxuan Ren, Man Ho Au, Ka-Ho Chow, Lei Chen, Yanmin Zhao, Junhao Su, Ruibang Luo

{"title":"Toward owner governance in genomic data privacy with Governome.","authors":"Jingcheng Zhang, Yekai Zhou, Yingxuan Ren, Man Ho Au, Ka-Ho Chow, Lei Chen, Yanmin Zhao, Junhao Su, Ruibang Luo","doi":"10.1016/j.crmeth.2025.101171","DOIUrl":"10.1016/j.crmeth.2025.101171","url":null,"abstract":"Advancements in sequencing technologies grant individuals unprecedented access to their genomic data. However, existing data management systems or protocols are inadequate in privacy protection, limiting individuals' control over their genomic information, hindering data sharing, and posing challenges for biomedical research. Therefore, demand exists for an owner-governed system fulfilling owner authority, life cycle data encryption, and verifiability simultaneously. Here, we realized Governome, an owner-governed data management system empowering individuals with real-time control over their genomic data. Governome leverages a blockchain to manage transactions and permissions, granting data owners dynamic permission management with full transparency on data usage. It uses homomorphic encryption and zero-knowledge proofs to enable genomic data storage and computation in an encrypted and verifiable form throughout its life cycle. Governome can support versatile genomic applications. We implemented and tested individual variant query, cohort study, genome-wide association study (GWAS) analysis, and forensics on 2,504 1000 Genomes Project (1kGP) genomes, demonstrating its robustness and scalability. Governome is open-source at https://github.com/HKU-BAL/Governome.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101171"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatial dissimilarity analysis in single-cell transcriptomics. 单细胞转录组学的空间差异性分析。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-08-20 DOI: 10.1016/j.crmeth.2025.101141

Quan Shi, Karsten Kristiansen

引用次数: 0

Feature-driven whole-tissue imaging with subcellular resolution. 亚细胞分辨率特征驱动的全组织成像。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-09-02 DOI: 10.1016/j.crmeth.2025.101148

Jinlong Lin, Zach Marin, Xiaoding Wang, Hazel M Borges, Qionghua Shen, Pierre-Emmanuel Y N'Guetta, Xuemei Luo, Baylee A Porter, Yuanyuan Xue, Md Torikul Islam, Tai Ngo, Doreen Idonije, Seweryn Gałecki, Arin B Aurora, Hu Zhao, Suzanne D Conzen, Sean J Morrison, Shuang Liang, Zhenyu Zhong, Lori L O'Brien, Kevin M Dean

{"title":"Feature-driven whole-tissue imaging with subcellular resolution.","authors":"Jinlong Lin, Zach Marin, Xiaoding Wang, Hazel M Borges, Qionghua Shen, Pierre-Emmanuel Y N'Guetta, Xuemei Luo, Baylee A Porter, Yuanyuan Xue, Md Torikul Islam, Tai Ngo, Doreen Idonije, Seweryn Gałecki, Arin B Aurora, Hu Zhao, Suzanne D Conzen, Sean J Morrison, Shuang Liang, Zhenyu Zhong, Lori L O'Brien, Kevin M Dean","doi":"10.1016/j.crmeth.2025.101148","DOIUrl":"10.1016/j.crmeth.2025.101148","url":null,"abstract":"Existing microscopy approaches are often unable to identify and contextualize rare but biologically meaningful events due to limitations associated with simultaneously achieving both high-resolution imaging and a cm-scale field of view. Here, we present multiscale cleared tissue axially swept light-sheet microscopy (MCT-ASLM), a platform combining cm-scale imaging with targeted high-resolution interrogation of intact tissues in human-guided or autonomous modes. Capable of capturing fields of view up to 21 mm at micron-scale resolution, MCT-ASLM can seamlessly transition to a targeted imaging mode with an isotropic resolution that approaches ∼300 nm. This versatility enables detailed studies of hierarchical organization and spatially complex processes, including mapping neuronal circuits in rat brains, visualizing glomerular innervation in mouse kidneys, and examining metastatic tumor microenvironments. By bridging subcellular- to tissue-level scales, MCT-ASLM offers a powerful method for unraveling how local events contribute to global biological phenomena.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101148"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144993393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A modular, adaptable, and accessible implant kit for chronic electrophysiological recordings in rats. 大鼠慢性电生理记录的模块化，适应性强，易于使用的植入试剂盒。

IF 4.5

Cell Reports Methods Pub Date : 2025-09-15 Epub Date: 2025-09-02 DOI: 10.1016/j.crmeth.2025.101146

Raquel J Ibáñez Alcalá, Andrea Y Macias, Cory N Heaton, Ricardo Sosa Jurado, Alexis A Salcido, Neftali F Reyes, Serina A Batson, Luis D Davila, Dirk W Beck, Lara I Rakocevic, Atanu Giri, Kenichiro Negishi, Sabrina M Drammis, Ki A Goosens, Travis M Moschak, Alexander Friedman

{"title":"A modular, adaptable, and accessible implant kit for chronic electrophysiological recordings in rats.","authors":"Raquel J Ibáñez Alcalá, Andrea Y Macias, Cory N Heaton, Ricardo Sosa Jurado, Alexis A Salcido, Neftali F Reyes, Serina A Batson, Luis D Davila, Dirk W Beck, Lara I Rakocevic, Atanu Giri, Kenichiro Negishi, Sabrina M Drammis, Ki A Goosens, Travis M Moschak, Alexander Friedman","doi":"10.1016/j.crmeth.2025.101146","DOIUrl":"10.1016/j.crmeth.2025.101146","url":null,"abstract":"Electrophysiological implants enable exploration of the relationship between neuronal activity and behavior. These technologies evolve rapidly, with multiple iterations of recording systems developed and utilized. Chronic implants must address a litany of complications, including retention of high signal-to-noise ratio in probes and the ability to withstand excess force over the experimental period. To overcome these issues, we designed a chronic implant for rats. Our comprehensive protocol optimizes the entire implant process, from assembling and testing the probes (Neuropixels) to implantation. In addition to addressing the complications previously mentioned, our implant can vertically adjust probes with micron precision and is constructed using modular components, allowing it to be easily modified for various research contexts, electrophysiological recording systems, headstages, and probe types.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101146"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144993815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0