High-dimensional generalized median adaptive lasso with application to omics data
Brief Bioinform. 2024 Jan 22;25(2):bbae059. doi: 10.1093/bib/bbae059.ABSTRACTRecently, there has been a growing interest in variable selection for causal inference within the context of high-dimensional data. However, when the outcome exhibits a skewed distribution, ensuring the accuracy of variable selection and causal effect estimation might be challenging. Here, we introduce the generalized median adaptive lasso (GMAL) for covariate selection to achieve an accurate estimation of causal effect even when the outcome follows skewed distributions. A distinctive feature of our proposed method is that we utilize a linear medi...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Yahang Liu Qian Gao Kecheng Wei Chen Huang Ce Wang Yongfu Yu Guoyou Qin Tong Wang Source Type: research

Exploring miRNA-target gene pair detection in disease with coRmiT
Brief Bioinform. 2024 Jan 22;25(2):bbae060. doi: 10.1093/bib/bbae060.ABSTRACTA wide range of approaches can be used to detect micro RNA (miRNA)-target gene pairs (mTPs) from expression data, differing in the ways the gene and miRNA expression profiles are calculated, combined and correlated. However, there is no clear consensus on which is the best approach across all datasets. Here, we have implemented multiple strategies and applied them to three distinct rare disease datasets that comprise smallRNA-Seq and RNA-Seq data obtained from the same samples, obtaining mTPs related to the disease pathology. All datasets were pre...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Jose Cordoba-Caballero James R Perkins Federico Garc ía-Criado Diana Gallego Alicia Navarro-S ánchez Mireia Moreno-Estell és Concepci ón Garcés Fernando Bonet Carlos Rom á-Mateo Rocio Toro Bel én Perez Pascual Sanz Matthias Kohl Elena Rojano Pedro Source Type: research

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality
Brief Bioinform. 2024 Jan 22;25(2):bbae064. doi: 10.1093/bib/bbae064.ABSTRACTRNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics an...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Clement Bernard Guillaume Postic Sahar Ghannay Fariza Tahi Source Type: research

Benchmarking enrichment analysis methods with the disease pathway network
Brief Bioinform. 2024 Jan 22;25(2):bbae069. doi: 10.1093/bib/bbae069.ABSTRACTEnrichment analysis (EA) is a common approach to gain functional insights from genome-scale experiments. As a consequence, a large number of EA methods have been developed, yet it is unclear from previous studies which method is the best for a given dataset. The main issues with previous benchmarks include the complexity of correctly assigning true pathways to a test dataset, and lack of generality of the evaluation metrics, for which the rank of a single target pathway is commonly used. We here provide a generalized EA benchmark and apply it to t...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Davide Buzzao Miguel Castresana-Aguirre Dimitri Guala Erik L L Sonnhammer Source Type: research

Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function
CONCLUSIONS: Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.PMID:38436562 | DOI:10.1093/bib/bbae070 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Chuyu Pan Bolun Cheng Xiaoyue Qin Shiqiang Cheng Li Liu Xuena Yang Peilin Meng Na Zhang Dan He Qingqing Cai Wenming Wei Jingni Hui Yan Wen Yumeng Jia Huan Liu Feng Zhang Source Type: research

scDOT: enhancing single-cell RNA-Seq data annotation and uncovering novel cell types through multi-reference integration
Brief Bioinform. 2024 Jan 22;25(2):bbae072. doi: 10.1093/bib/bbae072.ABSTRACTThe proliferation of single-cell RNA-seq data has greatly enhanced our ability to comprehend the intricate nature of diverse tissues. However, accurately annotating cell types in such data, especially when handling multiple reference datasets and identifying novel cell types, remains a significant challenge. To address these issues, we introduce Single Cell annotation based on Distance metric learning and Optimal Transport (scDOT), an innovative cell-type annotation method adept at integrating multiple reference datasets and uncovering previously ...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Yi-Xuan Xiong Xiao-Fei Zhang Source Type: research

Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression
Brief Bioinform. 2024 Jan 22;25(2):bbae052. doi: 10.1093/bib/bbae052.ABSTRACTSpatial transcriptomics technologies have shed light on the complexities of tissue structures by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods, especially those utilized in platforms like Visium, often relinquish spatial details owing to intrinsic resolution limitations. In response, we introduce TransformerST, an innovative, unsupervised model anchored in the Transformer architecture, which operates independently of references, thereby ensuring cost-efficiency by circumventing the need for single-cell RNA sequenci...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Chongyue Zhao Zhongli Xu Xinjun Wang Shiyue Tao William A MacDonald Kun He Amanda C Poholek Kong Chen Heng Huang Wei Chen Source Type: research

High-dimensional generalized median adaptive lasso with application to omics data
Brief Bioinform. 2024 Jan 22;25(2):bbae059. doi: 10.1093/bib/bbae059.ABSTRACTRecently, there has been a growing interest in variable selection for causal inference within the context of high-dimensional data. However, when the outcome exhibits a skewed distribution, ensuring the accuracy of variable selection and causal effect estimation might be challenging. Here, we introduce the generalized median adaptive lasso (GMAL) for covariate selection to achieve an accurate estimation of causal effect even when the outcome follows skewed distributions. A distinctive feature of our proposed method is that we utilize a linear medi...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Yahang Liu Qian Gao Kecheng Wei Chen Huang Ce Wang Yongfu Yu Guoyou Qin Tong Wang Source Type: research

Exploring miRNA-target gene pair detection in disease with coRmiT
Brief Bioinform. 2024 Jan 22;25(2):bbae060. doi: 10.1093/bib/bbae060.ABSTRACTA wide range of approaches can be used to detect micro RNA (miRNA)-target gene pairs (mTPs) from expression data, differing in the ways the gene and miRNA expression profiles are calculated, combined and correlated. However, there is no clear consensus on which is the best approach across all datasets. Here, we have implemented multiple strategies and applied them to three distinct rare disease datasets that comprise smallRNA-Seq and RNA-Seq data obtained from the same samples, obtaining mTPs related to the disease pathology. All datasets were pre...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Jose Cordoba-Caballero James R Perkins Federico Garc ía-Criado Diana Gallego Alicia Navarro-S ánchez Mireia Moreno-Estell és Concepci ón Garcés Fernando Bonet Carlos Rom á-Mateo Rocio Toro Bel én Perez Pascual Sanz Matthias Kohl Elena Rojano Pedro Source Type: research

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality
Brief Bioinform. 2024 Jan 22;25(2):bbae064. doi: 10.1093/bib/bbae064.ABSTRACTRNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics an...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Clement Bernard Guillaume Postic Sahar Ghannay Fariza Tahi Source Type: research

Benchmarking enrichment analysis methods with the disease pathway network
Brief Bioinform. 2024 Jan 22;25(2):bbae069. doi: 10.1093/bib/bbae069.ABSTRACTEnrichment analysis (EA) is a common approach to gain functional insights from genome-scale experiments. As a consequence, a large number of EA methods have been developed, yet it is unclear from previous studies which method is the best for a given dataset. The main issues with previous benchmarks include the complexity of correctly assigning true pathways to a test dataset, and lack of generality of the evaluation metrics, for which the rank of a single target pathway is commonly used. We here provide a generalized EA benchmark and apply it to t...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Davide Buzzao Miguel Castresana-Aguirre Dimitri Guala Erik L L Sonnhammer Source Type: research

Enhanced polygenic risk score incorporating gene-environment interaction suggests the association of major depressive disorder with cardiac and lung function
CONCLUSIONS: Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene-environment interactions in PRS-based studies.PMID:38436562 | DOI:10.1093/bib/bbae070 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Chuyu Pan Bolun Cheng Xiaoyue Qin Shiqiang Cheng Li Liu Xuena Yang Peilin Meng Na Zhang Dan He Qingqing Cai Wenming Wei Jingni Hui Yan Wen Yumeng Jia Huan Liu Feng Zhang Source Type: research

scDOT: enhancing single-cell RNA-Seq data annotation and uncovering novel cell types through multi-reference integration
Brief Bioinform. 2024 Jan 22;25(2):bbae072. doi: 10.1093/bib/bbae072.ABSTRACTThe proliferation of single-cell RNA-seq data has greatly enhanced our ability to comprehend the intricate nature of diverse tissues. However, accurately annotating cell types in such data, especially when handling multiple reference datasets and identifying novel cell types, remains a significant challenge. To address these issues, we introduce Single Cell annotation based on Distance metric learning and Optimal Transport (scDOT), an innovative cell-type annotation method adept at integrating multiple reference datasets and uncovering previously ...
Source: Briefings in Bioinformatics - March 4, 2024 Category: Bioinformatics Authors: Yi-Xuan Xiong Xiao-Fei Zhang Source Type: research

TransGCN: a semi-supervised graph convolution network-based framework to infer protein translocations in spatio-temporal proteomics
Brief Bioinform. 2024 Jan 22;25(2):bbae055. doi: 10.1093/bib/bbae055.ABSTRACTProtein subcellular localization (PSL) is very important in order to understand its functions, and its movement between subcellular niches within cells plays fundamental roles in biological process regulation. Mass spectrometry-based spatio-temporal proteomics technologies can help provide new insights of protein translocation, but bring the challenge in identifying reliable protein translocation events due to the noise interference and insufficient data mining. We propose a semi-supervised graph convolution network (GCN)-based framework termed Tr...
Source: Briefings in Bioinformatics - March 1, 2024 Category: Bioinformatics Authors: Bing Wang Xiangzheng Zhang Xudong Han Bingjie Hao Yan Li Xuejiang Guo Source Type: research

Elevated incidence of somatic mutations at prevalent genetic sites
Brief Bioinform. 2024 Jan 22;25(2):bbae065. doi: 10.1093/bib/bbae065.ABSTRACTThe common loci represent a distinct set of the human genome sites that harbor genetic variants found in at least 1% of the population. Small somatic mutations occur at the common loci and non-common loci, i.e. csmVariants and ncsmVariants, are presumed with similar probabilities. However, our work revealed that within the coding region, common loci constituted only 1.03% of all loci, yet they accounted for 5.14% of TCGA somatic mutations. Furthermore, the small somatic mutation incidence rate at these common loci was 2.7 times that observed in th...
Source: Briefings in Bioinformatics - March 1, 2024 Category: Bioinformatics Authors: Mengyao Wang Shuai Cheng Li Bairong Shen Source Type: research