Bioinformatics advances最新文献

SpaFlow: a Nextflow pipeline for QC and clustering of MxIF datasets.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-14 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf032

Brenna C Novotny, Raymond Moore, Lynn Langit, David Haley, Rachel L Maus, Jun Jiang, Caitlin Ward, Ray Guo, Ellen L Goode, Svetomir N Markovic, Chen Wang

{"title":"SpaFlow: a Nextflow pipeline for QC and clustering of MxIF datasets.","authors":"Brenna C Novotny, Raymond Moore, Lynn Langit, David Haley, Rachel L Maus, Jun Jiang, Caitlin Ward, Ray Guo, Ellen L Goode, Svetomir N Markovic, Chen Wang","doi":"10.1093/bioadv/vbaf032","DOIUrl":"10.1093/bioadv/vbaf032","url":null,"abstract":"Motivation: Multiplex immunofluorescence (MxIF) enables the quantification of multiple protein markers at a single-cell level while preserving spatial information, offering a powerful tool for studying tissue microenvironments. However, the flexibility in MxIF panel design poses challenges in standardizing cell phenotyping.Results: We present SpaFlow, an efficient, customizable pipeline for unsupervised clustering and classification of MxIF data, implemented using Nextflow. SpaFlow performs quality control, clustering, and postclustering analysis on segmented and quantified MxIF data, facilitating reproducible and scalable analyses across various computing platforms. The SpaFlow pipeline integrates three clustering and classification packages-Seurat, SCIMAP, and CELESTA-each providing unique methodologies for identifying cell types based on phenotypic markers. A novel \"meta-clustering\" approach condenses clusters across multiple regions of interest into common meta-clusters, streamlining the cell-type identification process in large datasets. SpaFlow's robust quality control steps, including signal summation and cell density filtering, mitigate artifacts that may impact clustering accuracy. We demonstrate the utility of SpaFlow in a case study involving 297 ovarian tumor cores, where SpaFlow successfully identified biologically meaningful cell populations, including tumor-infiltrating lymphocytes, efficiently and rapidly. Additionally, SpaFlow's reproducibility is validated using serial tonsil sections, confirming its capability to consistently identify distinctive cell populations across matched ROIs.Availability and implementation: SpaFlow is freely available with detailed documentation and examples at https://github.com/dimi-lab/SpaFlow.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf032"},"PeriodicalIF":2.4,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11879158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

easyEWAS: a flexible and user-friendly R package for epigenome-wide association study. easyEWAS：用于全表观基因组关联研究的灵活且用户友好的 R 软件包。

IF 2.4

Bioinformatics advances Pub Date : 2025-02-13 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf026

Yuting Wang, Meijie Jiang, Siyuan Niu, Xu Gao

{"title":"easyEWAS: a flexible and user-friendly R package for epigenome-wide association study.","authors":"Yuting Wang, Meijie Jiang, Siyuan Niu, Xu Gao","doi":"10.1093/bioadv/vbaf026","DOIUrl":"10.1093/bioadv/vbaf026","url":null,"abstract":"Motivation: Rapid advancements in high-throughput sequencing technologies especially the Illumina DNA methylation Beadchip greatly fuelled the surge in epigenome-wide association study (EWAS), providing crucial insights into intrinsic DNA methylation modifications associated with environmental exposure, diseases, and health traits. However, current tools are complex and less user-friendly to accommodate appropriate EWAS designs and make downstream analyses and result interpretations complicated, especially for clinicians and public health professionals with limited bioinformatic skills.Results: We integrated the current state-of-the-art EWAS analysis methods and tools to develop a flexible and user-friendly R package easyEWAS for conducting DNA methylation-based research using Illumina DNA methylation Beadchips. With easyEWAS, we provide a battery of statistical methods to support differential methylation position analysis across various scenarios, as well as differential methylation region analysis based on the DMRcate method. To facilitate result interpretation, we provide comprehensive functional annotation and result visualization functionalities. Additionally, a bootstrap-based internal validation was incorporated into easyEWAS to ensure the robustness of EWAS results. Evaluation in asthma patients as the example demonstrated that easyEWAS could simplify and streamline the conduction of EWAS and corresponding downstream analyses, thus effectively advancing DNA methylation research in public health and clinical settings.Availability and implementation: easyEWAS is implemented as an R package and is available at https://github.com/ytwangZero/easyEWAS.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf026"},"PeriodicalIF":2.4,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11878637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CRIBAR: a fast and flexible sgRNA design tool for CRISPR imaging.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-12 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf022

Xiaoli Chen, Md Mahfuzur Rahaman, Ardalan Naseri, Shaojie Zhang

引用次数: 0

PPIXpress and PPICompare webservers infer condition-specific and differential PPI networks.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-11 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf003

Hoang Thu Trang Do, Sudharshini Thangamurugan, Volkhard Helms

{"title":"PPIXpress and PPICompare webservers infer condition-specific and differential PPI networks.","authors":"Hoang Thu Trang Do, Sudharshini Thangamurugan, Volkhard Helms","doi":"10.1093/bioadv/vbaf003","DOIUrl":"10.1093/bioadv/vbaf003","url":null,"abstract":"Summary: We present PPIXpress and PPICompare as two webservers that enable analysis of protein-protein interaction networks (PPINs). Given a reference PPIN and user-uploaded expression data from one or multiple samples, PPIXpress constructs context-dependent PPINs based on major transcripts and high-confidence domain interactions data. To derive a differential PPIN that distinguishes two groups of contextualized PPINs, PPICompare identifies statistically significant altered interactions between multiple context-dependent PPINs from PPIXpress. We present a case study where PPIXpress and PPICompare webservers were used in combination to construct the PPINs specific for melanocytic nevi and primary melanoma cells, and to detect the rewired protein interactions between these two sample types.Availability and implementation: PPIXpress and PPICompare webservers are available at https://service.bioinformatik.uni-saarland.de/ppi-webserver/index_PPIXpress.jsp and https://service.bioinformatik.uni-saarland.de/ppi-webserver/index_PPICompare.jsp, respectively. Alternatively, the webservers and application updates can be found at https://service.bioinformatik.uni-saarland.de/ppi-webserver/.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf003"},"PeriodicalIF":2.4,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11845280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143484643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-10 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf025

Zena Lapp, Hyejin Yoon, Brian Foley, Thomas Leitner

{"title":"Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters.","authors":"Zena Lapp, Hyejin Yoon, Brian Foley, Thomas Leitner","doi":"10.1093/bioadv/vbaf025","DOIUrl":"10.1093/bioadv/vbaf025","url":null,"abstract":"Motivation: The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment.Results: Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified.Availability and implementation: Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf025"},"PeriodicalIF":2.4,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842049/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

mapPat: tracking pathogens evolution in space and time.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-07 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf015

Erika Ferrandi, Graziano Pesole, Matteo Chiara

{"title":"mapPat: tracking pathogens evolution in space and time.","authors":"Erika Ferrandi, Graziano Pesole, Matteo Chiara","doi":"10.1093/bioadv/vbaf015","DOIUrl":"10.1093/bioadv/vbaf015","url":null,"abstract":"Motivation: The COVID-19 pandemic highlighted the importance of genomic surveillance for monitoring pathogens evolution, mitigating the spread of infectious disorders, and informing decision-making by public health authorities. Since the need for the summarization and interpretation of large bodies of data, computational methods are critical for the implementation of effective genomic surveillance strategies.Results: Here, we introduce mapPat, an R Shiny application for the interactive visualization of pathogens genomic data in space and time. mapPat is designed as a user-friendly dashboard and allows the dynamic monitoring of the evolution of variants, lineages, and mutations in the genome of a pathogen at glance through informative geographic maps and elegant data visuals. mapPat provides a fine-grained map of pathogens evolution and circulation and represents a useful addition to the catalogue of bioinformatics methods for the genomic surveillance of pathogens.Availability and implementation: mapPat is available at GitHub (https://github.com/F3rika/mapPat.git).","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf015"},"PeriodicalIF":2.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11835230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

getENRICH: a tool for the gene and pathway enrichment analysis of non-model organisms.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-07 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf023

Ajay Bhatia, Pranjal Pruthi, Isha Chakraborty, Nityendra Shukla, Jitendra Narayan

{"title":"getENRICH: a tool for the gene and pathway enrichment analysis of non-model organisms.","authors":"Ajay Bhatia, Pranjal Pruthi, Isha Chakraborty, Nityendra Shukla, Jitendra Narayan","doi":"10.1093/bioadv/vbaf023","DOIUrl":"10.1093/bioadv/vbaf023","url":null,"abstract":"Motivation: The Gene Ontology system facilitates the functional annotation of genes by categorizing them into specific biological processes, cellular components, and molecular functions. Despite numerous tools like DAVID and Enrichr, analysing non-model organisms remains challenging due to a lack of genetic information and available tools.Results: To address this, we present getENRICH, a comprehensive tool for gene enrichment analysis tailored for non-model organisms. Available in both command-line and web-based graphical user interface (GUI) formats, getENRICH facilitates user-friendly interaction for gene dataset uploads, parameter configuration, and visualization. getENRICH employs hypergeometric distribution for P-value calculation and Benjamini-Hochberg correction for multiple testing.Availability and implementation: getENRICH is freely available under the MIT license, with the source code, documentation, and example datasets available on GitHub (https://github.com/jnarayan81/getENRICH) and the GUI version available at https://getenrich.igib.res.in/.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf023"},"PeriodicalIF":2.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11845281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143484718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simplicity within biological complexity.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-06 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbae164

Nataša Pržulj, Noël Malod-Dognin

{"title":"Simplicity within biological complexity.","authors":"Nataša Pržulj, Noël Malod-Dognin","doi":"10.1093/bioadv/vbae164","DOIUrl":"10.1093/bioadv/vbae164","url":null,"abstract":"Motivation: Heterogeneous, interconnected, systems-level, molecular (multi-omic) data have become increasingly available and key in precision medicine. We need to utilize them to better stratify patients into risk groups, discover new biomarkers and targets, repurpose known and discover new drugs to personalize medical treatment. Existing methodologies are limited and a paradigm shift is needed to achieve quantitative and qualitative breakthroughs.Results: In this perspective paper, we survey the literature and argue for the development of a comprehensive, general framework for embedding of multi-scale molecular network data that would enable their explainable exploitation in precision medicine in linear time. Network embedding methods (also called graph representation learning) map nodes to points in low-dimensional space, so that proximity in the learned space reflects the network's topology-function relationships. They have recently achieved unprecedented performance on hard problems of utilizing few omic data in various biomedical applications. However, research thus far has been limited to special variants of the problems and data, with the performance depending on the underlying topology-function network biology hypotheses, the biomedical applications, and evaluation metrics. The availability of multi-omic data, modern graph embedding paradigms and compute power call for a creation and training of efficient, explainable and controllable models, having no potentially dangerous, unexpected behaviour, that make a qualitative breakthrough. We propose to develop a general, comprehensive embedding framework for multi-omic network data, from models to efficient and scalable software implementation, and to apply it to biomedical informatics, focusing on precision medicine and personalized drug discovery. It will lead to a paradigm shift in the computational and biomedical understanding of data and diseases that will open up ways to solve some of the major bottlenecks in precision medicine and other domains.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbae164"},"PeriodicalIF":2.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11805345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143384228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Queer voices in computational biology: the first ISCB LGBTQI+ Symposium.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-06 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbae204

R Gonzalo Parra, Mark N Wass, Seth Munholland, Mallory L Wiper, Diane Kovats, Lorena Pantano, Roland L Dunbrack

{"title":"Queer voices in computational biology: the first ISCB LGBTQI+ Symposium.","authors":"R Gonzalo Parra, Mark N Wass, Seth Munholland, Mallory L Wiper, Diane Kovats, Lorena Pantano, Roland L Dunbrack","doi":"10.1093/bioadv/vbae204","DOIUrl":"10.1093/bioadv/vbae204","url":null,"abstract":"The first ISCB LGBTQI+ Symposium, held during Pride Month in 2024, marked a significant milestone for the International Society for Computational Biology (ISCB) community to promote diversity. This event aimed to provide a safe and supportive space for LGBTQI+ members of the society to share their experiences, address unique challenges in Bioinformatics and Computational Biology, and foster strategies for creating an equitable environment within ISCB. Through keynote presentations, short talks, and a roundtable discussion, participants explored topics such as minority stress, visibility, and the impact of role models. The symposium was rooted in a recognition of the historical and ongoing marginalization faced by LGBTQI+ individuals and sought to challenge systemic barriers while emphasizing the importance of community and representation. This article details the journey behind organizing the symposium, including overcoming the challenges of ensuring inclusivity and privacy, and highlights the profound impact of role models and collective action in advancing LGBTQI+ equity in science.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbae204"},"PeriodicalIF":2.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11804971/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143384224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FAIRification of the DMRichR pipeline: advancing epigenetic research on environmental and evolutionary model organisms.

IF 2.4

Bioinformatics advances Pub Date : 2025-02-06 eCollection Date: 2025-01-01 DOI: 10.1093/bioadv/vbaf024

Wassim Salam, Marcin W Wojewodzic, Dagmar Frisch

{"title":"FAIRification of the DMRichR pipeline: advancing epigenetic research on environmental and evolutionary model organisms.","authors":"Wassim Salam, Marcin W Wojewodzic, Dagmar Frisch","doi":"10.1093/bioadv/vbaf024","DOIUrl":"10.1093/bioadv/vbaf024","url":null,"abstract":"Summary: Bioinformatics tools often prioritize humans or human-related model organisms, overlooking the requirements of environmentally relevant species, which limits their use in ecological research. This gap is particularly challenging when implementing existing software, as inadequate documentation can delay the innovative use of environmental models for modern risk assessment of chemicals that can cause aberration in methylation patterns. The establishment of fairness in ecological and evolutionary studies is already constrained by more limited resources in these fields of study, and an additional imbalance in tool availability further hinders comprehensive ecological research.To address these gaps, we adapted the DMRichR package, a tool for epigenetic analysis, for use with custom, non-model genomes. As an example, we here use the crustacean Daphnia, a keystone grazer in aquatic ecosystems. This adaptation involved the modification of specific code, computing three new species-specific packages (BSgenome, TxDb, and org.db), and computing a CpG islands track using the makeCGI package. Additional adjustments to the DMRichR package were also necessary to ensure proper functionality. The developed workflow can now be applied not only to different Daphnia species that were previously unsupported but also to any other species for which an annotated reference genome is available.Availability and implementation: Code and data are available at https://github.com/wassimsalam01/DMRichR-FAIRification and at https://github.com/folkehelseinstituttet/DMRichR-FAIRification as well as DOI 10.5281/zenodo.13366959. This work is open-source software available under the GNU Affero General Public License (AGPL) version 3.0.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf024"},"PeriodicalIF":2.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11879348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0