Bio-protocol最新文献

{"title":"A Guide to Basic RNA Sequencing Data Processing and Transcriptomic Analysis.","authors":"Rowayna Shouib, Gary Eitzen, Rineke Steenbergen","doi":"10.21769/BioProtoc.5295","DOIUrl":"10.21769/BioProtoc.5295","url":null,"abstract":"<p><p>RNA sequencing (RNA-Seq) has transformed transcriptomic research, enabling researchers to perform large-scale inspection of mRNA levels in living cells. With the growing applicability of this technique to many scientific investigations, the analysis of next-generation sequencing (NGS) data becomes an important yet challenging task, especially for researchers without a bioinformatics background. This protocol offers a beginner-friendly step-by-step guide to analyze NGS data (starting from raw .fastq files), providing the required codes with an explanation of the different steps and software used. We outline a computational workflow that includes quality control, trimming of reads, read alignment to the genome, and gene quantification, ultimately enabling researchers to identify differentially expressed genes and gain insights on mRNA levels. Multiple approaches to visualize this data using statistical and graphical tools in R are also described, allowing the generation of heatmaps and volcano plots to represent genes and gene sets of interest. Key features • Provides a beginner-friendly protocol for RNA-Seq analysis to obtain insights into gene expression. • Pipeline starts with raw .fastq files and involves analysis in command line/terminal and R (via RStudio). • Yields a variety of output files that represent mRNA levels amongst different samples. Output files include count files, heatmaps, ordered lists of DEGs, and volcano plots.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5295"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067304/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014263","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}

{"title":"Optimized Protocol for DNA Extraction in Three <i>Theobroma</i> Species.","authors":"Angie F Riascos-España, Brayan Toro A Cuastumal, María Castro I Zambrano, Juan Zambrano C Arteaga, Pedro A Velasquez-Vasconez","doi":"10.21769/BioProtoc.5297","DOIUrl":"10.21769/BioProtoc.5297","url":null,"abstract":"<p><p>DNA extraction is a crucial step in molecular biology research, particularly for genetic and genomic analyses. These studies require a high concentration of high-quality DNA, which is often a challenge for underexplored species or when the available plant material consists of aged tissue. To address these challenges, the cetyltrimethylammonium bromide (CTAB)-based DNA extraction method has been optimized to improve efficiency and yield. The process begins with an overnight incubation of plant tissue macerated with liquid nitrogen in a solution containing a high concentration of CTAB (4%). Subsequently, the mixture undergoes two washes with chloroform: isoamyl alcohol. The nucleic acids are then precipitated using isopropanol, followed by a wash with 70% ethanol to ensure purity. Finally, the purified DNA is resuspended in ultrapure water. This optimized procedure produces high-quality DNA suitable for various downstream applications, including PCR and sequencing, even from older leaves of the three <i>Theobroma</i> species: <i>T. cacao, T. bicolor</i>, and <i>T. grandiflorum</i>. Additionally, this protocol significantly enhances throughput and allows for the parallel processing of a substantially larger number of samples compared to conventional techniques. Key features • An efficient CTAB-based DNA extraction protocol provides high-quality nucleic acids from older leaves by increasing CTAB concentration and incubation time in lysis buffer. • Provides reliable yields in the three <i>Theobroma</i> species: <i>T. cacao, T. bicolor</i>, and <i>T. grandiflorum</i>. • A high-throughput workflow reduces processing time and increases daily sample capacity, supporting large-scale genomic investigations.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5297"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067297/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014320","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}

{"title":"snPATHO-seq: A Detailed Protocol for Single Nucleus RNA Sequencing From FFPE.","authors":"Wani Arjumand, Kellie Wise, Hannah DuBose, Jasmine T Plummer, Luciano G Martelotto","doi":"10.21769/BioProtoc.5291","DOIUrl":"10.21769/BioProtoc.5291","url":null,"abstract":"<p><p>Formalin-fixed paraffin-embedded (FFPE) samples remain an underutilized resource in single-cell omics due to RNA degradation from formalin fixation. Here, we present snPATHO-seq, a robust and adaptable approach that enables the generation of high-quality single-nucleus (sn) transcriptomic data from FFPE tissues, utilizing advancements in single-cell genomic techniques. The snPATHO-seq workflow integrates optimized nuclei isolation with the 10× Genomics Flex assay, targeting short RNA fragments to mitigate FFPE-related RNA degradation. Benchmarking against standard 10× 3' and Flex assays for fresh/frozen tissues confirmed robust detection of transcriptomic signatures and cell types. snPATHO-seq demonstrated high performance across diverse FFPE samples, including diseased tissues like breast cancer. It seamlessly integrates with FFPE spatial transcriptomics (e.g., FFPE Visium) for multi-modal spatial and single-nucleus profiling. Compared to workflows like 10× Genomics' snFFPE, snPATHO-seq delivers superior data quality by reducing tissue debris and preserving RNA integrity via nuclei isolation. This cost-effective workflow enables high-resolution transcriptomics of archival FFPE samples, advancing single-cell omics in translational and clinical research. Key features • Optimized nuclei isolation from FFPE tissues enables high-quality single-nucleus transcriptomics by minimizing debris and maximizing intact nuclear yield. • Compatible with 10× Genomics Flex, leveraging short RNA probes to overcome FFPE RNA fragmentation challenges. • Outperforms existing FFPE workflows in cell type detection sensitivity across archival, degraded, or aged samples. • Low-cost, accessible protocol using off-the-shelf reagents, suitable for broad translational and archival tissue applications.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5291"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144058904","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}

{"title":"Standardized Flow Cytometry Method for Absolute Counting of Intraepithelial Lymphocytes in the Intestinal Mucosa Using TruCount^TM Beads.","authors":"Corentin Joulain, Stéphanie Bessoles, Andrada S Chiron, Guillaume Sarrabayrouse, Salima Hacein-Bey-Abina","doi":"10.21769/BioProtoc.5307","DOIUrl":"10.21769/BioProtoc.5307","url":null,"abstract":"<p><p>In the intestinal epithelium, intraepithelial lymphocytes (IELs) coexist with intestinal epithelial cells (IECs). The IELs have an important role in defending the intestinal tract against pathogens and eliminating tumor cells. Anomalies in the absolute IEL count have been reported in various digestive diseases. IELs are typically counted using histologic techniques or under light microscopy after isolation of the epithelium. However, these techniques can introduce bias, which might account for the discrepancies in counts from one study to another. Here, we describe a flow cytometry assay for determining the absolute IEL count and the IEL/IEC ratio. We combined a conventional epithelial isolation method with a BD TruCount^TM bead-based absolute counting technique to quantify IELs (CD45⁺ CD326/EpCAM- CD103⁺CD3⁺) and IECs (CD45- CD326/EpCAM⁺) in a C57BL/6 mouse model. Key features • Intraepithelial lymphocytes (IELs) play a crucial role in maintaining mucosal integrity and defending against pathogens. • Conventional manual counting of IELs using a hemocytometer relies heavily on the operator's expertise. • Flow cytometry offers a more standardized approach to cell counting. • Using TruCount^TM beads to quantify IELs and intraepithelial cells (IECs) by flow cytometry and assess their ratio ensures reproducibility and comparison with immunohistochemical methods. Graphical Overview.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5307"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089825/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144113046","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}

{"title":"Assessing Metabolite Interactions With Chloroplastic Proteins via the PISA Assay.","authors":"Anna Karlsson, Emil Sporre, Linnéa Strandberg, Szilvia Z Tóth, Elton P Hudson","doi":"10.21769/BioProtoc.5298","DOIUrl":"10.21769/BioProtoc.5298","url":null,"abstract":"<p><p>Plants rely on metabolite regulation of proteins to control their metabolism and adapt to environmental changes, but studying these complex interaction networks remains challenging. The proteome integral solubility alteration (PISA) assay, a high-throughput chemoproteomic technique, was originally developed for mammalian systems to investigate drug targets. PISA detects changes in protein stability upon interaction with small molecules, quantified through LC-MS. Here, we present an adapted PISA protocol for <i>Arabidopsis thaliana</i> chloroplasts to identify potential protein interactions with ascorbate. Chloroplasts are extracted using a linear Percoll gradient, treated with multiple ascorbate concentrations, and subjected to heat-induced protein denaturation. Soluble proteins are extracted via ultracentrifugation, and proteome-wide stability changes are quantified using multiplexed LC-MS. We provide instructions for deconvolution of LC-MS spectra and statistical analysis using freely available software. This protocol enables unbiased screening of protein regulation by small molecules in plants without requiring prior knowledge of interaction partners, chemical probe design, or genetic modifications. Key features • Optimization of the PISA assay to study protein-ligand interactions in plant chloroplasts, including isolation of chloroplasts. • Study of regulation on a proteome level, without genetic manipulation or prior knowledge of interaction partners. • High proteome coverage, low sample requirement, 5-fold reduction of TMT-labeling cost, and short LC-MS analysis time. • Adaptable to other organisms, such as bacteria, with minor modifications.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5298"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067301/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994281","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}

{"title":"A Cartilaginous Organoid System Derived From Human Expanded Pluripotent Stem Cells (hEPSCs).","authors":"Hong Wang, Jingyang Qiu, Yin Lin, Xiaochun Bai, Xiaocui Wei","doi":"10.21769/BioProtoc.5304","DOIUrl":"10.21769/BioProtoc.5304","url":null,"abstract":"<p><p>The development of human organotypic models of cartilage provides essential insights into chondrogenesis and chondrocyte hypertrophy while enabling advanced applications in drug discovery, gene editing, and tissue regeneration. Here, we present a robust and efficient protocol for differentiating human expanded pluripotent stem cells (hEPSCs) into hypertrophic chondrocytes through a sclerotome intermediate. The protocol involves initial sclerotome induction, followed by 3D chondrogenic culture and subsequent hypertrophic maturation induced by bone morphogenetic protein-4 (BMP4), thyroid hormone (T3), and β-glycerophosphate. This protocol also allows for sensitive testing of the effects of various compounds on hypertrophic differentiation during the maturation process. Furthermore, we identify an α-adrenergic receptor antagonist, phentolamine, as an inhibitor of hypertrophic differentiation. This organoid system provides a practical platform for exploring cartilage hypertrophy mechanisms and testing therapeutic strategies for cartilage regeneration. Key features • This differentiation protocol generates hypertrophic chondrocytes from hEPSCs through a sclerotome intermediate. • This protocol facilitates sensitive testing of compounds during the hypertrophic maturation stage, enabling the study of molecular mechanisms and therapeutic interventions for cartilage hypertrophy. • This protocol identifies the α-adrenergic receptor antagonist phentolamine as a modulator of hypertrophic differentiation.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5304"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067298/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055034","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}

{"title":"A Cold-Active Protease Tissue Dissociation Protocol for the Preservation of the Tendon Fibroblast Transcriptome.","authors":"Arul Subramanian, Pavan K Nayak, Thomas F Schilling","doi":"10.21769/BioProtoc.5293","DOIUrl":"10.21769/BioProtoc.5293","url":null,"abstract":"<p><p>Traditional tissue dissociation methods for bulk- and single-cell sequencing use various protease and/or collagenase combinations at temperatures ranging from 28 to 37 °C, which cause transcriptional cell stress that may alter data interpretation. Such artifacts can be reduced by dissociating cells in cold-active proteases, but few studies have shown that this improves cell-type specific transcription, particularly in tissues hypersensitive to mechanical integrity and extracellular matrix (ECM) interactions. To address this, we have dissociated zebrafish tendons and ligaments in subtilisin A at 4 °C and compared the results with 37 °C collagenase dissociation using bulk RNA sequencing. We find that high-temperature collagenase dissociation causes general cell stress in tendon fibroblasts (tenocytes) as reported in previous studies with other cell types, but also that high temperature specifically downregulates hallmark genes involved in tenocyte specification and ECM production in vivo. Our results suggest that cold-protease dissociation reduces transcriptional artifacts and increases the robustness of RNA-sequencing datasets such that they better reflect native in vivo tissue microenvironments. Key features • Utilizing a cold-active protease derived from the Himalayan soil bacterium <i>B. licheniformis</i> for tissue dissociation preserves cell transcriptomes, increasing data quality of downstream sequencing experiments. • This method is reproducible and requires no extra equipment for tissue agitation. • Tenocytes isolated using this method show lower stress and better preserved native expression of key tenocyte markers and ECM genes than with traditional warm-dissociation methods. • This protocol is ideal for cell types that are particularly sensitive to microenvironment signals or are embedded in extracellular matrix.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5293"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060442","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}

{"title":"Applying LFQRatio Normalization in Quantitative Proteomic Analysis of Microbial Co-culture Systems.","authors":"Mengxun Shi, Caroline A Evans, Josie L McQuillan, Josselin Noirel, Jagroop Pandhal","doi":"10.21769/BioProtoc.5294","DOIUrl":"10.21769/BioProtoc.5294","url":null,"abstract":"<p><p>Quantitative proteomic analysis plays a crucial role in understanding microbial co-culture systems. Traditional techniques, such as label-free quantification (LFQ) and label-based proteomics, provide valuable insights into the interactions and metabolic exchanges of microbial species. However, the complexity of microbial co-culture systems often leads to challenges in data normalization, especially when dealing with comparative LFQ data where ratios of different organisms can vary across experiments. This protocol describes the application of LFQRatio normalization, a novel normalization method designed to improve the reliability and accuracy of quantitative proteomics data obtained from microbial co-cultures. The method was developed following the analysis of factors that affect both the identification of proteins and the quantitative accuracy of co-culture proteomics. These include peptide physicochemical characteristics such as isoelectric point (pI), molecular weight (MW), hydrophobicity, dynamic range, and proteome size, as well as shared peptides between species. We then created a normalization method based on LFQ intensity values named LFQRatio normalization. This approach was demonstrated by analysis of a synthetic co-culture of two bacteria, <i>Synechococcus elongatus</i> cscB/SPS and <i>Azotobacter vinelandii</i> ΔnifL. Results showed enhanced accuracy of differentially expressed proteins, allowing for more reliable biological interpretation. This protocol provides a reliable and effective tool with wider application to analyze other co-culture systems to study microbial interactions. Key features • Assessment of factors affecting the quantitative accuracy of co-culture proteomics. • Provides a LFQRatio normalization method for label-free quantification of microbial co-cultures. • Recommendations for co-culture proteomics for mixed microbial populations.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5294"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047195","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}

{"title":"Human iPSC-Derived Neuron and Oligodendrocyte Co-culture as a Small-Molecule Screening Assay for Myelination.","authors":"Stefanie Elke Chie, Zsofia Szentpetery, Melanie Generali, Tanja Kuhlmann, Giancarlo Natalucci, Maria Consolata Miletta","doi":"10.21769/BioProtoc.5227","DOIUrl":"10.21769/BioProtoc.5227","url":null,"abstract":"<p><p>Neurons and oligodendrocytes are the building blocks of the brain. Neurons form synaptic connections and transmit signals, while oligodendrocytes, including oligodendrocyte precursor cells (OPCs) and their derivatives, are vital for central nervous system maintenance and myelination. The demand for human-specific neuron-oligodendrocyte model systems to study these interactions has grown, yet co-culture protocols remain limited. Recent advancements in the field provide methods for deriving co-cultures of neurons and OPCs from human induced pluripotent stem cells (hiPSC), each with distinct benefits and challenges. This study presents a time-efficient, reproducible method to derive neurons and O4-expressing oligodendrocytes, followed by a straightforward co-culture system that minimizes astrocyte differentiation and ensures robust neuron and oligodendrocyte populations. Key features • Reliable, stable generation of neurons and O4-expressing oligodendrocytes within a practical timeframe. • Co-culture system utilizing hIPSC-derived neurons and O4-expressing oligodendrocytes. • Maturation of neurons and oligodendrocytes achieved within 10 days of co-culturing. Graphical overview <b>Graphical overview.</b> The diagram outlines the sequential steps involved in the preparation, differentiation, and analysis phases. Key stages include the differentiation of neural progenitor cells (NPCs) into O4-expressing oligodendrocytes and neurons separately and then combining them into a co-culture, which can then be used for further experiments.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5227"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067306/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144038108","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}

{"title":"Analysis of qRT-PCR Data to Identify the Most Stable Reference Gene Using gQuant.","authors":"Abhay Kumar Pathak, Sukhad Kural, Shweta Singh, Lalit Kumar, Manjari Gupta, Garima Jain","doi":"10.21769/BioProtoc.5292","DOIUrl":"10.21769/BioProtoc.5292","url":null,"abstract":"<p><p>The accurate quantification of nucleic acid-based biomarkers, including long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs), is essential for disease diagnostics and risk assessment across the biological spectrum. Quantitative reverse transcription PCR (qRT-PCR) is the gold standard assay for the quantitative measurement of RNA expression levels, but its reliability depends on selecting stable reference targets for normalization. Yet, the lack of consensus on a universally accepted reference gene for a given sample type or species, despite being necessary for accurate quantification, presents a challenge to the broad application of such biomarkers. Various tools are currently being used to identify a stably expressed gene by using qRT-PCR data of a few potential normalizer genes. However, existing tools for normalizer gene selection are fraught with both statistical limitations and inadequate graphical user interfaces for data visualization. gQuant, the tool presented here, essentially overcomes these limitations. The tool is structured in two key components: the preprocessing component and the data analysis component. The preprocessing addresses missing values in the given dataset by the imputation strategies. After data preprocessing, normalizer genes are ranked using democratic strategies that integrate predictions from multiple statistical methods. The effectiveness of gQuant was validated through data available online as well as in-house data derived from urinary exosomal miRNA expression datasets. Comparative analysis against existing tools demonstrated that gQuant delivers more stable and consistent rankings of normalizer genes. With its promising performance, gQuant enhances the precision and reproducibility in the identification of normalizer genes across diverse research scenarios, addressing key limitations of RNA biomarker-based translational research. Key features • Accurate reference gene selection: gQuant identifies the most stable gene in qRT-PCR datasets using a multi-metric approach including SD, GM, CV, and KDE. • Robust missing data handling: Implements imputation and removal strategies to ensure data integrity and accurate normalizer selection. • Bias-free ranking algorithm: Utilizes a voting-based classifier to provide fair and consistent ranking, overcoming limitations of weighted approaches. • Comprehensive visualization: Offers boxplots and KDE plots for analyzing gene expression variability, aiding in data interpretation.</p>","PeriodicalId":93907,"journal":{"name":"Bio-protocol","volume":"15 9","pages":"e5292"},"PeriodicalIF":1.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12067311/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144031686","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}