Web-based Analysis Research Articles

Determination of Ki-67 indices in neuroendocrine tumours of the gastrointestinal tract: the past, the present, and the future.

Ki-67 index (Ki-67i) is integral to the grading of many tumours. There remains considerable variability across pathologists in methods used to determine Ki-67i and in their results. Manual counting (or "eyeballing") is widely used, but digital pathology tools such as web-based image analysis and artificial intelligence-assisted cell detection software have become available in daily pathology practice. This study aims to compare the accuracy and efficiency of manual and two digital methods of Ki-67i determination. H&E and Ki-67 immunohistochemical (IHC) slides/images of 12 gastrointestinal neuroendocrine tumours (GI-NETs) were provided to 8 pathologists to evaluate Ki-67i via manual estimation (ME; the "past"), web-based image analysis using cellular segmentation (AI4Path.ca; the "present"), and software-based image analysis with built-in AI algorithms (QuPath; the "future"). Data collected include Ki67i, time expended, total cells counted, and pathologists' confidence level in the reported result. Deviation of Ki-67i from a gold standard result (GS) was analyzed using multiple linear regression, and results were compared via paired t test. Our results found no statistically significant differences in Ki-67i deviation from GS when comparing ME and AI4P methods for all 12 cases. The QP Ki-67i detection accuracy varied significantly. ME was the method with the least time expenditure. Junior pathologists are less confident in ME. Grading consensus was comparable among all three methods. These findings suggest that while digital pathology can confer increased Ki-67i accuracy in some cases of GI-NETs, higher time expenditure and proper hotspot selection may represent barriers to the adoption of digital pathology methods in the future.

Web-based Land Suitability Analysis for Horticulture Crop (Kiwi) in Champawat districts, Uttrakhand using MCDM and Geospatial Analysis

Identifying the suitability of a horticulture fruit with a defined area is an active research area, it has been attempted through different approaches, surveying and geographic information system are the two most popular techniques utilized extensively for this activity across the globe. GIS has its proven advantage over the field surveys based approach and modern GIS tools offers automation of the entire work flow for this activity. This study presents a web-based land suitability analysis for kiwi fruit cultivation in the Champawat District of Uttarakhand, using AHP, TOPSIS, and Ensemble modeling in conjunction with Multi-Criteria Decision Making (MCDM) and Geospatial Analysis. Land suitability was evaluated across various classes based on nine criteria viz. elevation, chilling hours, land use/land cover (LULC), soil texture, soil depth, temperature, rainfall, slope, and aspect. The AHP method identified 26.09 hectares as highly suitable, 14,606.19 hectares as suitable, 31,899.77 hectares as moderately suitable, 8,807.99 hectares as less suitable, and 192.23 hectares as not suitable. TOPSIS results showed 4,294.32 hectares as highly suitable, 14,193.54 hectares as suitable, 11,782.52 hectares as moderately suitable, and 2,399.21 hectares as less suitable. The ensemble method indicated 24.15 hectares as highly suitable, 8,763.51 hectares as suitable, 13,785.13 hectares as moderately suitable, 2,472.13 hectares as less suitable, and 191.94 hectares as not suitable. Integrating these findings revealed that the ensemble approach closely aligns with AHP in identifying highly suitable and less suitable areas, while TOPSIS emphasizes moderate suitability. This synthesis provides valuable insights for land use planning for kiwi cultivation. Additionally, an online spatial decision support system (SDSS) was developed using the Django framework, offering a modular and secure environment for informed decision-making.

EnteroBase in 2025: exploring the genomic epidemiology of bacterial pathogens.

This paper presents an update on the content, accessibility and analytical tools of the EnteroBase platform for web-based pathogen genome analysis. EnteroBase provides manually curated databases of genome sequence data and associated metadata from currently>1.1 million bacterial isolates, more recently including Streptococcus spp. and Mycobacterium tuberculosis, in addition to Salmonella,Escherichia/Shigella,Clostridioides,Vibrio,Helicobacter,YersiniaandMoraxella. We have implemented the genome-based detection of antimicrobial resistance determinants and the new bubble plot graphical tool for visualizing bacterial genomic population structures, based on pre-computed hierarchical clusters. Access to data and analysis tools is provided through an enhanced graphical user interface and a new application programming interface (RESTful API). EnteroBase is now being developed and operated by an international consortium, to accelerate the development of the platform and ensure the longevity of the resources built. EnteroBase can be accessed at https://enterobase.warwick.ac.uk as well as https://enterobase.dsmz.de.

A Novel Data Analytics Methodology for Discovering Behavioral Risk Profiles: The Case of Diners During a Pandemic

Understanding tourist profiles and behaviors during health pandemics is key to better preparedness for unforeseen future outbreaks, particularly for tourism and hospitality businesses. This study develops and applies a novel data analytics methodology to gain insights into the health risk reduction behavior of restaurant diners/patrons during their dining out experiences in a pandemic. The methodology builds on data relating to four constructs (question categories) and measurements (questions and attributes), with the constructs being worry, health risk prevention behavior, health risk reduction behavior, and demographic characteristics. As a unique contribution, the methodology generates a behavioral typology by identifying risk profiles, which are expressed as one- and two-level decision rules. For example, the results highlighted the significance of restaurants’ adherence to cautionary measures and diners’ perception of seclusion. These and other factors enable a multifaceted analysis, typology, and understanding of diners’ risk profiles, offering valuable guidance for developing managerial strategies and skill development programs to promote safer dining experiences during pandemics. Besides yielding novel types of insights through rules, another practical contribution of the research is the development of a public web-based analytics dashboard for interactive insight discovery and decision support.

Analysis of the Effects of Securing Baseflow and Improving Water Quality through the Introduction of LID Techniques

Rapid climate change and increasing water use have led to various problems in small- and medium-sized urban streams during dry periods, such as stream drying, water pollution, and ecological degradation, reducing their physical and ecological functions. Ensuring adequate baseflow and improving water quality during these critical periods are essential for maintaining urban stream health. While previous studies have explored the effects of Low Impact Development (LID) techniques (e.g., green roof, rainwater harvesting system, permeable pavement, infiltration trench) on infiltration and groundwater recharge, they have primarily focused on general flow regimes rather than dry and low-flow periods. This study specifically evaluates the effects of LID techniques on securing baseflow and improving water quality during dry periods, utilizing the SWAT-MODFLOW model and the Web-based Hydrograph Analysis Tool (WHAT) system. The results show that LID techniques reduce peak flow by an average of 27% and secure an additional 43% of baseflow during dry periods. Suspended solids (SS) and total phosphorus (T-P) concentrations were reduced by 15% and 41%, respectively. These findings demonstrate the effectiveness of LID techniques not only in managing stormwater runoff during flood events but also in maintaining baseflow and water quality during dry periods, thus providing valuable insights for sustainable urban watershed management.

Mortality Trends of Patients with Systemic Lupus Erythematosus on Dialysis in the Japanese Society for Dialysis Therapy (JSDT) Registry: Web-Based Analysis of Dialysis Data Archives (WADDA) System

Mortality Trends of Patients with Systemic Lupus Erythematosus on Dialysis in the Japanese Society for Dialysis Therapy (JSDT) Registry: Web-Based Analysis of Dialysis Data Archives (WADDA) System

Design of Tools for Visualizing Thermodynamic Concepts in Steam Power Plant Trainer Processes with Web-Based Exploratory Data Analysis (EDA)

Thermodynamics is considered one of the most complex and challenging subjects for many students. This is primarily due to comprehending abstract concepts such as entropy, enthalpy, and energy flow, which involve complex mathematical equations and are rarely accompanied by tangible visualizations. This research aims to design, develop, and test a data-based visualization tool for thermodynamics testing results. This study collected and processed data from thermodynamics testing and simulations, such as the mini-steam power plant trainer used as a teaching aid in thermodynamics education, as the foundation for designing a data-based visualization tool for thermodynamics concepts. The visualization tool was created using the Python programming language integrated with the web-based Streamlit framework. The designed visualization tool encompasses various features, including automated data reporting, visualization of variable correlations using correlation heatmaps, Sankey diagrams for visualizing energy flow, and the capability to predict electrical output using machine learning integrated with three different machine learning algorithms. The visualization tool was evaluated by thermodynamics experts using a Likert scale. Based on the results obtained, the experts gave an average score of 4 in the information accuracy aspect in the good category. This shows that the information displayed in this visualization tool is by thermodynamics learning at Padang State University. In the visualization aspect, experts gave an average score of 4.25, which is in the Good and Very Good range. In alignment with the education aspect, experts gave an average score of 3.75, which is close to the good category. This shows that this aspect is considered suitable for studying thermodynamics, although shortcomings still need to be corrected. Experts gave a relatively high assessment of the Ease-of-Use aspect, with an average score of 4.5, with a range of Good and Very Good. This enables students to better understand complex patterns, cause-and-effect relationships, and parameter changes within thermodynamics concepts.

Location factors and ecosystem embedding of sustainability-engaged blockchain companies in the US. A web-based analysis

While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy demand. In our study, we present a novel approach to identifying sustainability-focused blockchain companies and relate their level of engagement to location factors and entrepreneurial ecosystem embeddedness. For this, we use a large-scale web scraping approach to analyze the textual content and hyperlink networks of all US companies from their websites. Our results show that blockchain remains a niche technology, with its use communicated by about 0.6% of US companies. However, the proportion of blockchain companies that are committed to sustainability is significantly higher than in the overall firm population. Additionally, we find that such sustainability-engaged blockchain companies have, at least quantitatively, a more intensive embedding in entrepreneurial ecosystems, while infrastructural and socio-economic location factors hardly play a role.

Development of Sentiment Analysis System of Simple Pol Application on Google Play Store Using Naive Bayes Classifier Method and BERT Prediction

Digitalization in public services raises various sentiments that are very dynamic, one example is the Simpel Pol Health Test application made by PT Cipta Sari Arsonia (CSA). The research objective is to obtain useful information from accurate community review sentiments for service improvement and feedback for service providers and application developers. The method used is Naïve Bayes Classifier with Tf-idf weighting, Multinomial Naïve Bayes with review value indicators and review sentences predicted by the BERT method as a determinant of sentiment value whether positive or negative. Sentiment towards the application shows quite encouraging results, from 3000 data analyzed with 1772 positive reviews and 263 negative reviews with 80% training data and 20% test data, the naïve bayes classification model is able to provide a high level of accuracy, which is 88.7% with a precision of 88.5%, recall of 100% and f1-score of 93.9%. The data showed that most people gave a positive response to this application, with the dominant word being 'easy'. This system was developed using the local-based streamlit framework and proved to be quite reliable in developing systems for data processing and web-based data analysis even though the scraping process is slightly longer than the google colab service. Future research is expected to be able to predict data that is positive or negative with several parameters and several sentiment analysis methods at once and their comparison.

Whole genome sequencing of cr(VI) resistant Morganella morganii (1Ab1) towards identification of chromate transporters

Chromium (Cr) present naturally as the most abundant element on Earth’s crust. It usually exists combined with other chemical elements as oxygen and potassium in the form of chromium compounds. However, its level is raised due to leather tanning in tannery industries which turns less toxic trivalent chromium [Cr(III)] into highly toxic hexavalent chromium [Cr(VI)]. Chromium-resistant bacteria harbors Chr transporters in their genome which involves in metabolic reduction of toxic Cr to nontoxic Cr with the help of enzyme “chromate reductase.” This enzyme acts as a potential agent in bioremediation of highly chrome polluted sites. In this investigation, Whole Genome Sequencing (WGS) was done to find Chr transporters in the identified bacteria Morganella morganii (1Ab1) isolated from tannery effluent contaminated sites of Dindigul district, Tamil Nadu, India. Further, chr genes were confirmed using Real Time PCR and Web-based proteomic analysis tools such as Protter and Swiss Model. Finally output was reckoned for 3-D structure prediction and interactive visualization of the chr gene-encoded Chr protein that involves in Cr(VI) reduction.

Estimation of Groundwater Recharge in a Volcanic Aquifer System Using Soil Moisture Balance and Baseflow Separation Methods: The Case of Gilgel Gibe Catchment, Ethiopia

Understanding the recharge–discharge system of a catchment is key to the efficient use and effective management of groundwater resources. The present study focused on the estimation of groundwater recharge using Soil Moisture Balance (SMB) and Baseflow Separation (BFS) methods in the Gilgel Gibe catchment where water demand for irrigation, domestic, and industrial purposes is dramatically increasing. The demand for groundwater and the existing ambitious plans to respond to this demand will put a strain on the groundwater resource in the catchment unless prompt intervention is undertaken to ensure its sustainability. Ground-based hydrometeorological 36-years data (1985 to 2020) from 17 stations and satellite products from CHIRPS and NASA/POWER were used for the SMB method. Six BFS methods were applied through the Web-based Hydrograph Analysis Tool (WHAT), SepHydro, BFLOW, and Automated Computer Programming (PART) to sub-catchments and the main catchment to estimate the groundwater recharge. The streamflow data (discharge) obtained from the Ministry of Water and Energy were the main input data for the BFS methods. The average annual recharge of groundwater was estimated to be 313 mm using SMB for the years 1985 to 2020 and 314 mm using BFS for the years 1986 to 2003. The results from the SMB method revealed geographical heterogeneity in annual groundwater recharge, varying from 209 to 442 mm. Significant spatial variation is also observed in the estimated annual groundwater recharge using the BFS methods, which varies from 181 to 411 mm for sub-catchments. Hydrogeological conditions of the catchment were observed, and the yielding capacity of existing wells was assessed to evaluate the validity of the results. The recharge values estimated using SMB and BFS methods are comparable and hydrologically reasonable. The findings remarkably provide insightful information for decision-makers to develop effective groundwater management strategies and to prioritize the sub-catchments for immediate intervention to ensure the sustainability of groundwater.

Elaborating and performing optimization approaches for web-based 3D spatial analysis of 3D city models

ABSTRACT Three-dimensional (3D) geographic information systems (GIS) are vital for urban planning and architectural design, enabling detailed visualization and analysis of urban landscapes. However, the growing size of 3D city data and the transition to web environments cause performance challenges for real-time applications. This study addresses the need for optimizing 3D spatial analyses for the web using Quadtree data structures and multiprocessing tools. Optimization scenarios based on data size and hardware configurations are evaluated, and the best hosting plans for GIS applications on cloud services are also considered.

Web-Based Medical Imaging Analysis–Leveraging Progressive Web Application for DICOM and MPR Visualization: Software Development and Validation (Preprint)

Web-Based Medical Imaging Analysis–Leveraging Progressive Web Application for DICOM and MPR Visualization: Software Development and Validation (Preprint)

Online Provision of BRCA1 and BRCA2 Health Information: A Search Engine Driven Systematic Web-Based Analysis.

BRCA genetic testing is available for UK Jewish individuals but the provision of information online for BRCA is unknown. We aimed to evaluate online provision of BRCA information by UK organisations (UKO), UK Jewish community organisations (JCO), and genetic testing providers (GTP). Google searches for organisations offering BRCA information were performed using relevant sets of keywords. The first 100 website links were categorised into UKOs/JCOs/GTPs; additional JCOs were supplemented through community experts. Websites were reviewed using customised questionnaires for BRCA information. Information provision was assessed for five domains: accessibility, scope, depth, accuracy, and quality. These domains were combined to provide a composite score (maximum score = 5). Results were screened (n = 6856) and 45 UKOs, 16 JCOs, and 18 GTPs provided BRCA information. Accessibility was high (84%,66/79). Scope was lacking with 35% (28/79) addressing >50% items. Most (82%, 65/79) described BRCA-associated cancers: breast and/or ovarian cancer was mentioned by 78%(62/79), but only 34% (27/79) mentioned ≥1 pancreatic, prostate, melanoma. Few websites provided carrier frequencies in the general (24%,19/79) and Jewish populations (20%,16/79). Only 15% (12/79) had quality information with some/minimal shortcomings. Overall information provision was low-to-moderate: median scores UKO = 2.1 (IQR = 1), JCO = 1.6 (IQR = 0.9), and GTP = 2.3 (IQR = 1) (maximum-score = 5). There is a scarcity of high-quality BRCA information online. These findings have implications for UK Jewish BRCA programmes and those considering BRCA testing.

Are urologists underrepresented on fertility clinic websites? A web-based analysis.

Infertile couples frequently utilize the Internet to find various reproductive clinics and research their alternatives. Patients are increasingly using self-referral because of online information on health-care providers. The objective is to compare the image of infertility specialists to other team members on the websites of reproductive clinics. Information was gathered during November and December 2022 from two publicly accessible online registries which include the Human Fertilization and Embryology Authority located in the United Kingdom and the Society for Assisted Reproductive Technology located in the United States. We looked over every website that was accessible, paying close attention to how each team member was portrayed online. We examined a total of 447 clinic websites. Only 8% of the profiles of male infertility doctors were included. Contrarily, most websites (96%), which specialize in reproductive endocrinology and infertility, feature the profiles of female infertility experts. Male infertility professionals also had significantly lower representation than other clinic employees, such as nurses (55.7%, P < 0.0001), directors of embryology laboratories (46.5%, P < 0.0001), office personnel (39.6%, P < 0.0001), and embryology specialists (29.7%, P < 0.0001). Although male factor infertility explains the existence of over half of all cases of infertility, urologists who specialize in male infertility are glaringly understated on websites for fertility clinics. By improving this issue, fertility clinics can draw in more patients by making all members of the care team more visible.

Evaluation of spring flows using recession flow analysis techniques

ABSTRACT This study delves into the analysis of recession characteristics of spring base flow, focusing on the Hill campus spring (elevation of approximately 2,150 m) and Fakua spring (elevation of approximately 1,850 m) in the Tehri Garhwal district of Uttarakhand, India. Spanning from January 1999 to December 2004, discharge data from G.B. Pant University of Agriculture and Technology's Hill campus are employed. The research employs an automated, objective-based method to generate master recession curves (MRCs) and categorize them into early, intermittent, and late recession segments. Statistical parameters and low-flow indices from flow duration curves (FDCs) are utilized for flow assessment, while base flow indices (BFIs) are analyzed using the Web-based Hydrograph Analysis Tool (WHAT). The findings highlight the importance of water storage strategies during the rainy season for the sustainable utilization of spring water. The study suggests that the techniques applied are equally applicable for analyzing river flow recession characteristics, emphasizing the broader implications for integrated water resources planning and management in mountainous regions.

Inhibition of Amyloid-β (Aβ)-Induced Cognitive Impairment and Neuroinflammation in CHI3L1 Knockout Mice through Downregulation of ERK-PTX3 Pathway.

Several clinical studies reported that the elevated expression of Chitinase-3-like 1 (CHI3L1) was observed in patients suffering from a wide range of diseases: cancer, metabolic, and neurological diseases. However, the role of CHI3L1 in AD is still unclear. Our previous study demonstrated that 2-({3-[2-(1-Cyclohexen-1-yl)ethyl]-6,7-dimethoxy-4-oxo-3,4-dihydro-2-quinazolinyl}culfanyl)-N-(4-ethylphenyl)butanamide, a CHI3L1 inhibiting compound, alleviates memory and cognitive impairment and inhibits neuroinflammation in AD mouse models. In this study, we studied the detailed correlation of CHI3L1 and AD using serum from AD patients and using CHI3L1 knockout (KO) mice with Aβ infusion (300 pmol/day, 14 days). Serum levels of CHI3L1 were significantly elevated in patients with AD compared to normal subjects, and receiver operating characteristic (ROC) analysis data based on serum analysis suggested that CHI3L1 could be a significant diagnostic reference for AD. To reveal the role of CHI3L1 in AD, we investigated the CHI3L1 deficiency effect on memory impairment in Aβ-infused mice and microglial BV-2 cells. In CHI3L1 KO mice, Aβ infusion resulted in lower levels of memory dysfunction and neuroinflammation compared to that of WT mice. CHI3L1 deficiency selectively inhibited phosphorylation of ERK and IκB as well as inhibition of neuroinflammation-related factors in vivo and in vitro. On the other hand, treatment with recombinant CHI3L1 increased neuroinflammation-related factors and promoted phosphorylation of IκB except for ERK in vitro. Web-based gene network analysis and our results showed that CHI3L1 is closely correlated with PTX3. Moreover, in AD patients, we found that serum levels of PTX3 were correlated with serum levels of CHI3L1 by Spearman correlation analysis. These results suggest that CHI3L1 deficiency could inhibit AD development by blocking the ERK-dependent PTX3 pathway.

PESSA: A web tool for pathway enrichment score-based survival analysis in cancer.

The activation levels of biologically significant gene sets are emerging tumor molecular markers and play an irreplaceable role in the tumor research field; however, web-based tools for prognostic analyses using it as a tumor molecular marker remain scarce. We developed a web-based tool PESSA for survival analysis using gene set activation levels. All data analyses were implemented via R. Activation levels of The Molecular Signatures Database (MSigDB) gene sets were assessed using the single sample gene set enrichment analysis (ssGSEA) method based on data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The European Genome-phenome Archive (EGA) and supplementary tables of articles. PESSA was used to perform median and optimal cut-off dichotomous grouping of ssGSEA scores for each dataset, relying on the survival and survminer packages for survival analysis and visualisation. PESSA is an open-access web tool for visualizing the results of tumor prognostic analyses using gene set activation levels. A total of 238 datasets from the GEO, TCGA, EGA, and supplementary tables of articles; covering 51 cancer types and 13 survival outcome types; and 13,434 tumor-related gene sets are obtained from MSigDB for pre-grouping. Users can obtain the results, including Kaplan-Meier analyses based on the median and optimal cut-off values and accompanying visualization plots and the Cox regression analyses of dichotomous and continuous variables, by selecting the gene set markers of interest. PESSA (https://smuonco.shinyapps.io/PESSA/ OR http://robinl-lab.com/PESSA) is a large-scale web-based tumor survival analysis tool covering a large amount of data that creatively uses predefined gene set activation levels as molecular markers of tumors.

YBX1 as a prognostic biomarker and potential therapeutic target in hepatocellular carcinoma: A comprehensive investigation through bioinformatics analysis and in vitro study

BackgroundsY-box binding protein 1 (YBX1) is a DNA/RNA binding protein known to contribute to the progression of various malignancies, however, a comprehensive pan-cancer analysis to investigate YBX1 across a broad spectrum of cancer types has not yet been conducted. MethodsWe utilized the TIMER database for a comprehensive pan-cancer analysis and assessed YBX-1 expression via the TCGA and GEO databases. The relationship between YBX-1 expression and tumor-infiltrating cells was examined using TIMER and the R programming language. To evaluate the prognostic value of YBX1, we performed Kaplan-Meier plots and Cox regression analyses. Through LinkedOmics, we identified genes significantly correlated with YBX-1. The WEB-based Gene SeT AnaLysis Toolkit was used for KEGG pathway enrichment analysis. Additionally, using shRNA-mediated knockdown, we explored the potential role of YBX1 in tumor cell biology. ResultsOur study identifies pronounced overexpression of YBX-1 across multiple cancer types, correlating with adverse outcomes, notably in liver hepatocellular carcinoma (LIHC). A distinct association between elevated YBX-1 expression and heightened immune cell infiltration suggests YBX-1′s potential role in reshaping the tumor microenvironment. Intriguingly, our KEGG pathway analysis indicated a tight nexus between YBX-1 expression and lipid metabolism. Moreover, the suppression of YBX-1 via shRNA revealed diminished cellular proliferation and marked reductions in crucial molecules steering the fatty acid synthesis pathway, implicating YBX-1′s potential regulatory role in lipid metabolism within LIHC. ConclusionsYBX-1 serves as a favorable prognostic indicator in various cancers, particularly in liver hepatocellular carcinoma. Targeting YBX1 in HCC offers potential therapeutic strategies. This work paves the way for fresh insights into targeted therapeutic approaches for cancers, especially benefiting liver hepatocellular carcinoma patients.

Shaoxia: a web-based interactive analysis platform for single cell RNA sequencing data

BackgroundIn recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis.ResultsWe proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise.ConclusionShaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud, and its source code is publicly available at https://github.com/WiedenWei/shaoxia.