Interactive Web App Research Articles

Collapsible tree: interactive web app to present collapsible hierarchies.

A crucial component of intuitive data visualization is presenting a hierarchical tree structure with interactive functions. For example, single-cell transcriptomics studies may generate gene expression values with developmental trajectories or cell lineage structures. Two common visualization methods, t-SNE and UMAP, require two separate figures to depict the distribution of cell types and gene expression data, with low-dimension projections that may not capture the hierarchical structures among cells. Here, we present a JavaScript framework and an interactive web app named Collapsible Tree, which presents values jointly with interactive, expandable, and collapsible lineage structures. For example, the Collapsible Tree presents cellular states and gene expression from single-cell transcriptomics within a single hierarchical plot, enabling comparisons of gene expression across lineages and subtle patterns between sub-lineages. Our framework can facilitate the exploration of complicated value patterns that are not evident in UMAP or t-SNE plots. The Collapsible Tree web interface is available at https://collapsibletree.data2in.net. The JavaScript library source code is available at https://github.com/data2intelligence/collapsible_tree.

Silence is golden, but my measures still see—why cheaper-but-noisier outcome measures in large simple trials can be more cost-effective than gold standards

ObjectiveTo assess the cost-effectiveness of using cheaper-but-noisier outcome measures, such as a short questionnaire, for large simple clinical trials.BackgroundTo detect associations reliably, trials must avoid bias and random error. To reduce random error, we can increase the size of the trial and increase the accuracy of the outcome measurement process. However, with fixed resources, there is a trade-off between the number of participants a trial can enrol and the amount of information that can be collected on each participant during data collection.MethodsTo consider the effect on measurement error of using outcome scales with varying numbers of categories, we define and calculate the variance from categorisation that would be expected from using a category midpoint; define the analytic conditions under which such a measure is cost-effective; use meta-regression to estimate the impact of participant burden, defined as questionnaire length, on response rates; and develop an interactive web-app to allow researchers to explore the cost-effectiveness of using such a measure under plausible assumptions.ResultsAn outcome scale with only a few categories greatly reduced the variance of non-measurement. For example, a scale with five categories reduced the variance of non-measurement by 96% for a uniform distribution. We show that a simple measure will be more cost-effective than a gold-standard measure if the relative increase in variance due to using it is less than the relative increase in cost from the gold standard, assuming it does not introduce bias in the measurement. We found an inverse power law relationship between participant burden and response rates such that a doubling the burden on participants reduces the response rate by around one third. Finally, we created an interactive web-app (https://benjiwoolf.shinyapps.io/cheapbutnoisymeasures/) to allow exploration of when using a cheap-but-noisy measure will be more cost-effective using realistic parameters.ConclusionCheaper-but-noisier questionnaires containing just a few questions can be a cost-effective way of maximising power. However, their use requires a judgement on the trade-off between the potential increase in risk of information bias and the reduction in the potential of selection bias due to the expected higher response rates.

PheMIME: an interactive web app and knowledge base for phenome-wide, multi-institutional multimorbidity analysis.

To address the need for interactive visualization tools and databases in characterizing multimorbidity patterns across different populations, we developed the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME). This tool leverages three large-scale EHR systems to facilitate efficient analysis and visualization of disease multimorbidity, aiming to reveal both robust and novel disease associations that are consistent across different systems and to provide insight for enhancing personalized healthcare strategies. PheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities, utilizing data from Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. It offers interactive and multifaceted visualizations for exploring multimorbidity. Incorporating an enhanced version of associationSubgraphs, PheMIME also enables dynamic analysis and inference of disease clusters, promoting the discovery of complex multimorbidity patterns. A case study on schizophrenia demonstrates its capability for generating interactive visualizations of multimorbidity networks within and across multiple systems. Additionally, PheMIME supports diverse multimorbidity-based discoveries, detailed further in online case studies. The PheMIME is accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial and multiple case studies for demonstration are available at https://prod.tbilab.org/PheMIME_supplementary_materials/. The source code can be downloaded from https://github.com/tbilab/PheMIME. PheMIME represents a significant advancement in medical informatics, offering an efficient solution for accessing, analyzing, and interpreting the complex and noisy real-world patient data in electronic health records. PheMIME provides an extensive multimorbidity knowledge base that consolidates data from three EHR systems, and it is a novel interactive tool designed to analyze and visualize multimorbidities across multiple EHR datasets. It stands out as the first of its kind to offer extensive multimorbidity knowledge integration with substantial support for efficient online analysis and interactive visualization.

The spatial distribution of heat related hospitalizations and classification of the most dangerous heat events in California at a small-scale level

Many studies have explored the impact of extreme heat on health, but few have investigated localized heat-health outcomes across a wide area. We examined fine-scale variability in vulnerable areas, considering population distribution, local weather, and landscape characteristics. Using 36 different heat event definitions, we identified the most dangerous types of heat events based on minimum, maximum, and diurnal temperatures with varying thresholds and durations. Focusing on California's diverse climate, elevation, and population distribution, we analyzed hospital admissions for various causes of admission (2004–2013). Our matching approach identified vulnerable zip codes, even with small populations, on absolute and relative scales. Bayesian Hierarchical models leveraged spatial correlation. We ranked the 36 heat event types by attributable hospital admissions per zip code and provided code, simulated data, and an interactive web app for reproducibility. Our findings showed high variation in heat-related hospitalizations in coastal cities and substantial heat burdens in the Central Valley. Diurnal heat events had the greatest impact in the Central Valley, while nighttime extreme heat events drove burdens in the southeastern desert. This spatially informed approach guides local policies, prioritizing dangerous heat events to reduce the heat-health burden. The methodology is applicable to other regions, informing early warning systems and characterizing extreme heat impacts.

MetaboReport: from metabolomics data analysis to comprehensive reporting.

Metabolomics, as an essential tool in systems biology, is now widely accessible to researchers of all levels. Yet challenges remain in data analysis and result interpretation. To address these challenges, we introduced MetaboReport, a versatile and interactive web app that simplifies metabolomics experiment design, data preprocessing, exploration, statistical analysis, visualization, and reporting. MetaboReport produces a comprehensive HTML report, including project details, an introduction, interactive plots and tables, statistical results and an in-depth explanations and interpretation of the results. MetaboReport is particularly tailored for research labs and metabolomics core facilities that provide metabolomics services, allowing them to efficiently manage and document different metabolomics projects, and effectively report the metabolomics results to users. MetaboReport is freely accessible on https://metaboreport.com, with source code available on GitHub (https://github.com/YonghuiDong/MetReport). Alternatively, users can install MetaboReport as a standalone desktop app (https://metaboreport.sourceforge.io).

The phage shock protein (PSP) envelope stress response: discovery of novel partners and evolutionary history.

Bacterial phage shock protein (PSP) systems stabilize the bacterial cell membrane and protect against envelope stress. These systems have been associated with virulence, but despite their critical roles, PSP components are not well characterized outside proteobacteria. Using comparative genomics and protein sequence-structure-function analyses, we systematically identified and analyzed PSP homologs, phyletic patterns, domain architectures, and gene neighborhoods. This approach underscored the evolutionary significance of the system, revealing that its core protein PspA (Snf7 in ESCRT outside bacteria) was present in the last universal common ancestor and that this ancestral functionality has since diversified into multiple novel, distinct PSP systems across life. Several novel partners of the PSP system were identified: (i) the Toastrack domain, likely facilitating assembly of sub-membrane stress-sensing and signaling complexes, (ii) the newly defined HTH-associated α-helical signaling domain-PadR-like transcriptional regulator pair system, and (iii) multiple independent associations with ATPase, CesT/Tir-like chaperone, and Band-7 domains in proteins thought to mediate sub-membrane dynamics. Our work also uncovered links between the PSP components and other domains, such as novel variants of SHOCT-like domains, suggesting roles in assembling membrane-associated complexes of proteins with disparate biochemical functions. Results are available at our interactive web app, https://jravilab.org/psp.IMPORTANCEPhage shock proteins (PSP) are virulence-associated, cell membrane stress-protective systems. They have mostly been characterized in Proteobacteria and Firmicutes. We now show that a minimal PSP system was present in the last universal common ancestor that evolved and diversified into newly identified functional contexts. Recognizing the conservation and evolution of PSP systems across bacterial phyla contributes to our understanding of stress response mechanisms in prokaryotes. Moreover, the newly discovered PSP modularity will likely prompt new studies of lineage-specific cell envelope structures, lifestyles, and adaptation mechanisms. Finally, our results validate the use of domain architecture and genetic context for discovery in comparative genomics.

The Acoustic Index User's Guide: A practical manual for defining, generating and understanding current and future acoustic indices

Abstract Ecoacoustics, the study of environmental sound, is a rapidly growing discipline offering ecological insights at scales ranging from individual organisms to whole ecosystems. Substantial methodological developments over the last 15 years have streamlined extraction of ecological information from audio recordings. One widely used set of methods are acoustic indices, which offer numerical summaries of the spectral, temporal and amplitude patterns in audio recordings. Currently, the specifics of each index's background, methodology and the soundscape patterns they are designed to summarise, are spread across multiple sources. Critically, details of index calculation are sometimes scarce, making it challenging for users to understand how index values are generated. Discrepancies in understanding can lead to misuse of acoustic indices or reporting of spurious results. This hinders ecological inference, replicability and discourages adoption of these tools for conservation and ecosystem monitoring, where they might otherwise provide useful insight. Here we present the Acoustic Index User's Guide—an interactive RShiny web app that defines and deconstructs eight of the most commonly used acoustic indices to facilitate consistent application across the discipline. We break the acoustic indices calculations down into easy‐to‐follow steps to better enable practical application and critical interpretation of acoustic indices. We demonstrate typical soundscape patterns using a suite of 91 example audio recordings: 66 real‐world soundscapes from terrestrial, aquatic and subterranean systems around the world, and 25 synthetic files demonstrating archetypal soundscape patterns. Our interpretation figures signpost specific soundscape patterns likely to be reflected in acoustic indices' values. This RShiny app is a living resource; additional acoustic indices will be added in the future through collaboration with authors of pre‐existing and new indices. The app also serves as a best‐practice template for the information required when publishing new acoustic indices, so that authors can facilitate the widest possible understanding and uptake of their indices. In turn, improved understanding of acoustic indices will aid effective hypothesis generation, application and interpretation in ecological research, ecosystem monitoring and conservation management.

#956 Exome sequencing in adults with secondary thrombotic microangiopathy with kidney involvement

Abstract Background and Aims Currently, genetic testing is recommended in patients with thrombotic microangiopathy (TMA) and renal involvement when a complement-dependent TMA is clinically suspected. Due to a possibly poor phenotype-genotype correlation, this strategy may be suboptimal. We aimed to assess the impact of a strategy using Exome Sequencing (ES) regardless of initial suspicion. Method We conducted a prospective observational study. Data was collected in all consecutive adult patients who received a primary diagnostic ES test as part of routine care for unexplained chronic kidney disease between October 10, 2017, and December 31, 2022, at the Nephrology Department of Assistance Publique-Hôpitaux de Paris/Sorbonne University, Paris, France (Tenon and Pitié-Salpêtrière hospitals). Patients with thrombotic thrombocytopenic purpura or typical hemolytic and uremic syndrome were not included. The association between patients’ phenotypes and genotypes was explored using a validated method relying on Term Frequency-Inverse Document Frequency (TF-IDF). Results 1 413 patients underwent ES, of whom 153 (11%) had biological and/or histological indicators of TMA. ES identified a variant consistent with the renal phenotype in 20/153 (13%) cases. In 13/20 cases (65%), a genetic disorder which was not complement TMA was diagnosed: five patients had nephronophthisis (TTC21B, n = 4, NPHP3, n = 1); two had Alport's disease (COL4A4 and COL4A3, n = 1); one had Cobalamin-C deficiency (MMACHC); five had other distinct conditions (variants in SOX18, IFT140, WT1, TREX1 and UMOD). Direct clinical implications of performing ES were observed in 35/153 (23%) cases. An interactive web-app was developed to enable in-depth exploration of phenotype-genotype association, and no association between patients’ phenotypes and genotypes were observed. Conclusion First-tier ES in patients with TMA and renal involvement, irrespective of clinical suspicion, revealed diagnoses that would not have been initially obtained according to the currently recommended strategy. In patients with TMA and renal involvement, we did not find an association between patients’ phenotypes and genotypes.

Alpha-Band Frequency and Temporal Windows in Perception: A Review and Living Meta-analysis of 27 Experiments (and Counting).

Temporal windows in perception refer to windows of time within which distinct stimuli interact to influence perception. A simple example is two temporally proximal stimuli fusing into a single percept. It has long been hypothesized that the human alpha rhythm (an 8- to 13-Hz neural oscillation maximal over posterior cortex) is linked to temporal windows, with higher frequencies corresponding to shorter windows and finer-grained temporal resolution. This hypothesis has garnered support from studies demonstrating a correlation between individual differences in alpha-band frequency (IAF) and behavioral measures of temporal processing. However, nonsignificant effects have also been reported. Here, we review and meta-analyze 27 experiments correlating IAF with measures of visual and audiovisual temporal processing. Our results estimate the true correlation in the population to be between .39 and .53, a medium-to-large effect. The effect held when considering visual or audiovisual experiments separately, when examining different IAF estimation protocols (i.e., eyes open and eyes closed), and when using analysis choices that favor a null result. Our review shows that (1) effects have been internally and independently replicated, (2) several positive effects are based on larger sample sizes than the null effects, and (3) many reported null effects are actually in the direction predicted by the hypothesis. A free interactive web app was developed to allow users to replicate our meta-analysis and change or update the study selection at will, making this a "living" meta-analysis (randfxmeta.streamlit.app). We discuss possible factors underlying null reports, design recommendations, and open questions for future research.

Easy-Amanida: An R Shiny application for the meta-analysis of aggregate results in clinical metabolomics using Amanida and Webchem.

Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics is significantly lower compared to other omics disciplines. Metabolomics is the study of small chemical compounds in living organisms, which provides important insights into an organism's phenotype. However, the wide variety of compounds and the different experimental methods used in metabolomics make it challenging to perform a thorough meta-analysis. Additionally, there is a lack of consensus on reporting statistical estimates, and the high number of compound naming synonyms further complicates the process. Easy-Amanida is a new tool that combines two R packages, "amanida" and "webchem", to enable meta-analysis of aggregate statistical data, like p-value and fold-change, while ensuring the compounds naming harmonization. The Easy-Amanida app is implemented in Shiny, an R package add-on for interactive web apps, and provides a workflow to optimize the naming combination. This article describes all the steps to perform the meta-analysis using Easy-Amanida, including an illustrative example for interpreting the results. The use of aggregate statistics metrics extends the use of Easy-Amanida beyond the metabolomics field.

Mapmixture: An R package and web app for spatial visualisation of admixture and population structure.

The mapmixture R package and interactive web app are tools to aid visualisation of admixture and population structure in geographic space. The purpose of mapmixture is to enable and encourage molecular ecologists, and in particular population geneticists and phylogeneticists, to plot their admixture, ancestry or assignment results on a map when location information is available. mapmixture accepts data in the format typically generated by admixture analyses and visualises proportions to each genetic cluster per site as pie charts on a projected (optional) map. Combining this site-based map presentation approach with the routine individual-based presentation of admixture (structure) barplots will enhance interpretation of genetic-geographic patterns. Additionally, in the context of science communication, this enables clearer transfer of spatial genetic information to readers or listeners, and especially to audiences that do not have a background in genetics but who are able to use the genetic information as evidence in conservation management. The latest version of mapmixture is available on GitHub (https://github.com/tom-jenkins/mapmixture), which details installation instructions and examples of how to use the package and interactive web app.

BetAS: intuitive analysis and visualization of differential alternative splicing using beta distributions.

Next-generation RNA sequencing allows alternative splicing (AS) quantification with unprecedented resolution, with the relative inclusion of an alternative sequence in transcripts being commonly quantified by the proportion of reads supporting it as percent spliced-in (PSI). However, PSI values do not incorporate information about precision, proportional to the respective AS events' read coverage. Beta distributions are suitable to quantify inclusion levels of alternative sequences, using reads supporting their inclusion and exclusion as surrogates for the two distribution shape parameters. Each such beta distribution has the PSI as its mean value and is narrower when the read coverage is higher, facilitating the interpretability of its precision when plotted. We herein introduce a computational pipeline, based on beta distributions accurately modeling PSI values and their precision, to quantitatively and visually compare AS between groups of samples. Our methodology includes a differential splicing significance metric that compromises the magnitude of intergroup differences, the estimation uncertainty in individual samples, and the intragroup variability, being therefore suitable for multiple-group comparisons. To make our approach accessible and clear to both noncomputational and computational biologists, we developed betAS, an interactive web app and user-friendly R package for visual and intuitive differential splicing analysis from read count data.

CloudAISim: A toolkit for modelling and simulation of modern applications in AI-driven cloud computing environments

There is a very significant knowledge gap between Artificial Intelligence (AI) and a multitude of industries that exist in today’s modern world. This is primarily attributable to the limited availability of resources and technical expertise. However, a major obstacle is that AI needs to be flexible enough to work in many different applications, utilising a wide variety of datasets through cloud computing. As a result, we developed a benchmark toolkit called CloudAISim to make use of the power of AI and cloud computing in order to satisfy the requirements of modern applications. The goal of this study is to come up with a strategy for building a bridge so that AI can be utilised in order to assist those who are not very knowledgeable about technological advancements. In addition, we modelled a healthcare application as a case study in order to verify the scientific reliability of the CloudAISim toolkit and simulated it in a cloud computing environment using Google Cloud Functions to increase its real-time efficiency. A non-expert-friendly interface built with an interactive web app has also been developed. Any user without any technical knowledge can operate the entire model, which has a 98% accuracy rate. The proposed use case is designed to put AI to work in the healthcare industry, but CloudAISim would be useful and adaptable for other applications in the future.

Structural variants in Lewy body dementia and frontotemporal dementia spectrum

AbstractBackgroundStructural variants range from simple loss or gain of genetic material to complex events that restructure entire chromosomes. This heterogeneity coupled with variant size greater than sequencing read‐length makes structural variant mapping from short‐read sequencing data difficult and error‐prone. Consequently, the role of structural variants is poorly explored in many phenotypes, including dementia.MethodWe used the GATK‐SV pipeline that combines four external structural variant mapping algorithms with machine‐learning to build high‐quality consensus structural variant calls. We applied GATK‐SV to short‐read whole‐genome sequencing data of 2,601 frontotemporal dementia‐amyotrophic lateral sclerosis spectrum (FTD/ALS) patients, 2,612 Lewy body dementia (LBD) patients, and 4,132 neurologically unaffected participants.ResultAfter stringent quality‐control, we performed genome‐wide association studies on 2,307 ALS/FTD patients versus 3,677 controls with 4,699 common structural variants and 2,355 LBD patients versus 3,700 controls with 4,889 common structural variants. In the FTD/ALS cohort, we identified well‐known risk variants at the C9orf72 (p‐value = 4.99×10‐18, OR = 14.47, 95% CI = 7.90–26.49) and MAPT loci (p‐value = 3.48×10‐6, OR = 0.77, 95% CI = 0.68–0.86) corroborating the ability of our pipeline to identify disease‐associated structural variants. Moreover, we discovered, replicated, and validated TPCN1 as a novel risk locus for LBD (p‐value = 9.18×10‐6, OR = 1.43, 95% CI = 1.22–1.67). Further, we identified rare exonic variants with known pathogenic or likely pathogenic effects, such as an SNCA gene duplication in LBD and a deletion of exons 1 and 2 in CHCHD10 in FTD/ALS. We additionally observed structural variants in regulatory regions, e.g. a deletion of a key PSEN2 enhancer, which resulted in an approximate 0.70 fold‐change in PSEN2 expression in LBD. Finally, we built an interactive web app where structural variants can be visualized and explored (https://ndru-ndrs-lng-nih.shinyapps.io/non_ad_dementias_sv_app/).ConclusionCommon and rare structural variants play a role in LBD and FTD/ALS. Our structural variant resource is publicly available and can be used to further explore the role of structural variants in LBD and FTD/ALS.

MarINvaders: A web toolkit of marine species for use in environmental assessments

AbstractInvasive species are the second most important reason for species extinction since 1500 ad. In addition, these invasive species can cause vast economic loss. In marine ecoregions, alien species introductions are increasing, and those that become invasive have caused profound changes in many marine ecoregions. We compiled a database consisting of information about where species are alien, where they are not, and which species are listed as threatened by invasive species. In addition, we developed an interactive Webapp for visualizing and analyzing the results. We used the Ocean Biogeographic Information System (OBIS) for identifying the presence of a species in a marine ecoregion. Information from the World Register of Marine Species (WoRMS), the Global Invasive Species Database (GISD), and the Nature Conservancy database on marine invasive species (NatCon) was used to identify the names and locations of marine alien species. Information from the International Union for Conservation of Nature (IUCN) Red List revealed which species are considered to be threatened by invasive species. Our database lists 112,399 marine species, of which 966 are alien species and 1655 are listed as threatened by invasive species by the IUCN. These are distributed throughout 225 marine ecoregions (97% of marine ecoregions). Our results confirm previous studies about the prevalence of alien and invasive species and provide an up‐to‐date status about known and recorded species and their distribution. This information can be used as a fundament for developing impact assessment models and identifying management strategies to combat marine invasive species.

Health Care Providers' Readiness to Adopt an Interactive 3D Web App in Consultations About Female Genital Mutilation/Cutting: Qualitative Evaluation of a Prototype.

Comprehensive and appropriate health care provision to women and girls with female genital mutilation or cutting (FGM/C) is lacking. Use of visuals in health care provider (HCP) consultations facilitates the communication of health information and its comprehension by patients. A web app featuring a 3D visualization of the genitourinary anatomy was developed to support HCPs in conferring clinical information about FGM/C to patients. The aim of this study was to explore HCP perspectives on the use of visuals in discussion about FGM/C with their patients as well as to obtain their feedback on whether an interactive 3D web app showing the genitourinary anatomy would be helpful in patient consultations about FGM/C, identifying key features that are relevant to their clinical practice. We evaluated the web app through a semistructured interview protocol with seven HCPs from various disciplines experienced in care for women and girls with FGM/C in migration-destination settings. Interviews were audio- and video-recorded for transcription, and were then analyzed thematically for contextualized data regarding HCPs' willingness to use a 3D web app visualizing anatomy in FGM/C consultations with patients. All but one of the seven participants expressed keen interest in using this web app and its 3D visuals of anatomy in FGM/C consultations with patients. Participants shared the common contexts for the use of visuals in health care for FGM/C and the concepts they are used to support, such as to help describe a patient's genitals after FGM/C and reinforce an understanding of clitoral anatomy, to illustrate the process of defibulation, or to explain the physiological effects of FGM/C. Participants also highlighted the benefit of using visuals that patients can relate to, expressing approval for the ability to customize the vulva by FGM/C subtype, skin tone, and complexity of the visual shown in the web app. Despite critiques that the visualization may serve to perpetuate idealistic standards for how a vulva should look, participants largely agreed on the web app's perceived usefulness to clinical practice and beyond. Evaluation of the web app developed in this study identified that digital tools with 3D models of the genitourinary anatomy that are accessible, informative, and customizable to any specific patient are likely to aid HCPs in communicating clinical information about FGM/C in consultations. Universal access to the web app may be particularly useful for HCPs with less experience in FGM/C. The app also prompts options for applications such as for personal use, in medical education, in patient medical records, or in legal settings. Further qualitative research with patients is required to confirm that adoption of the web app by HCPs in a consultation setting will indeed benefit patient care for women and girls with FGM/C.

Paper Sensor Modified with MoS2 for Detection of Dopamine Using a Machine-Intelligent Web App Interface.

The sensing behavior of a MoS2-functionalized paper sensor towards dopamine was explored through a combinatorial approach of theoretical analysis, subsequent experimental validation, and machine-learning-driven predictive modeling of the measured electrochemical outputs. The suitability of the chosen 2D material for efficient detection of dopamine was confirmed using density functional theory. The physisorption behavior along with electrostatic interaction due to the incorporation of dopamine on MoS2 was unraveled under the purview of theoretically estimated noncovalent interaction and charge density difference plot. The theoretical Löwdin population analysis elucidates the alteration in oxidation potential of dopamine, as observed in electrochemical experiments. The electrochemical responses of the developed sensor with the spiked serum samples showed an average accuracy of more than 96% with a limit of detection of 10 nM. Furthermore, implementation of a machine-intelligent interactive web app interface improved the resolution of the sensing platform significantly with an enhanced accuracy of nearly 99%.

Pykanto: A python library to accelerate research on wild bird song

Abstract Studying the vocalisations of wild animals can be a challenge due to the limitations of traditional computational methods, which often are time‐consuming and lack reproducibility. Here, I present pykanto, a new software package that provides a set of tools to build, manage, and explore large sound databases. It can automatically find discrete units in animal vocalisations, perform semi‐supervised labelling of individual repertoires with a new interactive web app and feed data to deep learning models. pykanto can be used to streamline research on, for example, individual vocal signatures and acoustic similarity between individuals and populations. To demonstrate its capabilities, I put the library to the test on the vocalisations of male great tits in Wytham Woods, near Oxford, UK. The results show that the identities of individual birds can be accurately determined from their songs and that the use of pykanto improves the efficiency and reproducibility of the process.

An advanced method to streamline p-hacking

Recent research proposed an efficient way of streamlining p-hacking: a metric of randomly generated p-values that always indicates significant results (pointless). However, the metric’s applicability is limited, since it covers only a very small range of use cases that are relevant for p-hacking researchers. To address this issue, we present extra pointless, a new metric that allows researchers to freely specify desired p-value ranges while safeguarding full reproducibility. Our newly introduced extra pointless metric not only addresses the limitations of the original metric but also answers editors’ and reviewers’ calls for alternative and innovative statistical approaches. An R-based, interactive shiny web app helps researchers with little background in coding to apply our metric.

Abstract 1452: Big data analysis revealed signalling activity and key regulators in human prostate cancer cell lines

Abstract Background: Human prostate cancer (PCa) cell lines are the most used models for research. The commonly used PCa cell lines can be roughly categorized into 3 groups: androgen receptor (AR)+, neuroendocrine (NE)+ and double negative (AR- NE-) cell lines. However, although these cell lines have been extensively used in PCa research since their establishment decades ago, a global molecular characterization of these cell lines is still lacking, especially in the aspect of cell signaling activity and their clinical relevance, which requires a large scale of data mining. Methods: The RNA-seq, DNA-seq and proteomic datasets were gathered from public cohort and our lab’s collection. From these data, a PCa cell line multi-omics database (PCMD) was established. Single sample gene set enrichment analysis (ssGSEA) was used to reveal the signaling pathways enriched in each PCa cell line. Additionally, human PCa patient single cell RNAseq data-based deconvolution and human PCa patient bulk RNAseq data-based nearest-neighbor (NN) graph analysis were used to evaluate the clinical relevance of each PCa cell line. The DNA-seq, ATAC-seq, DNase HS-seq and Bisulfite-seq datasets were used to annotate the key genes. Results: The PCMD database was established by compiling more than 1000 RNASeq datasets derived from various PCa cell lines. The important signaling pathways and transcription factors were revealed for each PCa cell line. Further, the cell lines were annotated with relative clinical stages. Additionally, an interactive webApp was established for scientists to explore and visualize PCMD data. Conclusion: our research characterized PCa cell lines using unbiased strategies and large sample number. It is our hope that this study would aid researchers to develop hypothesis and choose appropriate cell line to use. Funding: This study is supported by: Feist-Weiller Cancer Center, LSU Health Shreveport. Citation Format: Siyuan Cheng, Lin Li, Xiuping Yu. Big data analysis revealed signalling activity and key regulators in human prostate cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1452.