THRESHOLD is an advanced gene saturation analysis tool designed to uncover meaningful patterns in gene expression data across large transcriptomic datasets. By analyzing upregulated and downregulated genes, THRESHOLD provides insights into disease mechanisms, therapeutic targets, and cellular responses. Equipped with customizable parameters such as saturation type, restriction factors, and rank type, the tool delivers interactive saturation graphs to identify critical expression thresholds and pinpoint the most saturated genes.
Beyond gene identification, THRESHOLD supports key research domains, including disease differentiation, discovery of genetic markers, and early detection of disease indicators. Its dual analysis modes—Incremental Saturation for step-by-step expression pattern analysis and Overall Saturation for a comprehensive overview—empower researchers to explore the genomic landscape with precision and clarity.
With its user-friendly interface and powerful analytical capabilities, THRESHOLD serves as a valuable resource for advancing our understanding of gene expression dynamics, driving progress in personalized medicine, and informing future healthcare innovations. THRESHOLD is available at GitHub (https://github.com/alperuzun/THRESHOLD)
THRESHOLD is available as a preprint at bioRxiv, October 22, 2024.
Proteinarium 2 (P2) is a multi-sample protein–protein interaction (PPI) tool to identify clusters of patients with shared networks to better understand the mechanism of complex diseases and phenotypes. This tool was designed to enhance the analysis of experimental data by identifying disease associated biological networks that define clusters of patients, as well as the visualization of such networks with user specified parameters. P2 now is available as a webtool. It covers multiple PPI databases and has user frendly interactive interface with additional functionalities and analysis. P2 is available at https://proteinarium.brown.edu/
VIVA (Visualization of Variants) is a user-friendly command line tool for creating publication quality graphics from Variant Call Format (VCF) files. It has been designed for clinicians and bioinformaticians to explore their VCF files visually. In a single command, users can extract genotype or read depth information and plot trends in interactive categorical heatmaps and scatter plots of average read depth values. VIVA offers a robust set of filters to select variants and samples of interest for analysis. VIVA is especially useful in early data exploration for identifying batch effect and sources of poor read depth in sequencing experiments, as well as identifying distribution of disease causing variants in a set of clinical samples.
You can download VIVA from this link (https://github.com/compbiocore/VariantVisualization.jl).
Published in Scientific Reports on Sept 2, 2019.
Proteinarium (Multi-Sample Protein-Protein Interaction Analysis and Visualization Tool) is a multi-sample protein-protein interaction network analysis and visualization tool. Proteinarium was specifically designed to analyze multi-sample gene lists. Proteinarium’s input can be derived from transcriptome analysis, whole exome sequencing data or any high-throughput screening approach. Its strength lies in use of gene lists for each sample as a distinct input which are further analyzed through protein interaction analyses. Proteinarium is a command-line tool written entirely in Java with no external dependencies. Java version 8 or above (Java 9, or Java 10) must be installed in order to run Proteinarium.
Proteinarium is freely available at this link (https://github.com/alperuzun/Proteinarium/).
Published in Genomics on July 15, 2020.
Database for Preeclampsia (dbPEC) contains published literature and associated genes for preeclampsia. Articles were manually reviewed by trained curators. Extracted genes associated with preeclampsia or severe preeclampsia, early or late onset, maternal or fetal tissue sources, and concurrent conditions (ie, IUGR, gestational hypertension, or hemolysis, elevated liver enzymes, and low platelet count [HELLP]) are documented.
dbPEC can be accessed from this link –> dbPEC (https://dbpec.brown.edu/index.php)
Published in DATABASE on Mar 5, 2016
The Database for Preterm Birth (dbPTB) is a web-based aggregation tool to organize the genes, genetic variations and pathways involved in preterm birth, dbPTB. We used semantic data mining to extract all published articles related to preterm birth. All articles were reviewed by a team of curators. Genes identified from public databases and archives of expression arrays were aggregated with genes curated from the literature.
dbPTB can be accessed from this link –> dbPTB (https://dbptb.brown.edu/)
Published in DATABASE on Feb 8, 2012.
