Search Results for "disease"
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Showing 12 open source projects for "disease"
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clusterProfiler
A universal enrichment tool for interpreting omics data
...It supports both over-representation analysis and gene set enrichment analysis, letting you work with unranked gene lists or ranked statistics from differential pipelines. The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. It is designed for breadth, covering coding and non-coding features and thousands of organisms by leveraging continuously updated annotations. Results are returned in tidy, manipulation-friendly structures and pair naturally with rich visualization functions (via companion tooling) to summarize pathways, terms, and gene–set relationships. -
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OptiMIClass
Automatic n-dimensional data clustering tool powered by five advanced
...The software was a direct outcome of “Combinatorial optimization heuristics for data classification” (Code: 5402-1440-3901), and its development continued within the related project “Disease propagation: heuristics applied to optimizing control measures” (Code: 540114404201). -
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PANDORA
Revolutionizing Biomedical Research with Advanced Machine Learning
PANDORA is a machine learning (ML) tool that can be used to integrate various data types, including clinical, transcriptome and microbiome data and find connections in large datasets. PANDORA can be easily installed using Docker, a pre-built version of the software can be pulled from DockerHub. In order to run a test instance of PANDORA, users will first need to prepare their local environment by downloading, installing, and configuring Docker. genular is a community behind SIMON an... -
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scArches
Reference mapping for single-cell genomics
Single-cell architecture surgery (scArches) is a package for reference-based analysis of single-cell data. scArches allows your single-cell query data to be analyzed by integrating it into a reference atlas. By mapping your data into an integrated reference you can transfer cell-type annotation from reference to query, identify disease states by mapping to healthy atlas, and advanced applications such as imputing missing data modalities or spatial locations. -
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Hetionet
Hetionet: an integrative network of disease
Hetionet is a hetnet — network with multiple node and edge (relationship) types — which encodes biology. The hetnet was designed for Project Rephetio, which aims to systematically identify why drugs work and predict new therapies for drugs. The JSON and Neo4j formats contain node and edge properties, which are absent in the TSV and matrix formats, including licensing information. Therefore the recommended formats are JSON and Neo4j. Our hetio package in Python reads the JSON format, but it... -
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decd
R package for complex disease analysis
This is a R packages designed for complex disease when large scale expression data is available -
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CVDdb
Cerebrovascular Disease database
Our integrated database schema is an add-on schema to Loris (http://loris.ca/, Das et al, 2011), and includes 3079 subjects and over 550 federated and searchable data items including imaging details, medical history and examination, stroke and laboratory details, which maps to large multi-centre stroke trials with imaging data from over 10,000 patients from 30 countries. Here we provide our current version of our schema, and data dictionary. The data itself is for internal access only during... -
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Random Bits Regression
Random Bits Regression is a strong general predictor.
...The accuracy and robustness improvement of our method over existing method could bring huge benefits in some critical applications. For example, natural disaster prediction, stock price prediction, personal/population disease prediction. The fast-speed nature of our method not only allows big data analysis but also enables real-time recognition and predictions. The RBR framework also hints the mechanism of brain function and leads to a "wide learning" hypothesis. We believe that this method will make a great impact and enable many downstream applications. -
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ExAM-Exome_Analysis_And_Mining
A whole exome sequencing analysis package and its graphical interface
...Here, we present an interactive and free analysis package, ExAM, dedicated to whole exome sequencing data analysis. It is accessible to non-computer scientists and provides a complete set of information, as well as decision support to prioritize candidate disease causing variants. -
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HomSI
Homozygous Stretch Identifier from next-generation sequencing data
...This situation leads to the prevalence of recessive diseases among the members of these families. Homozygosity mapping is based on this observation and several recessive disease genes have been discovered with the help of this technique in consanguineous families. The researchers typically use SNP arrays to determine the homozygous regions and then search for the disease gene by sequencing the genes within this candidate disease loci. Recently, the advent of next generation sequencing enables the concurrent identification of homozygous regions and the detection of mutations relevant for diagnosis, using data from a single sequencing experiment. ... -
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Snp Viewer
A program for visualising Affymetrix SNP array data
A program for visualising Affymetrix SNP array data for identification regions of homozygosity. Written to aid autozygosity mapping and aid the discovery of potential disease loci. -
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This disease-centric project contributes data integration and analysis tools from the Institute for Systems Biology (ISB). We offer this project to the research community to further our efforts in disease prediction and prevention.
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