Search Results for "data" - Page 3
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Showing 102 open source projects for "data"
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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MHNs Data Science Examples
Collection of data science examples.
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vitae
R Markdown Résumés and CVs
vitae is an R package that streamlines resume and CV creation via R Markdown. It includes a collection of LaTeX and HTML templates along with helper functions to dynamically populate content from data sources such as ORCID or spreadsheets. -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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Awesome Network Analysis
A curated list of awesome network analysis resources
...It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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psychmeta
Psychometric meta-analysis toolkit
The psychmeta package provides tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Currently, the package supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Please refer to the overview tutorial vignette for an introduction to psychmeta’s functions and workflows. psychmeta is hosted on both CRAN and GitHub. -
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Statistical Rethinking 2024
This course teaches data analysis
The 2024 repository is the most recent version of the course, reflecting ongoing refinements in pedagogy, statistical modeling techniques, and coding practices. It provides updated notebooks, R scripts, and model examples, some streamlined and restructured compared to previous years. The 2024 repo also highlights the transition toward more robust Stan models and integration with newer Bayesian workflow practices, continuing to emphasize accessibility for learners while modernizing the tools.... -
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ggthemes
Additional themes, scales, and geoms for ggplot2
...It is often used to make ggplot2 plots adhere to aesthetic styles from famous news outlets, scientific journals, or presentation decks. Additional color scales and palettes for discrete and continuous data to match theme aesthetics. Extensive documentation and examples for each theme / scale so users can see how plots look and tweak them. -
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Statistical Rethinking 2023
Statistical Rethinking Course for Jan-Mar 2023
...It continues to provide scripts for lectures and tutorials, while integrating refinements to examples, notation, and computational workflows introduced that year. Compared with 2022, some models are rewritten for clarity, and teaching materials reflect refinements in McElreath’s evolving presentation of Bayesian data analysis. Students following the 2023 lecture videos use this repository as their coding reference. There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting. -
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MetEx
MetEx is a computational tool for metabolite targered extraction and a
...The new annotation method based on targeted extraction algorithms can annotate more than 2 times metabolites than classical peak detection-based annotation method because it reduces the loss of metabolite signal in the data preprocessing process. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Amplicon_Sequencing_Worfklow
Analyzing amplicon data from sequences to stats
This is a collection of scripts and instructions on how to analyzing amplicon sequence data (i.e., 16S, ITS2, & other marker genes). I created this workflow to create a consistent set of methods for analyzing amplicon sequence data, from when you first receive the sequence data to statistical analyses & data visualization. All you need is to have the latest version of R installed, some experience with the command line & shell, and enough memory to run all of the programs. ... -
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AI-Agent-Host
The AI Agent Host is a module-based development environment.
...Being data-aware involves connecting a language model to other sources of data, enabling a comprehensive understanding and analysis of information. -
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tidyverse
Easily install and load packages from the tidyverse
tidyverse is a meta‑package that installs and loads a cohesive suite of R packages designed for data science, sharing underlying design principles, grammar, and data structures. Core components include ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, forcats, and more. It promotes tidy data workflows and consistency across tasks. -
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latex2exp
Use LaTeX in R graphics
latex2exp is an R package that lets you use LaTeX in plots. It parses and converts LaTeX to R’s custom plotmath expressions. You can read the full documentation on the package’s website. Expressions returned by latex2exp can be used to create formatted text and mathematical formulas and symbols to be rendered as axis labels, annotations, legends, titles, etc. throughout R’s plotting system. -
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methylr
a single shiny solution from sequencer data to pathway analysis
Here we introduce methylR, a complete pipeline for the analysis of both 450K and EPIC Illumina arrays which not only offers data visualization and normalization but also provide additional features such as the annotation of the genomic features resulting from the analysis, pairwise comparisons of DMCs with different graphical representation plus functional and pathway enrichment as downstream analysis, all packed in a minimal, elegant and intuitive graphical user interface which brings the analysis of array DNA methylation data. -
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activAnalyzer is a Shiny app that has been developed to analyze daily physical behavior data recorded at the hip in adults using an ActiGraph accelerometer (.agd file from a GT3X, GT3X+, wGT3X+ or wGT3X-BT device). Once analysis is completed, the app allows exporting results to .csv files and generating a report of the measurement (in either an .html format or a .pdf format). All the configured inputs relevant for interpreting the results are recorded in the report.
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hui
hewies user interface - 3D scientific visualisation tool
Python project with goal to provide FOSS library to extract, analyse and visualise data in a 3D fashion. The instance will connect to a data source, ods sheet, csv, sql DB, pyodbc the instance will analyse and/or transform the data to be presented to the visualisation functionality the instance will visualise the data in a 3D fashion, likely using third party FOSS -
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant... -
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Data Analysis for the Life Sciences
Rmd source files for the HarvardX series PH525x
This repository holds the R Markdown (.Rmd) source files for the PH525x / HarvardX course series (Data Analysis for the Life Sciences / Genomics) managed by GenomicsClass. It functions as the canonical source for course lab exercises, lecture modules, and reading materials in reproducible format. Students and learners use these R Markdown files to follow along, knit notebooks, run code samples, and complete the lab-based assignments. -
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mlr
Machine Learning in R
R does not define a standardized interface for its machine-learning algorithms. Therefore, for any non-trivial experiments, you need to write lengthy, tedious, and error-prone wrappers to call the different algorithms and unify their respective output. {mlr} provides this infrastructure so that you can focus on your experiments! The framework provides supervised methods like classification, regression, and survival analysis along with their corresponding evaluation and optimization methods,... -
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geocompr
Geocomputation with R: an open source book
This repository hosts the source for Geocomputation with R, an open-source book covering spatial data analysis, visualization, and modeling using R. It teaches how to work with vector and raster data, coordinate systems, mapping, and geocomputation techniques using packages like sf, terra, tmap, and more. Actively maintained and updated for real-world geospatial workflows. -
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Statistical Rethinking 2022
Statistical Rethinking course winter 2022
This repository hosts the 2022 version of the Statistical Rethinking course. It contains course materials such as R scripts, notebooks, and worked examples aligned with McElreath’s textbook. The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a direct hands-on reference for students following the 2022 recorded lecture series. ... -
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Statistics for Data Scientists
"Statistics for Data Scientists: 50 Essential Concepts"
The “statistics-for-data-scientists” repository is a pedagogical resource designed to bridge rigorous statistics theory and practical data science workflows. The code and materials are intended to help data scientists and analysts grasp statistical principles (e.g. inference, regressions, hypothesis testing, probability, confidence intervals) in contexts relevant to real data analysis tasks. -
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KidneyExplorer
Kidney proteomics data explorer enables you to investigate diseases
KidneyExplorer enables you to interactively survey kidney proteomics datasets from different kidney disease models. Here you can download the corresponding SQL database dumps. The original website for the shiny app is: https://kidneyapp.shinyapps.io/kidneyorganoids/ -
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QuantifyPoly(A)
Quantification of poly(A) sites from 3' end sequencing data
QuantifyPoly(A) - a tool for quantification of poly(A) sites from 3' end sequencing data. [1] QuantifyPoly(A) user manual Please visit the Wiki page of this website. [2] QuantifyPoly(A) Q&A For Q&A, please visit the Blog page of this website. [3] QuantifyPoly(A) bug report You can report a bug as a Ticket request, or start a topic session in the Discussion webpage of this website. -
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R4DS (R for Data Science)
R for data science: a book
...Includes many example datasets, diagrams, code samples, and “hands-on” exercises. Comprehensive coverage of data-science workflow: data import, cleaning, transformation, exploration, modelling etc. Includes topics beyond basics: relational data (joins), date/time, strings, working with missing values, visualizing data, etc.