MultiQC_TestData - Test data for MultiQC. See https://github.com/ewels/MultiQC

  •        20

MultiQC is a tool to aggregate bioinformatics results across many samples into a single report. This repository contains files to test MultiQC with. These are used in the automated Travis CI build tests and can be used whilst developing for MultiQC.

https://github.com/ewels/MultiQC_TestData

Tags
Implementation
License
Platform

   




Related Projects

MultiQC - Aggregate results from bioinformatics analyses across many samples into a single report.

  •    Python

MultiQC is a tool to create a single report with interactive plots for multiple bioinformatics analyses across many samples. MultiQC is written in Python (tested with v2.7, 3.4, 3.5 and 3.6). It is available on the Python Package Index and through conda using Bioconda.

Awesome-Bioinformatics - A curated list of awesome Bioinformatics libraries and software.

  •    

Sequence Processing includes tasks such as demultiplexing raw read data, and trimming low quality bases. The following tools can be used to visualize genomic data or for constructing customized visualizations of genomic data including sequence data from DNA-Seq, RNA-Seq, and ChIP-Seq, variants, and more.

nextflow - A DSL for data-driven computational pipelines

  •    Groovy

With the rise of big data, techniques to analyse and run experiments on large datasets are increasingly necessary. Parallelization and distributed computing are the best ways to tackle this kind of problem, but the tools commonly available to the bioinformatics community traditionally lack good support for these techniques, or provide a model that fits badly with the specific requirements in the bioinformatics domain and, most of the time, require the knowledge of complex tools or low-level APIs.

Bio4j - Bioinformatics Graph based DB

  •    Java

Bio4j is a bioinformatics graph based DB including most data available in Uniprot KB (SwissProt + Trembl), Gene Ontology (GO), UniRef (50,90,100), RefSeq, NCBI Taxonomy, and Expasy Enzyme DB. Bio4j provides a completely new and powerful framework for protein related information querying and management. Since it relies on a high-performance graph engine, data is stored in a way that semantically represents its own structure.

Bioinformatics-Training - Bioinformatics training resources

  •    R

This is a resource for learning more about PacBio data and bioinformatics analysis. THIS WEBSITE AND CONTENT AND ALL SITE-RELATED SERVICES, INCLUDING ANY DATA, ARE PROVIDED "AS IS," WITH ALL FAULTS, WITH NO REPRESENTATIONS OR WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTIES OF MERCHANTABILITY, SATISFACTORY QUALITY, NON-INFRINGEMENT OR FITNESS FOR A PARTICULAR PURPOSE. YOU ASSUME TOTAL RESPONSIBILITY AND RISK FOR YOUR USE OF THIS SITE, ALL SITE-RELATED SERVICES, AND ANY THIRD PARTY WEBSITES OR APPLICATIONS. NO ORAL OR WRITTEN INFORMATION OR ADVICE SHALL CREATE A WARRANTY OF ANY KIND. ANY REFERENCES TO SPECIFIC PRODUCTS OR SERVICES ON THE WEBSITES DO NOT CONSTITUTE OR IMPLY A RECOMMENDATION OR ENDORSEMENT BY PACIFIC BIOSCIENCES.


csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang

  •    Go

Similar to FASTA/Q format in field of Bioinformatics, CSV/TSV formats are basic and ubiquitous file formats in both Bioinformatics and data sicence. People usually use spreadsheet softwares like MS Excel to do process table data. However it's all by clicking and typing, which is not automatically and time-consuming to repeat, especially when we want to apply similar operations with different datasets or purposes.

reflow - A language and runtime for distributed, incremental data processing in the cloud

  •    Go

Reflow is a system for incremental data processing in the cloud. Reflow enables scientists and engineers to compose existing tools (packaged in Docker images) using ordinary programming constructs. Reflow then evaluates these programs in a cloud environment, transparently parallelizing work and memoizing results. Reflow was created at GRAIL to manage our NGS (next generation sequencing) bioinformatics workloads on AWS, but has also been used for many other applications, including model training and ad-hoc data analyses. Reflow thus allows scientists and engineers to write straightforward programs and then have them transparently executed in a cloud environment. Programs are automatically parallelized and distributed across multiple machines, and redundant computations (even across runs and users) are eliminated by its memoization cache. Reflow evaluates its programs incrementally: whenever the input data or program changes, only those outputs that depend on the changed data or code are recomputed.

BioDWH: Bioinformatics Data Warehouse

  •    Java

BioDWH is a bioinformatics data warehouse software kit that integrates biological information from multiple public life science data sources into a local RDBMS. It provides up-to-date integrated knowledge, platform and database independence.

awesome - Awesome resources on Bioinformatics, data science, machine learning, programming language (Python, Golang, R, Perl) and miscellaneous stuff

  •    

Collection of useful resources on Bioinformatics, data science, machine learning, programming language (Python, Golang, R, Perl, etc.) and miscellaneous stuff.

EDAM Ontology

  •    

EDAM is a bioinformatics tools and data ontology. Its defined terms and relationships provide a structured, controlled vocabulary to describe in semantic terms bioinformatics web services, data schema, tools, web servers, databases and so on.

BioJava - Java Framework for Processing Biological Data

  •    Java

BioJava is an open-source project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

rust-bio - This library provides implementations of many algorithms and data structures that are useful for bioinformatics

  •    Rust

This library provides implementations of many algorithms and data structures that are useful for bioinformatics. All provided implementations are rigorously tested via continuous integration. Please see the homepage for examples and documentation.

scikit-bio - scikit-bio is an open-source, BSD-licensed, Python package providing data structures, algorithms, and educational resources for bioinformatics

  •    Python

scikit-bio is an open-source, BSD-licensed Python 3 package providing data structures, algorithms and educational resources for bioinformatics. To view scikit-bio's documentation, visit scikit-bio.org.

awesome-single-cell - List of software packages for single-cell data analysis, including RNA-seq, ATAC-seq, etc

  •    

List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Contributions welcome... Gender bias at conferences is a well known problem (http://www.sciencemag.org/careers/2015/07/countering-gender-bias-conferences). Creating a list of potential speakers can help mitigate this bias and a community of people developing and maintaining helps to further diversify this list beyond smaller networks.

MicroArray Explorer

  •    Java

Microarray Explorer (MAExplorer) is a Java microarray data-mining bioinformatics program. It includes data management, graphics, statistics, clustering, reports, gene data-filtering, user written MAEPlugins, documentation, tutorials, demo data.

XEML

  •    DotNet

Welcome to the XEML project page. This project aims to realize a standard for the control and documentation of experimental design and growth, with a maximum of power in terms of data processing, not only to obtain reliable molecular and physiological data, but also to make plant

dash - Interactive, Reactive Web Apps for Python. Dash Is Productive™

  •    Python

Build on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical python code. Here’s a 43-line example of a Dash App that ties a Dropdown to a D3.js Plotly Graph. As the user selects a value in the Dropdown, the application code dynamically exports data from Google Finance into a Pandas DataFrame. This app was written in just 43 lines of code (view the source).

Test Data Generator

  •    

Testdata is a configurable, customizable tool that generates test data. Values can be generated in arbitrary sequences and placed in tabular, tree, and other data structures. Multiple output formats are supported, including XML.

BioSharp

  •    DotNet

BioSharp is a pure and test-driven .NET library for use in bioinformatics and related fields.