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A catalogue of available long read sequencing data analysis tools
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README.md

scRNA-tools

long-read-tools

Project Status Lifecycle

A database of software tools for the analysis of long read sequencing data. To make it into the database software must be available for download and public use somewhere (CRAN, Bioconductor, PyPI, Conda, GitHub, Bitbucket, a private website etc). To view the database head to https://www.long-read-tools.org.

Purpose

This database is designed to be an overview of the currently available long read analysis software, it is unlikely to be 100% complete or accurate but will be updated as new software becomes available. If you notice a problem or would like to add something please make a pull request or open an issue.

Citation

The manuscript is currently under development. However, if you find the long-read-tools database useful for your work you could still cite our database(e.g. Walter and Eliza Hall Institute of Medical Research. (2018). long-read-tools [database]. Retrieved from http://www.long-read-tools.org).

Structure

The main tools table has the following columns:

  • Name
  • Platform - Programming language or platform where it can be used
  • DOIs - Publication DOIs separated by semi-colons
  • PubDates - Publication dates separated with semi-colons. Preprints are marked with PREPRINT and will be updated when published.
  • Code - URL for publicly available code.
  • Description
  • License - Software license
  • Technologies in Focus - Long read sequencing technologies of the data available tools are developed for
  • Categories (Described below)

Categories

The categories are TRUE/FALSE columns on the lrs_tools_master.csv indicating if the software has a particular function. These are designed to be used as filters, for example when looking for software to accomplish a particular task. They are also the most likely to be inaccurate as software is frequently updated and it is hard to judge all the functions a package has without making significant use of it. You wil see that there some tools hve been reported for multiple categories. The categories are assigned based on whether the tool:

  • Alignment - Aligns long reads to a reference
  • BaseCalling - Detects of change of electrical current produced by ONT sequencers and translate it to a DNA sequence
  • LongReadOverlapping - Finds pairs of reads that align to each other
  • DenovoAssembly - Assembles long reads
  • GeneratingConsensusSequence - Generate a consensus sequence from the assembled reads
  • AnalysisPipelines - Is a pipelines that include several tools
  • ErrorCorrectionAndPolishing - Corrects the errors to improve the genome assembly or reads before assembly. Some use a hybrid method of using short reads to achieve long reads with high accuracy
  • GeneExpressionAnalysis - Tests of differential expression across samples
  • EvaluatingExisitingMethods - Benchmarks and/or evaluates functionality of existing tools and/or generating synthetic long read datasets
  • GapFilling - Improves existing assemblies based on localised alignment and assembly
  • IsoformDetection - Identifies multiple isoforms encoded by a single gene due to alternative splicing
  • BaseModicifactionDetection - Identifies modifications to individual bases like 5-methylcytosine, 5-hydroxymethylcytosine, and N6-methyladenine in DNA sequences
  • ProvideSummaryStatistics - Provides statistics that could be looked at to evaluate the quality of data
  • QualityChecking - Provides a measure of the quality of the reads
  • QualityFiltering - Removes low quality reads based on a specified quality threshold
  • Metagenomics - Is used for studying genetic material recovered directly from environmental samples
  • Simulators - Simulates a sequencing process and produce in-silico reads
  • Demultiplexing - Uses barcode or other information to know which sequences came from which samples in a pool of samples
  • Normalisation - Removes unwanted variation that may affect results
  • QualityTrimming - Removes low-quality reads
  • ReadQuantification - Quantifies of expression from reads
  • SuitableForSingleCellExperiments - Can be used for analysing/processing single-cell data generated by long read sequencing platforms
  • TestedOnHumanData - Provides evidence in publications to have been successfully employed to analyse human data
  • TestedOnNonHumanData - Provides evidence in publications to have been successfully employed to analyse non-human data
  • SNPAndVariantAnalysis - Detects or uses variants
  • Visualisation - Visualises some aspect of long read data or analysis

Contributors

Thank you to everyone who has contributed to long-read-tools! Your efforts to build and improve this resource for the community are greatly appreciated!

The following people have made significant contributions to the long-read-tools database or website:

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