Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-nanopore
A curated list of awesome nanopore analysis tools.
https://github.com/GoekeLab/awesome-nanopore
Last synced: 1 day ago
JSON representation
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Software packages
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Basecalling
- Close sourced (May request code by emailing [email protected])
- Dorado - [C++] - Production basecaller from 2022, successor to Guppy.
- Nanocall - [C++] - [Nanocall: an open source basecaller for Oxford Nanopore sequencing data](https://academic.oup.com/bioinformatics/article/33/1/49/2525680)
- PoreSeq - [C++] - [De novo sequencing and variant calling with nanopores using PoreSeq](https://www.nature.com/articles/nbt.3360)
- Nanonet - [C++] - [Nanonet - Development version of RNN basecaller](https://github.com/ProgramFiles/nanonet)
- DeepNano - [Python] - [DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0178751)
- Chiron - [Python] - [Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning](https://academic.oup.com/gigascience/article/7/5/giy037/4966989)
- Causalcall - [Python] - [Causalcall: Nanopore Basecalling Using a Temporal Convolutional Network](https://www.frontiersin.org/articles/10.3389/fgene.2019.01332/full)
- Bonito - [Python] - A PyTorch Basecaller for Oxford Nanopore Reads (research, not production basecaller)
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Segmentation
- tombo resquiggle - [Python] - [Re-squiggle Algorithm](https://nanoporetech.github.io/tombo/resquiggle.html).
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Raw signal data manipulation, conversion, visualisation, etc.
- pyslow5 - [Python] - [pyslow5 python library
- slow5lib - [C] - [Fast nanopore sequencing data analysis with SLOW5
- slow5tools - [C/C++] - [Toolkit for converting (FAST5 <-> SLOW5), compressing, viewing, indexing and manipulating data in SLOW5 format](https://hasindu2008.github.io/slow5tools/)
- SquiggleKit SquigglePlot - [Python] - [SquiggleKit: a toolkit for manipulating nanopore signal data](https://academic.oup.com/bioinformatics/article/35/24/5372/5537108)
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Adaptive sampling / ReadUntil Real-time mapping / signal mapping
- Readfish - [Python] - [Readfish enables targeted nanopore sequencing of gigabase-sized genomes](https://www.nature.com/articles/s41587-020-00746-x)
- UNCALLED - [C++] - [Targeted nanopore sequencing by real-time mapping of raw electrical signal with UNCALLED](https://www.nature.com/articles/s41587-020-0731-9)
- SquiggleNet - [Python] - [Real-Time, Direct Classification of Nanopore Signals with SquiggleNet](https://www.biorxiv.org/content/10.1101/2021.01.15.426907v2)
- Sigmap - [C/C++] - [Real-time mapping of nanopore raw signals
- cwDTW - [C/C++] - [An accurate and rapid continuous wavelet dynamic time warping algorithm for end-to-end mapping in ultra-long nanopore sequencing](https://academic.oup.com/bioinformatics/article/34/17/i722/5093233)
- OpenDBA - [C++/CUDA] - [GPU-accelerated Dynamic Time Warp (DTW) Barycenter Averaging](https://github.com/nodrogluap/OpenDBA#how-do-i-use-this-for-oxford-nanopore-data)
- Magenta & Maxwell - [C++/CUDA] - [Fast signal-level matching for direct RNA nanopore sequencing](https://github.com/nodrogluap/maxwell)
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RNA modification analysis
- DiffErr - [Python] - A tool for detecting modifications from Nanopore DRS errors using a low modification control.
- MINES - [Python] - [Direct RNA sequencing enables m6A detection in endogenous transcript isoforms at base specific resolution](https://rnajournal.cshlp.org/content/early/2019/10/17/rna.072785.119).
- EpiNano - [Python] - [Accurate detection of m6A RNA modifications in native RNA sequences](https://www.nature.com/articles/s41467-019-11713-9).
- Nanom6A - [Python] - [Quantitative profiling of N6-methyladenosine at single-base resolution in stem-differentiating xylem of Populus trichocarpa using Nanopore direct RNA sequencing](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-020-02241-7).
- m6anet - [Python] - [Detection of m6A from direct RNA sequencing using a multiple instance learning framework](https://www.nature.com/articles/s41592-022-01666-1).
- nano-ID - [R] - [Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms](https://genome.cshlp.org/content/30/9/1332.full).
- nanoRMS - [Python] - [Quantitative profiling of pseudouridylation dynamics in native RNAs with nanopore sequencing](https://www.nature.com/articles/s41587-021-00915-6?proof=t%3B).
- Yanocomp - [Python] - [Yanocomp: robust prediction of m6A modifications in individual nanopore direct RNA reads](https://www.biorxiv.org/content/10.1101/2021.06.15.448494v1).
- ELIGOS - [Python] - [Decoding the epitranscriptional landscape from native RNA sequences](https://academic.oup.com/nar/article/49/2/e7/5876284).
- nanoDoc - [Python] - [nanoDoc: RNA modification detection using Nanopore raw reads with Deep One-Class Classification](https://www.biorxiv.org/content/10.1101/2020.09.13.295089v1).
- nanocompore - [Python] - [RNA modifications detection by comparative Nanopore direct RNA sequencing](https://www.biorxiv.org/content/10.1101/843136v1).
- DRUMMER - [Python] - [Direct RNA sequencing reveals m6A modifications on adenovirus RNA are necessary for efficient splicing](https://www.nature.com/articles/s41467-020-19787-6.pdf?origin=ppub).
- xPore - [Python] - [Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore](https://doi.org/10.1038/s41587-021-00949-w).
- tombo detect_modifications - [Python] - [Modified Base Detection](https://nanoporetech.github.io/tombo/modified_base_detection.html).
- Magnipore - [Python] - [Magnipore: Prediction of differential single nucleotide changes in the Oxford Nanopore Technologies sequencing signal of SARS-CoV-2 samples](https://doi.org/10.1101/2023.03.17.533105)
- DENA - [Python/R] - [DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N6-methyladenosine on RNA](https://doi.org/10.1186/s13059-021-02598-3)
- mAFiA - [Python] - [Detecting m6A at single-molecular resolution via direct RNA sequencing and realistic training data](https://doi.org/10.1038/s41467-024-47661-2)
- Penguin - [Python] - [Penguin: A Tool for Predicting Pseudouridine Sites in Direct RNA Nanopore Sequencing Data](https://doi.org/10.1016/j.ymeth.2022.02.005)
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DNA modification analysis
- modkit - [Rust] - Extract modified base calls from dorado BAM output to bedMethyl format, also calculate DMRs
- Megalodon - [C++] - Research modified base caller which uses rerio, remora and a genome (deprecated by ONT 2023 for Dorado).
- modbam2bed - [C++] - Convert modified base calls from megalodon etc to bedMethyl format (deprecated by ONT 2023 for Modkit)
- nanoNOMe - [Python] - [Simultaneous profiling of chromatin accessibility and methylation on human cell lines with nanopore sequencing](https://www.nature.com/articles/s41592-020-01000-7).
- signalAlign - [C] - [Mapping DNA methylation with high-throughput nanopore sequencing](https://www.nature.com/articles/nmeth.4189).
- mCaller - [Python] - [Single-molecule sequencing detection of N6-methyladenine in microbial reference materials](https://www.nature.com/articles/s41467-019-08289-9).
- DeepSignals - [Python] - [DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning](https://academic.oup.com/bioinformatics/article/35/22/4586/5474907).
- NanoMod - [Python] - [NanoMod: a computational tool to detect DNA modifications using Nanopore long-read sequencing data](https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-5372-8).
- f5c call-methylation - [C/C++/CUDA] - [GPU accelerated adaptive banded event alignment for rapid comparative nanopore signal analysis](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03697-x)
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RNA structure prediction
- nanoSHAPE - [Python] - [Direct detection of RNA modifications and structure using single molecule nanopore sequencing](https://www.biiorxiv.org/content/10.1101/2020.05.31.126763v1).
- PORE-cupine - [R] - [Determination of isoform-specific RNA structure with nanopore long reads](https://www.nature.com/articles/s41587-020-0712-z).
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Poly(A) tail length estimation
- tailfindr - [R] - [tailfindr: Alignment-free poly(A) length measurement for Oxford Nanopore RNA and DNA sequencing](https://rnajournal.cshlp.org/content/early/2019/07/02/rna.071332.119).
- nanopolish polya - [C++] - [Nanopore native RNA sequencing of a human poly(A) transcriptome](https://www.nature.com/articles/s41592-019-0617-2?proof=t).
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Transcript discovery and quantification
- RNAbloom2 - [Java] - [Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2](https://www.nature.com/articles/s41467-023-38553-y)
- RATTLE - [C++] - [RATTLE: reference-free reconstruction and quantification of transcriptomes from Nanopore sequencing](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02715-w)
- bambu - [R] - [Context-Aware Transcript Quantification from Long Read RNA-Seq data with Bambu](https://rdcu.be/deluQ)
- NanoSplicer - [Python] - [Identification of splice junctions from nanopore sequencing using raw signal squiggles](https://academic.oup.com/bioinformatics/article/38/15/3741/6594111)
- TALON - [Python] - [Python package for identifying and quantifying known and novel genes/isoforms in long-read transcriptome data sets](https://www.biorxiv.org/content/10.1101/672931v2) **Run before** [TranscriptClean](https://github.com/mortazavilab/TranscriptClean)
- trackcluster - [Python] - [trackcluster is an isoform calling and quantification pipeline for long RNA/cDNA reads](https://genome.cshlp.org/content/30/2/287.short)
- FLAIR - [Python] - [Full-Length Alternative Isoform analysis of RNA](https://www.nature.com/articles/s41467-020-15171-6)
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Genome Assembly
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Single-cell analysis
- BLAZE - [Python] - [Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE](https://www.biorxiv.org/content/10.1101/2022.08.16.504056v1)
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Contact
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Reads simulation
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Pipelines
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Single-cell analysis
- MOP2 - [Nextflow] - [MasterOfPores: A Workflow for the Analysis of Oxford Nanopore Direct RNA Sequencing Datasets](https://www.frontiersin.org/articles/10.3389/fgene.2020.00211/full)
- nf-core/nanoseq - [Nextflow] - [A systematic benchmark of Nanopore long read RNA sequencing for transcript level analysis in human cell lines](https://www.biorxiv.org/content/10.1101/2021.04.21.440736v1)
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Metagenomics
- nf-Wochenende - [Nextflow, Python] - [Wochenende - modular and flexible alignment-based shotgun metagenome analysis](https://www.biorxiv.org/content/10.1101/2022.03.18.484377v3)
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Reads simulation
- NanoSim - [Python] - [NanoSim: nanopore sequence read simulator based on statistical characterization.](https://doi.org/10.1093/gigascience/gix010), [Trans-NanoSim characterizes and simulates nanopore RNA-sequencing data.](https://academic.oup.com/gigascience/article/9/6/giaa061/5855462?login=true), [Characterization and simulation of metagenomic nanopore sequencing data with Meta-NanoSim.](https://academic.oup.com/gigascience/article/doi/10.1093/gigascience/giad013/7080817?login=true)
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What is an awesome list?
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Reads simulation
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Programming Languages
Sub Categories
RNA modification analysis
18
Basecalling
9
DNA modification analysis
9
Adaptive sampling / ReadUntil Real-time mapping / signal mapping
7
Transcript discovery and quantification
7
Raw signal data manipulation, conversion, visualisation, etc.
4
Reads simulation
3
Single-cell analysis
3
Genome Assembly
2
RNA structure prediction
2
Poly(A) tail length estimation
2
Segmentation
1
Metagenomics
1
Keywords
nanopore
14
bioinformatics
8
rna-seq
6
nanopore-sequencing
5
genomics
4
oxford-nanopore
4
rna
3
methylation
3
transcriptome
3
cdna
2
transcriptomics
2
pacbio
2
r
2
transcript-quantification
2
nextflow
2
pipeline
2
rna-modifications
2
basecalling
2
epigenetics
2
sequencing
2
ont
2
single-cell-rna-seq
1
pacbio-sequencing
1
denovo-assembly
1
bulk-rna-seq
1
bioinformatics-tool
1
libtorch
1
pytorch
1
adaptive-sampling
1
modified-bases
1
python
1
modification
1
tensorflow
1
predict-rna-modifications
1
machine-learning
1
rna-modification-stoichiometry
1
tombo-resquiggling
1
raw-signal
1
epitranscriptomics
1
epigenomics
1
comparative-analysis
1
science
1
genome-assembly
1
c-plus-plus
1
unicorns
1
resources
1
lists
1
awesome-list
1
awesome
1
simulator
1