NANOPACK

Overview of my long read processing and analysis tools.

Tools

NanoPlot: creating many relevant plots derived from reads (fastq), alignments (bam) and albacore summary files. Examples can be found in the gallery on my blog. NanoPack is also available as a web service.

NanoComp: comparing multiple runs on read length and quality based on reads (fastq), alignments (bam) or albacore summary files.

NanoQC: Generating plots to investigate nucleotide composition and quality distribution at the end of reads.

Cramino: Rust replacement for NanoStat - much quicker summary creation of BAM or CRAM files.

chopper: A rust implementation combining NanoLyse and NanoFilt into one faster tool for filtering, trimming, and removing contaminants

phasius: Rust tool to create a graphical representation of the read phasing performance (from BAM/CRAM files)

kyber: Rust tool for a minimalistic and standarized impression of a BAM/CRAM file, optionally comparing 2 or 3 datasets.

Deprecated (replaced by quicker alternatives)

NanoStat: Create a statistical summary from reads, an alignment or a summary file.

NanoFilt: Streaming script for filtering a fastq file based on a minimum length, minimum quality cut-off, minimum and maximum average GC. Also trimming nucleotides from either read ends is an option.

NanoLyse: Streaming script for filtering a fastq file to remove reads mapping to the lambda phage genome (control DNA used in nanopore sequencing). Uses minimap2/mappy.

Modules

nanoget: Functions for extracting features from reads, alignments and albacore summary data, parallelized.

nanomath: Functions for mathematical processing and calculating statistics.

Test data

nanotest provides small test datasets in fastq, bam and summary format (not included when installing NanoPack)

Installation

The python scripts are written and tested for Python >= 3.6. With pip install nanopack all python tools can be installed simultaneously, but using a conda environment is encouraged. For the rust tools binaries can be downloaded from the releases on the respective GitHub repositories, as well as installation through conda.

CITATION

If you use this tool, please consider citing our publication.