Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Bioinformatics. 2019 Nov 1;35(21):4445-4447. doi: 10.1093/bioinformatics/btz269.
The recent technological improvement of Oxford Nanopore sequencing pushed the throughput of these devices to 10-20 Gb allowing the generation of millions of reads. For these reasons, the availability of fast software packages for evaluating experimental quality by generating highly informative and interactive summary plots is of fundamental importance.
We developed PyPore, a three module python toolbox designed to handle raw FAST5 files from quality checking to alignment to a reference genome and to explore their features through the generation of browsable HTML files. The first module provides an interface to explore and evaluate the information contained in FAST5 and summarize them into informative quality measures. The second module converts raw data in FASTQ format, while the third module allows to easily use three state-of-the-art aligners and collects mapping statistics.
PyPore is an open-source software and is written in Python2.7, source code is freely available, for all OS platforms, in Github at https://github.com/rsemeraro/PyPore.
Supplementary data are available at Bioinformatics online.
最近牛津纳米孔测序技术的进步将这些设备的通量推至 10-20Gb，允许生成数百万个读数。出于这些原因，开发快速软件包对于通过生成高度信息丰富和交互式摘要图来评估实验质量变得至关重要。
我们开发了 PyPore，这是一个由三个模块组成的 Python 工具包，旨在从质量检查到与参考基因组对齐处理原始 FAST5 文件，并通过生成可浏览的 HTML 文件来探索它们的特征。第一个模块提供了一个接口来探索和评估 FAST5 中包含的信息，并将其总结为有用的质量度量。第二个模块将原始数据转换为 FASTQ 格式，而第三个模块允许轻松使用三种最先进的对齐器并收集映射统计信息。
PyPore 是一个开源软件，用 Python2.7 编写，源代码可在所有操作系统平台上免费获取，在 Github 上的网址为 https://github.com/rsemeraro/PyPore。
补充数据可在生物信息学在线获得。
