FASTA and FASTQ are the most widely used biological data formats that have become the de facto standard to exchange sequence data between bioinformatics tools. With the avalanche of next-generation sequencing data, the amount of sequence data being deposited and accessed in FASTA/Q formats is increasing dramatically. However, the existing tools have very low efficiency at random retrieval of subsequences due to the requirement of loading the entire index into memory. In addition, most existing tools have no capability to build index for large FASTA/Q files because of the limited memory. Furthermore, the tools do not provide support to randomly accessing sequences from FASTA/Q files compressed by gzip, which is extensively adopted by most public databases to compress data for saving storage. In this study, we developed pyfastx as a versatile Python package with commonly used command-line tools to overcome the above limitations. Compared to other tools, pyfastx yielded the highest performance in terms of building index and random access to sequences, particularly when dealing with large FASTA/Q files with hundreds of millions of sequences. A key advantage of pyfastx over other tools is that it offers an efficient way to randomly extract subsequences directly from gzip compressed FASTA/Q files without needing to uncompress beforehand. Pyfastx can easily be installed from PyPI (https://pypi.org/project/pyfastx) and the source code is freely available at https://github.com/lmdu/pyfastx.

Summary: Microsatellites are found to be related with various diseases and widely used in population genetics as genetic markers. However, it remains a challenge to identify microsatellite from large genome and screen microsatellites for primer design from a huge result dataset. Here, we present Krait, a robust and flexible tool for fast investigation of microsatellites in DNA sequences. Krait is designed to identify all types of perfect or imperfect microsatellites on a whole genomic sequence, and is also applicable to identification of compound microsatellites. Primer3 was seamlessly integrated into Krait so that users can design primer for microsatellite amplification in an efficient way. Additionally, Krait can export microsatellite results in FASTA or GFF3 format for further analysis and generate statistical report as well as plotting. Availability and implementation: Krait is freely available at https://github.com/lmdu/krait under GPL2 License, implemented in C and Python, and supported on Windows, Linux and Mac operating systems. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.