The Sequence Read Archive is an important repository for sequencing data. Metadata for sequencing datasets need to entered manually which makes the process prone to error and incomplete entry. The Zavolan lab created the tool HTSinfer which extracts metadata directly from the reads in given Illumina RNA-Seq libraries. Their tool is presented in the Bioinformatics publication "HTSinfer: inferring metadata from bulk Illumina RNA-Seq libraries".
Abstract
Summary: The Sequencing Read Archive is one of the largest and fastest-growing repositories of sequencing data, containing tens of petabytes of sequenced reads. Its data is used by a wide scientific community, often beyond the primary study that generated them. Such analyses rely on accurate metadata concerning the type of experiment and library, as well as the organism from which the sequenced reads were derived. These metadata are typically entered manually by contributors in an error-prone process, and are frequently incomplete. In addition, easy-to-use computational tools that verify the consistency and completeness of metadata describing the libraries to facilitate data reuse, are largely unavailable. Here, we introduce HTSinfer, a Python-based tool to infer metadata directly and solely from bulk RNA-sequencing data generated on Illumina platforms. HTSinfer leverages genome sequence information and diagnostic genes to rapidly and accurately infer the library source and library type, as well as the relative read orientation, 3' adapter sequence and read length statistics. HTSinfer is written in a modular manner, published under a permissible free and open-source license and encourages contributions by the community, enabling easy addition of new functionalities, e.g. for the inference of additional metrics, or the support of different experiment types or sequencing platforms.
Read the Publication in Bioinformatics (Open Access)
Abstract, figures and title from Balajti et al (2025) Bioinformatics published under a CC BY 4.0 licence.