Statz, B. | bioRxiv Science

bioRxiv2018

A comprehensive analysis of the usability and archival stability of omics computational tools and resources

Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through URLs published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed \"easy to install,\" and 28% of the tools failed to be installed at all due to problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software.

bioinformatics↗

bioRxiv2016

Profiling adaptive immune repertoires across multiple human tissues by RNA Sequencing

Assay-based approaches provide a detailed view of the adaptive immune system by profiling T and B cell receptor repertoires. However, these methods come at a high cost and lack the scale of standard RNA sequencing (RNA-seq). Here we report the development of ImReP, a novel computational method for rapid and accurate profiling of the adaptive immune repertoire from regular RNA-Seq data. We applied it to 8,555 samples across 544 individuals from 53 tissues from the Genotype-Tissue Expression (GTEx v6) project. ImReP is able to efficiently extract TCR- and BCR- derived reads from the RNA-Seq data and accurately assemble the complementarity determining regions 3 (CDR3s), the most variable regions of B- and T-cell receptors determining their antigen specificity. Using ImReP, we have created the systematic atlas of immunological sequences for B- and T-cell repertoires across a broad range of tissue types, most of which have not been studied for B and T cell receptor repertoires. We have also examined the compositional similarities of clonal populations between the GTEx tissues to track the flow of T- and B- clonotypes across immune-related tissues, including secondary lymphoid organs and organs encompassing mucosal, exocrine, and endocrine sites. The atlas of T- and B-cell receptor receptors, freely available at https://sergheimangul.wordpress.com/atlas-immune-repertoires/, is the largest collection of CDR3 sequences and tissue types. We anticipate this recourse will enhance future studies in areas such as immunology and advance development of therapies for human diseases. ImReP is freely available at https://sergheimangul.wordpress.com/imrep/.

immunology↗