RESUMO
High-throughput sequencing methods have increased the accessibility of plastid genomes, which are crucial for clarifying phylogenetic relationships. Current large sequencing efforts require software tools for routine display of their distinctive quadripartite structure, which is denoted by four junction sites. By concentrating on these junctions and their close vicinity, IRscope has emerged as the standard tool for detection of this structure and creating simplified comparative graphical maps of plastid genomes. Here, we provide an augmented version (IRplus) that encompasses a novel set of functions such as integrated error detection, flexible color schemes, and an upgraded method to detect inverted repeats in genomic sequences. Spanning across the plant tree of life, IRplus allows the quick visualization of various sets of plastid genomes and features, next to smooth interoperability with other widely used annotation file formats and platforms. The IRplus can be accessed at https://irscope.shinyapps.io/IRplus/, and source codes are freely available at https://github.com/AmiryousefiLab/IRplus.
Assuntos
Genomas de Plastídeos , Filogenia , GenômicaRESUMO
MOTIVATION: The drug sensitivity analysis is often elucidated from drug dose-response curves. These curves capture the degree of cell viability (or inhibition) over a range of induced drugs, often with parametric assumptions that are rarely validated. RESULTS: We present a class of non-parametric models for the curve fitting and scoring of drug dose-responses. To allow a more objective representation of the drug sensitivity, these epistemic models devoid of any parametric assumptions attached to the linear fit, allow the parallel indexing such as half-maximal inhibitory concentration and area under curve. Specifically, three non-parametric models including spline (npS), monotonic and Bayesian and the parametric logistic are implemented. Other indices including maximum effective dose and drug-response span gradient pertinent to the npS are also provided to facilitate the interpretation of the fit. The collection of these models is implemented in an online app, standing as useful resource for drug dose-response curve fitting and analysis. AVAILABILITY AND IMPLEMENTATION: The ENDS is freely available online at https://irscope.shinyapps.io/ENDS/ and source codes can be obtained from https://github.com/AmiryousefiLab/ENDS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.