BackgroundThe emergence of ribosome profiling to map actively translating ribosomes has laid the foundation for a diverse range of studies on translational regulation. The data obtained with different variations of this assay is typically manually processed, which has created a need for tools that would streamline and standardize processing steps.ResultsWe present Shoelaces, a toolkit for ribosome profiling experiments automating read selection and filtering to obtain genuine translating footprints. Based on periodicity, favoring enrichment over the coding regions, it determines the read lengths corresponding to bona fide ribosome protected fragments. The specific codon under translation (P-site) is determined by automatic offset calculations resulting in sub-codon resolution. Shoelaces provides both a user-friendly graphical interface for interactive visualisation in a genome browser-like fashion and a command line interface for integration into automated pipelines. We process 79 libraries and show that studies typically discard excessive amounts of quality data in their manual analysis pipelines.ConclusionsShoelaces streamlines ribosome profiling analysis offering automation of the processing, a range of interactive visualization features and export of the data into standard formats. Shoelaces stores all processing steps performed in an XML file that can be used by other groups to exactly reproduce the processing of a given study. We therefore anticipate that Shoelaces can aid researchers by automating what is typically performed manually and contribute to the overall reproducibility of studies. The tool is freely distributed as a Python package, with additional instructions, tutorial and demo datasets available at https://bitbucket.org/valenlab/shoelaces.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4912-6) contains supplementary material, which is available to authorized users.

Note: Also to appear in the Dagstuhl 2012 SciVis book by Springer. Please cite this paper with its arXiv citation information. Abstract Ultrasound is one of the most frequently used imaging modality in medicine. The high spatial resolution, its interactive nature and non-invasiveness makes it the first choice in many examinations. Image interpretation is one of ultrasound's main challenges. Much training is required to obtain a confident skill level in ultrasound-based diagnostics. State-of-the-art graphics techniques is needed to provide meaningful visualizations of ultrasound in real-time. In this paper we present the process-pipeline for ultrasound visualization, including an overview of the tasks performed in the specific steps. To provide an insight into the trends of ultrasound visualization research, we have selected a set of significant publications and divided them into a technique-based taxonomy covering the topics pre-processing, segmentation, registration, rendering and augmented reality. For the different technique types we discuss the difference between ultrasound-based techniques and techniques for other modalities.

Figure 1: Automatically generated peel to reveal the meta carpal bone of the middle finger. AbstractIn this paper a novel approach for peel-away visualizations is presented. The newly developed algorithm extends existing illustrative deformation approaches which are based on deformation templates and adds a new component of view-dependency of the peel region. The view-dependent property guarantees the viewer an unobstructed view on the inspected feature of interest. This is realized by rotating the deformation template so that the peeled-away segment always faces away from the viewer. Furthermore the new algorithm computes the underlying peel template on-the-fly, which allows animating the level of peeling. When structures of interest are tagged with segmentation masks, an automatic scaling and positioning of peel deformation templates allows guided navigation and clear view on structures in focus as well as feature-aligned peeling. The overall performance allows smooth interaction with reasonably sized datasets and peel templates as the implementation maximizes the utilization of computation power of modern GPUs.

Clipping is a fast, common technique for resolving occlusions. It only requires simple interaction, is easily understandable, and thus has been very popular for volume exploration. However, a drawback of clipping is that the technique indiscriminately cuts through features. Illustrators, for example, consider the structures in the vicinity of the cut when visualizing complex spatial data and make sure that smaller structures near the clipping plane are kept in the image and not cut into fragments. In this paper we present a new technique, which combines the simple clipping interaction with automated selective feature preservation using an elastic membrane. In order to prevent cutting objects near the clipping plane, the deformable membrane uses underlying data properties to adjust itself to salient structures. To achieve this behaviour, we translate data attributes into a potential field which acts on the membrane, thus moving the problem of deformation into the soft-body dynamics domain. This allows us to exploit existing GPU-based physics libraries which achieve interactive frame rates. For manual adjustment, the user can insert additional potential fields, as well as pinning the membrane to interesting areas. We demonstrate that our method can act as a flexible and non-invasive replacement of traditional clipping planes.

The emergence of ribosome profiling to map actively translating ribosomes has laid the foundation for a diverse range of studies on translational regulation. The data obtained with different variations of this assay is typically manually processed, which has created a need for tools that would streamline and standardize processing steps.We present Shoelaces, a toolkit for ribosome profiling experiments automating read selection and filtering to obtain genuine translating footprints. Based on periodicity, favoring enrichment over the coding regions, it determines the read lengths corresponding to bona fide ribosome protected fragments. The specific codon under translation (P-site) is determined by automatic offset calculations resulting in sub-codon resolution. Shoelaces provides both a user-friendly graphical interface for interactive visualisation in a genome browser-like fashion and a command line interface for integration into automated pipelines. We process 79 libraries and show that studies typically discard excessive amounts of data in their manual analysis pipelines.Shoelaces streamlines ribosome profiling analysis offering automation of the processing, a range of interactive visualization features and export of the data into standard formats.Shoelaces stores all processing steps performed in an XML file that can be used by other groups to exactly reproduce the processing of a given study. We therefore anticipate that (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.