Need For Analysis Software Research Articles

COSAP: Comparative Sequencing Analysis Platform

BackgroundRecent improvements in sequencing technologies enabled detailed profiling of genomic features. These technologies mostly rely on short reads which are merged and compared to reference genome for variant identification. These operations should be done with computers due to the size and complexity of the data. The need for analysis software resulted in many programs for mapping, variant calling and annotation steps. Currently, most programs are either expensive enterprise software with proprietary code which makes access and verification very difficult or open-access programs that are mostly based on command-line operations without user interfaces and extensive documentation. Moreover, a high level of disagreement is observed among popular mapping and variant calling algorithms in multiple studies, which makes relying on a single algorithm unreliable. User-friendly open-source software tools that offer comparative analysis are an important need considering the growth of sequencing technologies.ResultsHere, we propose Comparative Sequencing Analysis Platform (COSAP), an open-source platform that provides popular sequencing algorithms for SNV, indel, structural variant calling, copy number variation, microsatellite instability and fusion analysis and their annotations. COSAP is packed with a fully functional user-friendly web interface and a backend server which allows full independent deployment for both individual and institutional scales. COSAP is developed as a workflow management system and designed to enhance cooperation among scientists with different backgrounds. It is publicly available at https://cosap.bio and https://github.com/MBaysanLab/cosap/. The source code of the frontend and backend services can be found at https://github.com/MBaysanLab/cosap-webapi/ and https://github.com/MBaysanLab/cosap_frontend/ respectively. All services are packed as Docker containers as well. Pipelines that combine algorithms can be customized and new algorithms can be added with minimal coding through modular structure.ConclusionsCOSAP simplifies and speeds up the process of DNA sequencing analyses providing commonly used algorithms for SNV, indel, structural variant calling, copy number variation, microsatellite instability and fusion analysis as well as their annotations. COSAP is packed with a fully functional user-friendly web interface and a backend server which allows full independent deployment for both individual and institutional scales. Standardized implementations of popular algorithms in a modular platform make comparisons much easier to assess the impact of alternative pipelines which is crucial in establishing reproducibility of sequencing analyses.

Adaptation of Skyline for Targeted Lipidomics.

In response to the urgent need for analysis software that is capable of handling data from targeted high-throughput lipidomics experiments, we here present a systematic workflow for the straightforward method design and analysis of selected reaction monitoring data in lipidomics based on lipid building blocks. Skyline is a powerful software primarily designed for proteomics applications where it is widely used. We adapted this tool to a "Plug and Play" system for lipid research. This extension offers the unique capability to assemble targeted mass spectrometry methods for complex lipids easily by making use of building blocks. With simple yet tailored modifications, targeted methods to analyze main lipid classes such as glycerophospholipids, sphingolipids, glycerolipids, cholesteryl-esters, and cholesterol can be quickly introduced into Skyline for easy application by end users without distinct bioinformatics skills. To illustrate the benefits of our novel strategy, we used Skyline to quantify sphingolipids in mesenchymal stem cells. We demonstrate a simple method building procedure for sphingolipids screening, collision energy optimization, and absolute quantification of sphingolipids. In total, 72 sphingolipids were identified and absolutely quantified at the fatty acid scan species level by utilizing Skyline for data interpretation and visualization.

Ganglion cell complex and retinal nerve fiber layer measured by fourier-domain optical coherence tomography for early detection of structural damage in patients with preperimetric glaucoma

AimsTo evaluate the capability of Fourier-domain optical coherence tomography (FD-OCT) to detect structural damage in patients with preperimetric glaucoma.MethodsA total of 178 Caucasian subjects were enrolled in this cohort study: 116 preperimetric glaucoma patients and 52 healthy subjects. Using three-dimensional FD-OCT, the participants underwent imaging of the ganglion cell complex (GCC) and the optic nerve head. Sensitivity, specificity, likelihood ratios, and predictive values were calculated for all parameters at the first and fifth percentiles. Areas under the curves (AUCs) were generated for all parameters and were compared (Delong test). For both the GCC and the optic nerve head protocols, the OR logical disjunction (Boolean logic operator) was calculated.ResultsThe AUCs didn’t significantly differ. Macular global loss volume had the largest AUC (0.81). Specificities were high at both the fifth and first percentiles (up to 97%), but sensitivities were low, especially at the first percentile (55%–27%).ConclusionMacular and papillary diagnostic accuracies did not differ significantly based on the 95% confidence interval. The computation of the Boolean OR operator has been found to boost diagnostic accuracy. Using the software-provided classification, sensitivity and diagnostic accuracy were low for both the retinal nerve fiber layer and the GCC scans. FD-OCT does not seem to be decisive for early detection of structural damage in patients with no functional impairment. This suggests that there is a need for analysis software to be further refined to enhance glaucoma diagnostic capability.