Qu, L. | bioRxiv Science

bioRxiv2018

Optical Sectioning of Live Mammal with Near-Infrared Light Sheet

Deep-tissue three-dimensional optical imaging of live mammals in vivo with high spatiotemporal resolution in non-invasive manners has been challenging due to light scattering. Here, we developed near-infrared (NIR) light sheet microscopy (LSM) with optical excitation and emission wavelengths up to ~ 1320 nm and ~ 1700 nm respectively, far into the NIR-II (1000-1700 nm) region for 3D optical sectioning through live tissues. Suppressed scattering of both excitation and emission photons allowed one-photon optical sectioning at ~ 2 mm depth in highly scattering brain tissues. NIR-II LSM enabled non-invasive in vivo imaging of live mice, revealing never-before-seen dynamic processes such as highly abnormal tumor microcirculation, and 3D molecular imaging of an important immune checkpoint protein, programmed-death ligand 1 (PD-L1) receptors at the single cell scale in tumors. In vivo two-color near-infrared light sheet sectioning enabled simultaneous volumetric imaging of tumor vasculatures and PD-L1 proteins in live mammals.

bioengineering↗

bioRxiv2018

VCPA: genomic variant calling pipeline and data management tool for Alzheimer’s Disease Sequencing Project

Summary: We report VCPA, our SNP/Indel Variant Calling Pipeline and data management tool used for analysis of whole genome and exome sequencing (WGS/WES) for the Alzheimers Disease Sequencing Project. VCPA consists of two independent but linkable components: pipeline and tracking database. The pipeline is coded in Workflow Description Language and is fully optimized for the Amazon elastic compute cloud environment. This includes steps for processing raw sequence reads including read alignment, and all the way up to variant calling using GATK. The tracking database allows users to dynamically view the statuses of jobs running and the quality metrics reported by the pipeline. Users can thus monitor the production process and diagnose if any problem arises during the procedure. All quality metrics (>100 collected per processed genome) are stored in the database, thus facilitating users to compare, share and visualize the results. To summarize, VCPA is functional equivalent to the CCDG/TOPMed pipeline. Together with the dockerized database (also available as Amazon Machine Image), users can easily process any WGS/WES data on Amazon cloud with minimal installation.\n\nAvailability: VCPA is released under the MIT license and is available for academic and nonprofit use for free. The pipeline source code and step-by-step instructions are available from the National Institute on Aging Genetics of Alzheimers Disease Data Storage Site (http://www.niagads.org/VCPA).\n\nContact: yyee@pennmedicine.upenn.edu or lswang@pennmedicine.upenn.edu\n\nSupplementary information: Supplementary data are available at Bioinformatics online.

bioinformatics↗