Biology subjects

Qu, L.

Publications and source records attributed to Qu, L..

36 records · Page 2Linked to original sources

bioRxiv2022

Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlation

In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences can lead to misconceptions, which is especially intractable in emerging deep-learning ones. Current mapping methods fail to finely estimate the local quality, challenging to associate the SR scale content. Here, we develop a rolling Fourier ring correlation (rFRC) framework to evaluate the reconstruction uncertainties down to SR scale. To visually pinpoint regions with low reliability, a filtered rFRC is combined with a modified resolution scaled error map (RSM), offering a comprehensive and concise map for further examination. We demonstrate their performances on various SR imaging modalities, and the resulting quantitative maps enable better SR images integrated from different reconstructions. Beyond that, we provide a strategy for learning-based restorations, allowing a direct detection of both data and model uncertainties, and expect the representative cases can inspire further advances in this rapidly developing field.

biophysics↗

bioRxiv2022

Data Descriptor: Human whole exome genotype data for Alzheimer's Disease

Bigger sample size can help to identify new genetic variants contributing to an increased risk of developing Alzheimers disease. However, the heterogeneity of the whole-exome sequencing (WES) data generation methods presents a challenge to a joint analysis. Here we present a bioinformatics strategy for joint calling 20,504 WES samples collected across nine studies and sequenced using ten different capture kits in fourteen sequencing centers in the Alzheimers Disease Sequencing Project. gVCFs of samples were joint-called by the Genome Center for Alzheimers Disease into a single VCF, containing only positions within the union of capture kits. The VCF was then processed using specific strategies to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 15% are missense variants. 1.8% of the variants are with CADD>30. Our new strategy for processing these diversely generated WES samples has shown to generate high-quality data. The improved ability to combine data sequenced in different batches benefits the whole genomics research community. The WES data are accessible to the scientific community via https://dss.niagads.org/.

genetics↗

bioRxiv2022

Tree and shrub richness modify subtropical tree productivity by modulating the diversity and community composition of soil bacteria and archaea

BackgroundDeclines in plant biodiversity often have negative consequences for plant community productivity, and it becomes increasingly acknowledged that this may be driven by shifts in soil microbial community composition. These relationships have been well-established in grasslands, and few studies also indicate that fungi play a role in driving tree diversity-productivity relationships in forests. However, the role of bacteria and archaea, which are also highly abundant in forest soils and perform pivotal ecosystem functions, has been largely overlooked. Here, we investigated how tree and shrub richness affects stand-level tree productivity via modulating bacterial and archaeal community diversity and composition. We used a landscape-scale, subtropical tree biodiversity experiment (BEF-China) where tree (1, 2 or 4 species) and shrub richness (0, 2, 4, 8 species) were modified. ResultsOur results showed that tree and shrub species richness affected bacterial diversity, community composition, and co-occurrence networks, but such effects were marginal for archaea. Both tree and shrub species richness increased stand-level tree productivity by modulating soil microbial community composition, with the effects being mediated via increases in soil C:N ratios. ConclusionsOur findings imply the importance of bacterial and archaeal communities in driving the relationship between plant diversity and productivity in subtropical forests and highlight that we may require better a understanding of prokaryotic communities in forest soils.

ecology↗

bioRxiv2022

BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology

BigNeuron is an open community bench-testing platform combining the expertise of neuroscientists and computer scientists toward the goal of setting open standards for accurate and fast automatic neuron reconstruction. The project gathered a diverse set of image volumes across several species representative of the data obtained in most neuroscience laboratories interested in neuron reconstruction. Here we report generated gold standard manual annotations for a selected subset of the available imaging datasets and quantified reconstruction quality for 35 automatic reconstruction algorithms. Together with image quality features, the data were pooled in an interactive web application that allows users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and reconstruction data, and benchmarking of automatic reconstruction algorithms in user-defined data subsets. Our results show that image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. By benchmarking automatic reconstruction algorithms, we observed that diverse algorithms can provide complementary information toward obtaining accurate results and developed a novel algorithm to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms. Finally, to aid users in predicting the most accurate automatic reconstruction results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic reconstructions.

bioinformatics↗

bioRxiv2021

Non-Invasive Confocal Fluorescence Imaging of Mice Beyond 1700 nm Using Superconducting Nanowire Single-Photon Detectors

Light scattering by biological tissues sets a limit to the penetration depth of high-resolution optical microscopy imaging of live mammals in vivo. An effective approach to reduce light scattering and increase imaging depth is by extending the excitation and emission wavelengths to the > 1000 nm second near-infrared (NIR-II), also called the short-wavelength infrared (SWIR) window. Here, we developed biocompatible core-shell lead sulfide/cadmium sulfide (PbS/CdS) quantum dots emitting at ~1880 nm and superconducting nanowire single photon detectors (SNSPD) for single-photon detection up to 2000 nm, enabling one-photon fluorescence imaging window in the 1700-2000 nm (NIR-IIc) range. Confocal fluorescence imaging in NIR-IIc reached an imaging depth of ~ 800 m through intact mouse head, and enabled non-invasive imaging of inguinal lymph nodes (LNs) without any surgery. In vivo molecular imaging of high endothelial venules (HEVs) with diameter down to ~ 6.6 m in the lymph nodes was achieved, opening the possibility of non-invasive imaging of immune trafficking in lymph nodes at the single-cell/vessel level longitudinally.

biochemistry↗

bioRxiv2021

miR-544-3p mediates arthritis pain through regulation of FcγRI

Chronic or episodic joint pain is a major symptom in rheumatoid arthritis (RA) and its adequate treatment represents an unmet medical need. However, the cellular and molecular mechanisms underlying RA pain remain elusive. Non-coding microRNAs (miRNAs) have been implicated in the pathogenesis of RA as negative regulators of the stability or translation of specific target mRNAs. Yet, their significance in RA pain is still not well defined. We and other groups recently identified neuronally expressed Fc{gamma}RI as a key driver of arthritis pain in mouse RA models. Thus, we tested the hypothesis that miRNAs that target and regulate neuronal Fc{gamma}RI attenuate RA pain. Here, we show that miR-544-3p was robustly downregulated whereas Fc{gamma}RI was significantly upregulated in the dorsal root ganglion (DRG) in mouse RA models. Intrathecal injection of miR-544-3p mimic attenuated established mechanical and heat hyperalgesia in a mouse model of collagen II-induced arthritis (CIA). Moreover, this effect was likely mediated, at least in part, by Fc{gamma}RI since miR-544-3p mimic downregulated Fc{gamma}RI in the DRG during arthritis and genetic deletion of Fc{gamma}RI produced similar antihyperalgesic effects in the CIA model. This notion was further supported by a dual luciferase assay showing that miR-544-3p targeted Fc{gamma}RI by directly binding to its 3UTR. In addition, Fc{gamma}RI expression in DRG neurons in vitro was downregulated by miR-544-3p mimic and upregulated by miR-544-3p inhibitor. In naive mice, miR-544-3p mimic alleviated acute joint pain hypersensitivity induced by IgG immune complex (IgG-IC), whereas miR-544-3p inhibitor potentiated the pro-nociceptive behavioral effect of IgG-IC. These findings suggest that miR-544-3p causally participates in the maintenance of arthritis pain by targeting neuronal Fc{gamma}RI, and thus define miR-544-3p as a new potential therapeutic target for treating RA pain.

neuroscience↗

bioRxiv2021

Circular RNA Vaccines against SARS-CoV-2 and Emerging Variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its emerging variants of concern (VOC), such as Delta (B.1.617.2) and Omicron (B.1.1.529), has continued to drive the worldwide pandemic. Therefore, there is a high demand for vaccines with enhanced efficacy, high thermostability, superior design flexibility, and fast manufacturing speed. Here, we report a circular RNA (circRNA) vaccine that encodes the trimeric RBD of SARS-CoV-2 Spike protein. Without the need of nucleotide modification, 5-capping or 3-polyadenylation, circRNA could be rapidly produced via in vitro transcription and is highly thermostable whether stored in naked or lipid-nanoparticle (LNP)-encapsulated format. LNP-encapsulated circRNARBD elicited potent neutralizing antibodies and T cell responses, providing robust protection against Beta (B.1.351) and native viruses in mice and rhesus macaques, respectively. Notably, circRNA vaccine enabled higher and more durable antigen production than 1m{Psi}-modified mRNA vaccine, eliciting a higher proportion of neutralizing antibodies and stronger Th1-biased immune responses. Importantly, we found that circRNARBD-Omicron vaccine induced effective neutralizing antibodies against only Omicron but not Delta variant. By contrast, circRNARBD-Delta could elicit high level of neutralizing antibodies against both Delta and Omicron. Following two doses of either native- or Delta-specific vaccination, circRNARBD-Delta, but not Omicron or Beta vaccines, could effectively boost the neutralizing antibodies against both Delta and Omicron variants. These results suggest that circRNARBD-Delta is a favorable choice for vaccination to provide a broad-spectrum protection against the current variants of concern of SARS-CoV-2.

immunology↗

bioRxiv2021

Metapopulation Structure of Diatom-associated Marine Bacteria

Marine bacteria-phytoplankton interaction ultimately shapes ecosystem productivity. The biochemical mechanisms underlying their interactions become increasingly known, yet how these ubiquitous interactions drive bacterial evolution has not been illustrated. Here, we sequenced genomes of 294 bacterial isolates associated with 19 coexisting diatom cells. These bacteria constitute eight genetically monomorphic populations of the globally abundant Roseobacter group. Six of these populations are members of Sulfitobacter, arguably the most prevalent bacteria associated with marine diatoms. A key finding is that populations varying at the intra-specific level have been differentiated and each are either associated with a single diatom host or with multiple hosts not overlapping with those of other populations. These closely related populations further show functional differentiation; they differ in motility phenotype and they harbor distinct types of secretion systems with implication for mediating organismal interactions. This interesting host-dependent population structure is even evident for demes within a genetically monomorphic population but each associated with a distinct diatom cell, as shown by a greater similarity in genome content between isolates from the same host compared to those from different hosts. Importantly, the intra- and inter-population differentiation pattern remains when the analyses are restricted to isolates from intra-specific diatom hosts, ruling out distinct selective pressures and instead suggesting coexisting microalgal cells as physical barriers of bacterial gene flow. Taken together, microalgae-associated bacteria display a unique microscale metapopulation structure, which consists of numerous small populations whose evolution is driven by random genetic drift.

microbiology↗

bioRxiv2020

The landscape of micro-inversions provides clues for population genetic analysis of humans

BackgroundVariations in the human genome have been studied extensively. However, little is known about the role of micro-inversions (MIs), generally defined as small (<100 bp) inversions, in human evolution, diversity, and health. Depicting the pattern of MIs among diverse populations is critical for interpreting human evolutionary history and obtaining insight into genetic diseases. ResultsIn this paper, we explored the distribution of MIs in genomes from 26 human populations and 7 nonhuman primate genomes and analyzed the phylogenetic structure of the 26 human populations based on the MIs. We further investigated the functions of the MIs located within genes associated with human health. With hg19 as the reference genome, we detected 6,968 MIs among the 1,937 human samples and 24,476 MIs among the 7 nonhuman primate genomes. The analyses of MIs in human genomes showed that the MIs were rarely located in exonic regions. Nonhuman primates and human populations shared only 82 inverted alleles, and Africans had the most inverted alleles in common with nonhuman primates, which was consistent with the "Out of Africa" hypothesis. The clustering of MIs among the human populations also coincided with human migration history and ancestral lineages. ConclusionsWe propose that MIs are potential evolutionary markers for investigating population dynamics. Our results revealed the diversity of MIs in human populations and showed that they are essential to constructing human population relationships and have a potential effect on human health.

genomics↗

bioRxiv2020

NanoReviser: An Error-correction Tool for Nanopore Sequencing Based on a Deep Learning Algorithm

Nanopore sequencing is regarded as one of the most promising third-generation sequencing (TGS) technologies. Since 2014, Oxford Nanopore Technologies (ONT) has developed a series of devices based on nanopore sequencing to produce very long reads, with an expected impact on genomics. However, the nanopore sequencing reads are susceptible to a fairly high error rate owing to the difficulty in identifying the DNA bases from the complex electrical signals. Although several basecalling tools have been developed for nanopore sequencing over the past years, it is still challenging to correct the sequences after applying the basecalling procedure. In this study, we developed an open-source DNA basecalling reviser, NanoReviser, based on a deep learning algorithm to correct the basecalling errors introduced by current basecallers provided by default. In our module, we re-segmented the raw electrical signals based on the basecalled sequences provided by the default basecallers. By employing convolution neural networks (CNNs) and bidirectional long short-term memory (Bi-LSTM) networks, we took advantage of the information from the raw electrical signals and the basecalled sequences from the basecallers. Our results showed NanoReviser, as a post-basecalling reviser, significantly improving the basecalling quality. After being trained on standard ONT sequencing reads from public E. coli and human NA12878 datasets, NanoReviser reduced the sequencing error rate by over 5% for both the E. coli dataset and the human dataset. The performance of NanoReviser was found to be better than those of all current basecalling tools. Furthermore, we analyzed the modified bases of the E. coli dataset and added the methylation information to train our module. With the methylation annotation, NanoReviser reduced the error rate by 7% for the E. coli dataset and specifically reduced the error rate by over 10% for the regions of the sequence rich in methylated bases. To the best of our knowledge, NanoReviser is the first post-processing tool after basecalling to accurately correct the nanopore sequences without the time-consuming procedure of building the consensus sequence. The NanoReviser package is freely available at https://github.com/pkubioinformatics/NanoReviser.

bioinformatics↗

bioRxiv2020

Endonuclease activity of RecJ from extremely alkaliphilic Bacillus alcalophilus

At present, all documented RecJs are exonucleases, degrading single-stranded nucleic acids. Here, we report a novel RecJ, from the extremely alkaliphilic bacterium Bacillus alcalophilus (BaRecJ), which possesses endonuclease activity and can cleave supercoiled DNA. BaRecJ contains the typical DHH and DHHA1 domains, which are conserved in all RecJs, and a functionally unknown PIWI-like domain at the C-terminus. The endonuclease activity originates from the C-terminal domain of BaRecJ which contains PIWI-like domain, and the exonuclease activity from the DHH and DHHA1 domains. Mutational analysis reveals that several important residues affect the endonuclease activity of BaRecJ. Moreover, BaRecJ cleaves specific target sequences at moderate temperature when directed by a phosphorothioate-modified single-stranded DNA (S-modified ssDNA) guide. These findings suggest that BaRecJ is substantially different from any reported RecJs and has the potential to be developed as a new gene editing tool.

microbiology↗

bioRxiv2020

A common problem in the purification of calicivirus raised by molecular sieving: balance between purification and loss of viral particles

Caliciviridae is a group of RNA viruses could lead to gastrointestinal disease in humans and acute oral or upper respiratory tract disease in felines, no efficient vaccine so far. The preparation of immunogen is a challenge to obtain a safe and efficient vaccine candidate. Molecular sieving, due to the advantage of simple and fast purifying, is considered as a very powerful tool in calicivirus purification; however, also introduce mechanical damage to the viron. In this study, we took Feline Calicivirus (FCV), a common natural pathogen in cats as well as a classic model for caliciviruses studies, as a research object. Here, with the help of the cryo-electron microscope (cryo-EM), we collected particle images in both conditions of with and without molecular sieving post-processing, the impact of molecular sieving on FCV particles was evaluated by building a flexibility evaluation system after 3D classification. The results indicated that the molecular sieving will impact the stability of P domains through increasing flexibility. In addition, we successfully built up a scoring system to describe this flexibility of FCV P-domains, which can be extended to assess the purification effect to the entire calicivirus.

microbiology↗

bioRxiv2020

A single-cell transcriptome atlas during Cashmere goat hair follicle morphogenesis

Cashmere, also known as soft gold, is produced from the secondary hair follicles in Cashmere goats and its therefore of significance to investigate the molecular profiles during Cashmere goat hair follicle development. However, our current understanding of the machinery underlying Cashmere goat hair follicle remains largely unexplored and researches regarding hair follicle development mainly used the mouse as a research model. To provides comprehensively understanding on the cellular heterogeneity and cell lineage cell fate decisions, we performed single-cell RNA sequencing on 19,705 single cells from induction (embryonic day 60), organogenesis (embryonic day 90) and cytodifferentiation (embryonic day 120) stages of fetus Cashmere goat dorsal skin. Unsupervised clustering analysis identified 16 cell clusters and their corresponding cell types were also unprecedentedly characterized. Based on the lineage inference, we revealed detailed molecular landscape along the dermal and epidermal cell lineage developmental pathways. Notably, by cross-species comparasion of single cell data with murine model, we revelaed conserved programs during dermal condensate fate commitment and the heterochrony development of hair follicle development between mouse and Cashmere goat were also discussed here. Our work here delineate unparalleled molecular profiles of different cell populations during Cashmere goat hair follicle morphogenesis and provide a valuable resource for identifying biomarkers during Cashmere goat hair follicle development.

developmental biology↗

bioRxiv2020

Differentiation genes were governed by DNA methylation during hair follicle morphogenesis in Cashmere goat

DNA methylation plays a critical role in early embryonic skin development by controlling gene expression. Act as an indirect regulator, long non-coding RNA (lncRNA) recruit DNA methyltransferases to specific genomic sites to methylate DNA. However, the molecular regulation mechanisms underlying hair follicle morphogenesis is unclear in cashmere goat. In this study, RNA-seq and Whole-genome bisulfite sequencing (WGBS) in embryonic day 65 (E65) and E120 skin tissues of cashmere goat were used to reveal this complex regulatory process. RNA-seq, qRT-PCR and immunohistochemistry results showed that Wnt signaling played an important role in both hair follicle induction and differentiation stage, transcriptional factors (TFs) including Hoxc13, Sox9, Sox21, Junb, Lhx2, Vdr and Gata3 participated in hair follicle differentiation via specific expression at E120. Subsequently, combination of WGBS and RNA-seq analysis showed that the expression of hair follicle differentiation genes and TFs genes was negatively correlated with DNA methylation level generally. A portion of hair follicle differentiation genes were methylated and repressed in hair follicle induction stage but were subsequently demethylated and expressed during hair follicle differentiation stage, suggesting DNA methylation play an important role in hair morphogenesis through regulating associated gene expression. Furthermore, the potential differentially expressed lncRNAs associated with DNA methylation on target gene were revealed. LncRNA XR_001918556 may affect the DNA methylation of TFs gene Gata3, lnc-003786 may affect the DNA methylation of signaling gene Fgfr2. In conclusion, differentiation genes were governed by DNA methylation, resulting in repressed expression in hair follicle induction stage and high expression in hair follicle differentiation stage. Furtherly, potential lncRNAs associated with DNA methylation on target genes were delineated. This study would enrich the regulatory network and molecular mechanisms on hair morphogenesis.

developmental biology↗

bioRxiv2019

Complete single neuron reconstruction reveals morphological diversity in molecularly defined claustral and cortical neuron types

Ever since the seminal findings of Ramon y Cajal, dendritic and axonal morphology has been recognized as a defining feature of neuronal types. Yet our knowledge concerning the diversity of neuronal morphologies, in particular distal axonal projection patterns, is extremely limited. To systematically obtain single neuron full morphology on a brain-wide scale, we established a platform with five major components: sparse labeling, whole-brain imaging, reconstruction, registration, and classification. We achieved sparse, robust and consistent fluorescent labeling of a wide range of neuronal types by combining transgenic or viral Cre delivery with novel transgenic reporter lines. We acquired high-resolution whole-brain fluorescent images from a large set of sparsely labeled brains using fluorescence micro-optical sectioning tomography (fMOST). We developed a set of software tools for efficient large-volume image data processing, registration to the Allen Mouse Brain Common Coordinate Framework (CCF), and computer-assisted morphological reconstruction. We reconstructed and analyzed the complete morphologies of 1,708 neurons from the striatum, thalamus, cortex and claustrum. Finally, we classified these cells into multiple morphological and projection types and identified a set of region-specific organizational rules of long-range axonal projections at the single cell level. Specifically, different neuron types from different regions follow highly distinct rules in convergent or divergent projection, feedforward or feedback axon termination patterns, and between-cell homogeneity or heterogeneity. Major molecularly defined classes or types of neurons have correspondingly distinct morphological and projection patterns, however, we also identify further remarkably extensive morphological and projection diversity at more fine-grained levels within the major types that cannot presently be accounted for by preexisting transcriptomic subtypes. These insights reinforce the importance of full morphological characterization of brain cell types and suggest a plethora of ways different cell types and individual neurons may contribute to the function of their respective circuits.

neuroscience↗

bioRxiv2019

Leveraging Endogenous ADAR for Programmable Editing on RNA

Nucleic acid editing carries enormous potential for biological research and the development of therapeutics. Current tools for DNA or RNA editing rely on introducing exogenous proteins into living organisms, which is subject to potential risks or technical barriers due to possible aberrant effector activity, delivery limits and immunogenicity. Here, we report a programmable approach that employs a short RNA to leverage endogenous ADAR (Adenosine Deaminase Acting on RNA) proteins for targeted RNA editing. We engineered an RNA that is partially complementary to the target transcript to recruit native ADAR1 or ADAR2 to change adenosine to inosine at a specific site. We designated this new method as LEAPER (Leveraging Endogenous ADAR for Programmable Editing on RNA) and the ADAR-recruiting RNA as arRNA. arRNA, either expressed from plasmid or viral vector, or synthesized as an oligonucleotide, could achieve desirable editing. LEAPER has a manageable off-target rate on the targeted transcripts and rare global off-targets. We demonstrated that LEAPER could restore p53 function by repairing a specific cancer-relevant point mutation. Moreover, LEAPER could apply to a broad spectrum of cell types including multiple human primary cells, and it restored the -L-iduronidase catalytic activity in Hurler syndrome patient-derived primary fibroblasts without evoking innate immune responses. As a single molecule system akin to RNAi, LEAPER enables precise and efficient RNA editing, offering the transformative potential for basic research and therapeutics.

genomics↗

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↗