Biology subjects

Lloyd, W.

Publications and source records attributed to Lloyd, W..

6 recordsLinked to original sources

bioRxiv2025

Singe cell RNA sequencing data processing using cloud-based serverless computing

Singe cell RNA sequencing (scRNA-seq) has become a routine method for measuring cell activities. Processing large scRNA-seq datasets requires high-performance computing resources. The emergence of cloud computing allows us to leverage its on-demand capabilities without major investment in infrastructure. Serverless computing provides cost efficiency by allowing users to pay only for actual resource usage, eliminating the necessity for pre-allocated server capacities. Additionally, there is no requirement to set up servers in advance. We present a novel and generalizable methodology using serverless cloud computing to accelerate computationally intensive workflows. We create an on-demand "supercomputer" using rapidly deployable cloud serverless functions as automatically provisioned computation units. We tested our methodology of optimizing a scRNA-seq workflow by leveraging serverless functions on the cloud using two publicly available peripheral blood mononuclear cell (PBMC) datasets. In addition, we demonstrate our approach using data generated by the NIH MorPhiC program, where we process a 450 GB human scRNA-seq dataset across 86 cell lines designed to study the temporal impact of perturbations on pancreatic differentiation. We compared the total execution time of the scRNA-seq serverless workflow with the traditional workflow without using serverless functions, and demonstrate major speedup for large scRNA-seq datasets.

bioinformatics↗

bioRxiv2022

Accessible, interactive and cloud-enabled genomic workflows integrated with the NCI Genomic Data Commons

Cancer data is widely available in repositories such as the National Cancer Institute (NCI) Genomic Data Commons (GDC). These datasets could serve as controls or comparisons in compendium analyses with user data, avoiding the expense and time of generating additional datasets. However, the user must be able to process their new data in the same manner for these comparisons to be useful. This can be non-trivial. Although the executables themselves are usually available in repositories, the GDC pipelines that describe that entire analysis workflow are currently published as text-based standard operating procedures (SOPs). It is difficult to document a computational workflow to the level of detail and accuracy required to reproduce the results. Discrepancies between versions and exclusions of details accumulate as the documentation inevitably lags behind code revisions. We address this problem by converting the SOPs into a downloadable and executable format. Specifically, we converted the GDC DNA sequencing (DNA-Seq) and the GDC mRNA sequencing (mRNA-Seq) SOPs into reproducible, self-installing, containerized, and interactive graphical workflows. These can be applied to reproducibly process user data and to harmonize datasets across repositories. Using our publicly available graphical workflows, we harmonize raw RNA-Seq datasets from the GDC and the Genotype-Tissue Expression (GTEx) project that were originally processed using different methodologies to illustrate the importance of uniform processing of control and treatment data for accurate inference of differentially expressed genes. By disseminating the analytical methodology in a reproducible and easily executed form, we greatly increase the utility of the GDC by enabling researchers to uniformly process custom data and datasets across multiple repositories to enhance data interpretation. Our approach and open-source executable workflows of making the analytical process as readily available as the data can be applied to other data repositories to increase their impact on scientific research.

bioinformatics↗

bioRxiv2019

Longitudinal change in executive function is associated with impaired top-down frontolimbic regulation during reappraisal in older adults

Networks in the prefrontal cortex (PFC) that are important for executive function are also engaged in adaptive responding to negative events. These networks are particularly vulnerable to age-related structural atrophy and an associated loss of executive function, yet existing evidence suggests preserved emotion processing ability in aging. Using longitudinally acquired data from a battery of cognitive tasks, we defined a metric for the rate of decline of executive function. With this metric, we investigated relationships between changes in executive function and emotion reappraisal ability and brain structure, in older adults using functional and structural MRI. During task-based fMRI, participants were asked to cognitively reappraise negatively valenced images. We hypothesised one of two associations with decreasing executive function over time: 1) a decreased ability to reappraise reflected in decreased PFC and increased amygdala activation, or 2) a neural compensation mechanism characterised by increased PFC activation but no differential amygdala activation. Structurally, for a decreased reappraisal ability, we predicted a decrease in grey matter in PFC and/or a decrease of white matter integrity in amygdala-PFC pathways. Neither of the two hypotheses relating to brain function were completely supported, with the findings indicating a steeper decline in executive function associated with both increased PFC and increased left amygdala activity when reappraising negative stimuli. In addition, white matter integrity of the uncinate fasciculus, a primary white matter tract connecting the amygdala and ventromedial areas of PFC, was lower in those individuals who demonstrated a greater decrease in executive function. These findings highlight that when cognitive ability diminishes, active top-down emotional control is compromised.

neuroscience↗

bioRxiv2019

Rapid RNA sequencing data analysis using serverless computing

We present a novel method that yields 1100-fold computational speedup and allows biomedical scientists to interactively adjust alignment parameters in real time to iteratively improve final analytical results. Specifically, the alignment time for a 640 million read human RNA-sequencing dataset is reduced from 19 hours to 1 minute using serverless cloud computing. We provide a graphical interface for the accelerated workflows, thus making our methodology accessible to non-cloud experts.

bioinformatics↗

bioRxiv2018

Holistic optimization of RNA-seq workflow for multi-threaded environments

SummaryFor many next-generation sequencing pipelines, the most computationally intensive step is the alignment of reads to a reference sequence. As a result, alignment software such as the Burrows-Wheeler Aligner (BWA) is optimized for speed and and is often executed in parallel on the cloud. However, there are other less demanding steps that can also be optimized and significantly increase the speed especially when using many threads. We demonstrate this using a Unique-molecular-identifier (UMI) RNA sequencing pipeline consisting of 3 steps: split, align, and merge. Optimization of all three steps yields a 40% increase in speed when executed using a single thread. However, when executed using 16 threads, we observe a 4-fold improvement over the original parallel imple-mentation and more than an 8-fold improvement over the original single-threaded implementation. In contrast, optimizing only the alignment step results in just a 13% improvement over the original parallel workflow using 16 threads.

bioinformatics↗

bioRxiv2018

Thalamostriatal Interactions in Human Reversal Learning

Cognitive flexibility is crucial for adaptation and is disrupted in neuropsychiatric disorders and psychopathology. Human studies of flexibility using reversal learning tasks typically contrast error trials before and after reversal, which provides little information about the mechanisms that support learning and expressing a new response. However, animal studies suggest a specific role in this latter process for the connections between the dorsal striatum and the centromedian parafascicular (CM-Pf) thalamus, a system which may recruit the striatal cholinergic interneurons, but which is not well understood in humans. This study investigated the role of this system in human probabilistic reversal learning, specifically with respect to learning a new response strategy, contrasting its function to that of the better understood orbitoftontal-striatal systems. Using psychophysiological interaction (PPI) analysis of functional magnetic resonance imaging (fMRI) data we show that connectivity between the striatum and both the lateral orbitofrontal cortex (lOFC) and CM-Pf pathways increased during reversal, but not initial learning. However, while the strength of lOFC-striatal connectivity was associated with the speed of the reversal, the strength of CM-Pf-striatal connectivity was associated specifically with the quality of the reversal (reduced regressive errors). These findings expand our understanding of flexibility mechanisms in the human brain, bridging the gap with animal studies of this system.

neuroscience↗