Biology subjects

Zhou, W.

Publications and source records attributed to Zhou, W..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

The intestinal microbiome and Cetobacterium somerae inhibit viral infection through TLR2-type I IFN signaling axis in zebrafish

Accumulated evidences demonstrate that intestinal microbiome can inhibit viral infection. However, our knowledge of the signaling pathways and specific commensal microbes that mediate the antiviral response is limited. Here, a rhabdoviral infection model in zebrafish allows us to investigate the modes of action of microbiome-mediated antiviral effect. We observed that antibiotics-treated and germ-free zebrafish exhibited greater viral infection. Mechanistically, depletion of the intestinal microbiome alters TLR2-Myd88 signaling, and blunts neutrophil response and type I interferon (IFN) production. Moreover, a single commensal bacterium, Cetobacterium somerae, recapitulated TLR2- and type I IFN-dependent antiviral effect of the microbiome in gnotobiotic zebrafish, and C. somerae exopolysaccharides (CsEPS) was the effector molecule that engaged TLR2 to mediate antiviral function. Together, our results suggest a conserved role of intestinal microbiome in regulating type I IFN response among vertebrates, and reveal that the intestinal microbiome inhibits viral infection through a CsEPS-TLR2-type I IFN signaling axis in zebrafish.

microbiology↗

bioRxiv2024

Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program

The expansion of biobanks has significantly propelled genomic discoveries yet the sheer scale of data within these repositories poses formidable computational hurdles, particularly in handling extensive matrix operations required by prevailing statistical frameworks. In this work, we introduce computational optimizations to the SAIGE (Scalable and Accurate Implementation of Generalized Mixed Model) algorithm, notably employing a GPU-based distributed computing approach to tackle these challenges. We applied these optimizations to conduct a large-scale genome-wide association study (GWAS) across 2,068 phenotypes derived from electronic health records of 635,969 diverse participants from the Veterans Affairs (VA) Million Veteran Program (MVP). Our strategies enabled scaling up the analysis to over 6,000 nodes on the Department of Energy (DOE) Oak Ridge Leadership Computing Facility (OLCF) Summit High-Performance Computer (HPC), resulting in a 20-fold acceleration compared to the baseline model. We also provide a Docker container with our optimizations that was successfully used on multiple cloud infrastructures on UK Biobank and All of Us datasets where we showed significant time and cost benefits over the baseline SAIGE model.

genetics↗

bioRxiv2024

MSA: scalable DNA methylation screening BeadChip for high-throughput trait association studies

Epigenome-wide association studies (EWAS) are transforming our understanding of the interplay between epigenetics and complex human traits and phenotypes. We introduce the Methylation Screening Array (MSA), a new iteration of the Infinium technology for scalable and quantitative screening of trait associations of nuanced ternary-code cytosine modifications in larger, more inclusive, and stratified human populations. MSA integrates EWAS, single-cell, and cell-type-resolved methylome profiles, covering diverse human traits and diseases. Our first MSA applications yield multiple biological insights: we revealed a previously unappreciated role of 5-hydroxymethylcytosine (5hmC) in trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5-methylcytosines (5mCs) in defining tissues and cells epigenetic identities. In-depth analyses highlighted the cell type context of EWAS and GWAS hits. Using this platform, we conducted a comprehensive human 5hmC aging EWAS, discovering tissue-invariant and tissue-specific aging dynamics, including distinct tissue-specific rates of mitotic hyper- and hypomethylation rates. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

genomics↗

bioRxiv2024

LncCE: Landscape of Cellular-Elevated LncRNAs in Single Cells Across Normal and Cancer Tissues

Long non-coding RNAs (lncRNAs) have emerged as significant players for maintaining the morphology and function of tissues or cells. The precise regulatory effectiveness of lncRNA is closely associated with the spatial expression patterns across tissues and cells. Here, we proposed the Cellular-Elevated LncRNA (LncCE) database to systematically explore cellular-elevated (CE) lncRNAs across normal and cancer tissues in single cells. LncCE encompasses 87,946 CE lncRNAs of 149 cell types by analyzing 181 single-cell RNA sequencing (scRNA-seq) datasets, involved in 20 fetal normal tissues, 59 adult normal tissues, as well as 32 adult and 5 pediatric cancer tissues.Two main search options were provided via a given lncRNA name or a cell type. The output results emphasize both qualitative and quantitative expression features of lncRNAs across different cell types, co-expression with protein-coding genes as well as their involved in biological functions. For cancers, LncCE particularly provided quantitative figures for exhibiting their expression changes compared to control samples and clinical associations with patient overall survivals. Together, LncCE offers an extensive, quantitative and user-friendly interface to investigate cellular-elevated expression atlas for lncRNAs across normal and cancers tissues at single-cell level. The LncCE database is available at http://bio-bigdata.hrbmu.edu.cn/LncCE.

cancer biology↗

bioRxiv2024

Impaired Cortico-Amygdala Functional Connectivity Can Drive Social Behavior Deficits in Synucleinopathies

The small molecule protein -synuclein forms insoluble aggregates in a group of neurological disorders, including Parkinsons disease and dementia with Lewy bodies (DLB), which are collectively called synucleinopathies. In PD and DLB, the amygdala has been identified as a particularly susceptible region in the brain for the deposition of Lewy-like -synuclein aggregates. Though -synuclein aggregation is closely associated with neurodegeneration, there is a poor correlation between neurodegeneration in the amygdala and the clinical features of PD/DLB. We hypothesize that, prior to neurodegeneration, -synuclein aggregation disrupts functional cortical modulation of the amygdala circuits, leading to emotion dysregulation in synucleinopathies. In the present study, we combined electrophysiology, optogenetics, mouse model of synucleinopathies, and behavioral analysis to test this hypothesis. Using an -synuclein preformed fibrils (PFFs)-based mouse model of synucleinopathies, we reported dynamic changes in the levels of -synuclein pathology in the basolateral amygdala (BLA). Such dynamic changes of pathology associated with a decreased cortico-BLA connection strength prior to a significant loss of cortical axon terminals. In parallel to the reduced cortico-BLA connection, PFFs-injected mice manifested impaired social preference behavior. The impaired sociability of PFFs-injected mice could be rescued by chemogenetic stimulation of cortico-BLA inputs. Altogether, we presented a series of evidence to delineate key circuit events associated with -synuclein pathology development in the amygdala circuits. The present work highlights the necessity of a thorough investigation of functional consequences of -synuclein aggregation to advance our understand of pathophysiology of synucleinopathies and development of effective therapies.

neuroscience↗

bioRxiv2024

Antigen-driven expansion of public clonal T cell populations in inflammatory bowel diseases

BackgroundInflammatory Bowel Diseases (IBDs), including Crohns disease (CD) and ulcerative colitis (UC), are known to involve shifts in the T-cell repertoires of affected individuals. These include a reduction in regulatory T cells in both diseases, increase in TNF production in CD, expansion of an unconventional T-cell population in CD, and clonal expansion of abundant T-cell populations in CD mucosal tissue. There are also differential HLA risk and protective alleles between CD and UC, implying CD- and UC-specific repertoire changes that have not yet been identified. MethodsWe performed ImmunoSequencing on blood samples from 3,853 CD cases, 1,803 UC cases, and 5,596 healthy controls. For each sample we imputed HLA type and cytomegalovirus (CMV) infection status based on public T-cell receptor {beta} (TCRB) usage and identified public TCRBs enriched in CD or UC cases. FindingsWe determine that there is more expansion across clonotypes in CD, but not UC, compared with healthy controls. We also identify novel interactive effects of HLA-DQ heterodimers with CD and UC risk. Strikingly, from blood we identify public TCRBs specifically expanded in CD or UC. These sequences are more abundant in intestinal mucosal samples, form groups of similar CDR3 sequences, and can be associated to specific HLA alleles. Although the prevalence of these sequences is higher in ileal and ileocolonic CD than colonic CD or UC, the TCRB sequences themselves are shared across CD and not between CD and UC. InterpretationThere are peptide antigens that commonly evoke immune reactions in IBD cases and rarely in non-IBD controls. These antigens differ between CD and UC. CD, particularly ileal CD, also seems to involve more substantial changes in clonal population structure than UC, compared to healthy controls.

immunology↗

bioRxiv2024

Multi-omics Reveals Immune Response and Metabolic Profiles during High-Altitude Mountaineering

The physiological perturbations induced by high-altitude exposure in mountain climbers, manifesting as metabolic and immunologic deviations, have been previously reported but are not fully understood. In this study, we obtained longitudinal multi-omic profiles of blood samples for healthy mountain climbers during two mountaineering stages (acclimatization and extreme altitude mountaineering). Our integrative assay included metabolomics and lipidomics profiling of plasma coupled with single-cell transcriptomic analysis of 375,722 immune cells. Longitudinal analysis revealed dynamic immune response profiles, during the acclimatization period, characterized by the downregulation of inflammatory responses in monocytes and classical dendritic cells (cDCs) and an increase in the proportion of cytotoxic CD8+ T cells with enhanced immune effector processes. In contrast, during extreme altitude mountaineering, the activation of inflammatory responses and impairment of T cell effector function were observed, concomitant with an increased cellular response to hypoxia and oxidative stress pathways. Furthermore, we found upregulated glycolysis and antioxidant gene expression during extreme altitude mountaineering, which was primarily orchestrated by HIF1A and NFE2L2, while decreased expression of these genes was observed in dysregulated plasmacytoid dendritic cells (pDCs). Finally, high-resolution plasma metabolic analysis revealed significant alterations in the metabolism of climbers, involving enhanced glutamine and fatty acid metabolism.

bioinformatics↗

bioRxiv2024

Multi-omics delineate growth factor network underlying exercise effects in an Alzheimer's mouse model

Physical exercise represents a primary defense against age-related cognitive decline and neurodegenerative disorders like Alzheimers disease (AD). To impartially investigate the underlying mechanisms, we conducted single-nucleus transcriptomic and chromatin accessibility analyses (snRNA-seq and ATAC-seq) on the hippocampus of mice carrying AD-linked NL-G-F mutations in the amyloid precursor protein gene (APPNL-G-F) following prolonged voluntary wheel-running exercise. Our study reveals that exercise mitigates amyloid-induced changes in both transcriptomic expression and chromatin accessibility through cell type-specific transcriptional regulatory networks. These networks converge on the activation of growth factor signaling pathways, particularly the epidermal growth factor receptor (EGFR) and insulin signaling, correlating with an increased proportion of immature dentate granule cells and oligodendrocytes. Notably, the beneficial effects of exercise on neurocognitive functions can be blocked by pharmacological inhibition of EGFR and the downstream phosphoinositide 3-kinases (PI3K). Furthermore, exercise leads to elevated levels of heparin-binding EGF (HB-EGF) in the blood, and intranasal administration of HB-EGF enhances memory function in sedentary APPNL-G-F mice. These findings offer a panoramic delineation of cell type-specific hippocampal transcriptional networks activated by exercise and suggest EGF-related growth factor signaling as a druggable contributor to exercise-induced memory enhancement, thereby suggesting therapeutic avenues for combatting AD-related cognitive decline.

animal behavior and cognition↗

bioRxiv2024

Cell-free reconstitution of HIV-1 innate immune sensing reveals the capsid is a molecular cloak that protects reverse transcripts from cGAS

Retroviruses can be detected by the innate immune sensor cyclic GMP-AMP synthase (cGAS), which recognizes reverse-transcribed DNA and activates an antiviral response. However, the extent to which HIV-1 shields its genome from cGAS recognition remains unclear. To study this process in mechanistic detail, we reconstituted reverse transcription, genome release, and innate immune sensing of HIV-1 in a cell-free system. We found that wild-type HIV-1 capsids protect viral genomes from cGAS even after completing reverse transcription. Viral DNA could be "deprotected" by thermal stress, capsid mutations, or reduced concentrations of inositol hexakisphosphate (IP6) that destabilize the capsid. Strikingly, the capsid inhibitor lenacapavir also disrupted viral cores and dramatically potentiated cGAS activity, both in vitro and in cellular infections. Our results provide biochemical evidence that the HIV-1 capsid lattice conceals the genome from cGAS and that chemical or physical disruption of the viral core can expose HIV-1 DNA and activate innate immune signaling.

microbiology↗

bioRxiv2024

A tale of two tumors: differential, but detrimental, effects of glioblastoma extracellular vesicles (EVs) on normal human brain cells

Glioblastomas (GBMs) are dreadful brain tumors with abysmal survival outcomes. GBM EVs dramatically affect normal brain cells (largely astrocytes) constituting the tumor microenvironment (TME). EVs from different patient-derived GBM spheroids induced differential transcriptomic, secretomic, and proteomic effects on cultured astrocytes/brain tissue slices as GBM EV recipients. The net outcome of brain cell differential changes nonetheless converges on increased tumorigenicity. GBM spheroids and brain slices were derived from neurosurgical patient tissues following informed consent. Astrocytes were commercially obtained. EVs were isolated from conditioned culture media by ultrafiltration, ultraconcentration, and ultracentrifugation. EVs were characterized by nanoparticle tracking analysis, electron microscopy, biochemical markers, and proteomics. Astrocytes/brain tissues were treated with GBM EVs before downstream analyses. EVs from different GBMs induced brain cells to alter secretomes with pro-inflammatory or TME-modifying (proteolytic) effects. Astrocyte responses ranged from anti-viral gene/protein expression and cytokine release to altered extracellular signal-regulated protein kinase (ERK1/2) signaling pathways, and conditioned media from EV-treated cells increased GBM cell proliferation. Thus, astrocytes/brain slices treated with different GBM EVs underwent non-identical changes in various omics readouts and other assays, indicating "personalized" tumor-specific GBM EV effects on the TME. This raises concern regarding reliance on "model" systems as a sole basis for translational direction. Nonetheless, net downstream impacts from differential cellular and TME effects still led to increased tumorigenic capacities for the different GBMs.

cancer biology↗

bioRxiv2024

Microbial Analysis and Sanitization of Hydroponic Farming Facilities in Singapore

This study performed microbial analysis of nutrient film technique (NFT) hydroponic systems at three indoor farms in Singapore. To justify the necessity to sanitize the hydroponic systems, strong biofilm-forming bacteria were isolated from the facility and investigated with their influence on Salmonella colonizing on polyvinyl chloride (PVC) coupons in hydroponic nutrient solutions. Last, sanitization solutions were evaluated with both laboratory-scale and field-scale tests. As a result, the microbiome composition in NFT systems was found to be highly farm-specific. Strong biofilm formers Corynebacterium tuberculostearicum C2 and Pseudoxanthomonas mexicana C3 were found to facilitate the attachment and colonization of Salmonella on PVC coupons. When forming dual-species biofilms, the presence of C2 and C3 also significantly promoted the growth of Salmonella (P < 0.05). Sodium hypochlorite (NaOCl) exhibited superior efficacy in biofilm removal compared to hydrogen peroxide (H2O2) and sodium percarbonate (SPC). NaOCl at 50 ppm reduced C2 and C3 counts to < 1 log CFU/cm2 within 12 h, whereas neither 3% H2O2 nor 1% SPC achieved such an effect. In operational hydroponic systems, the concentration of NaOCl needed to achieve biofilm elimination increased to 500 ppm, likely due to the presence of organic matter accumulated during the crop cultivation and the higher persistence of the naturally formed multispecies biofilms. The sanitization (500 ppm NaOCl for 12 h) did not impede subsequent plant growth but chlorination by-product chlorate was detected with high levels from the hydroponic solution and plants in the sanitized systems without rinsing. IMPORTANCEThis studys significance lies first in its elucidation of the necessity to sanitize the hydroponic farming systems. The microbiome in hydroponic systems, although most of the times non-pathogenic, might serve as a hotbed for pathogens colonization and thus pose a higher risk for food safety. We thus explored sanitization solutions with both laboratory-scale and field-scale tests. Of the three tested sanitizers, NaOCl was the most effective and economical option, whereas one must note the vital importance of rinsing the hydroponic systems after sanitization with NaOCl.

microbiology↗

bioRxiv2024

Large-scale statistical mapping of T-cell receptor β sequences to Human Leukocyte Antigens

T-cell receptors (TCRs) interacting with peptides presented by human leukocyte antigens (HLAs) are the foundation of the adaptive immune system but population-level analysis of TCR-HLA interactions is lacking. Here we statistically associate[~] 106 public TCRs to specific HLAs using the TCR{beta} repertoires sampled from 4,144 HLA-genotyped subjects. The TCRs we associate are specific to unique HLA allotypes, not allelic groups, and to the paired -{beta} heterodimer of class II HLAs though exceptions are observed. This specificity permits highly accurate imputation of 248 class I and II HLAs from the TCR{beta} repertoire. Notably, 45 HLA-DP and -DQ heterodimers lack associated TCRs because they likely arise from non-functional trans-complementation. The public class I and II HLA-associated TCRs we identify are primarily expressed on CD8+ and CD4+ memory T cells, respectively, which are responding to various common antigens. Our results recapitulate fundamental biology, provide insights into the functionality of HLAs and demonstrate the power and potential of population-level TCR repertoire sequencing.

immunology↗

bioRxiv2024

Single-Molecule Orientation Imaging Reveals the Nano-Architecture of Amyloid Fibrils Undergoing Growth and Decay

Amyloid-beta (A{beta}42) aggregates are characteristic signatures of Alzheimers disease, but probing how their nanoscale architectures influence their growth and decay remains challenging using current technologies. Here, we apply time-lapse single-molecule orientation-localization microscopy (SMOLM) to measure the orientations and rotational "wobble" of Nile blue (NB) molecules transiently binding to A{beta}42 fibrils. We quantify correlations between fibril architectures, measured by SMOLM, and their growth and decay visualized by single-molecule localization microscopy (SMLM). We discover that stable A{beta}42 fibrils tend to be well-ordered, signified by well-aligned NB orientations and small wobble. SMOLM also shows that increasing order and disorder are signatures of growing and decaying A{beta}42 fibrils, respectively. We also observe SMLM-invisible fibril remodeling, including steady growth and decay patterns that conserve {beta}-sheet organization. SMOLM reveals that increased heterogeneity in fibril architectures is correlated with more dynamic remodeling and that large-scale fibril remodeling tends to originate from local regions that exhibit strong heterogeneity.

biophysics↗

bioRxiv2024

mLiftOver: Harmonizing Data Across Infinium DNA Methylation Platforms

Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the EPIC and the HumanMethylation450 (HM450) BeadChip. We present mLiftOver, a user-friendly tool that transfers probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells. Availability and implementationmLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 3.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/blob/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license.

bioinformatics↗

bioRxiv2024

Cancer Stemness Online: A resource for investigating cancer stemness and associations with immune response

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features, which are potential culprit in immunotherapy resistance. Although the state-of-art predictive computational methods have facilitated predicting the cancer stemness, currently there is no efficient resource that can meet various requirements of usage. Here, we presented the Cancer Stemness Online, an integrated resource for efficiently scoring cancer stemness potential at bulk and single-cell level. The resource integrates 8 robust predictive algorithms as well as 27 signature gene sets associated with cancer stemness for predicting the stemness scores. Downstream analyses were performed from five different aspects, including identifying the signature genes of cancer stemness, exploring the association with cancer hallmarks, cellular states, immune response and communication with immune cells, investigating the contributions for patient survival and the robustness analysis of cancer stemness among different methods. Moreover, the pre-calculated cancer stemness atlas for more than 40 cancer types can be accessed by users. Both the tables and diverse visualization for the analytical results are available for download. Together, Cancer Stemness Online is a powerful resource for scoring cancer stemness and going deeper and wider in the downstream functional interpretation, including immune response as well as cancer hallmark. Cancer Stemness Online is freely accessible at http://bio-bigdata.hrbmu.edu.cn/CancerStemnessOnline.

bioinformatics↗

bioRxiv2024

Seq2MAIT: A Novel Deep Learning Framework for Identifying Mucosal Associated Invariant T (MAIT) Cells

Mucosal-associated invariant T (MAIT) cells are a group of unconventional T cells that mainly recognize bacterial vitamin B metabolites presented on MHC-related protein 1 (MR1). MAIT cells have been shown to play an important role in controlling bacterial infection and in responding to viral infections. Furthermore, MAIT cells have been implicated in different chronic inflammatory diseases such as inflammatory bowel disease and multiple sclerosis. Despite their involvement in different physiological and pathological processes, a deeper understanding of MAIT cells is still lacking. Arguably, this can be attributed to the difficulty of quantifying and measuring MAIT cells in different biological samples which is commonly done using flow cytometry-based methods and single-cell-based RNA sequencing techniques. These methods mostly require fresh samples which are difficult to obtain, especially from tissues, have low to medium throughput, and are costly and labor-intensive. To address these limitations, we developed sequence-to-MAIT (Seq2MAIT) which is a transformer-based deep neural network capable of identifying MAIT cells in bulk TCR-sequencing datasets, enabling the quantification of MAIT cells from any biological materials where human DNA is available. Benchmarking Seq2MAIT across different test datasets showed an average area-under-the-receiver-operator-curve (AU[ROC]) >0.80. In conclusion, Seq2MAIT is a novel, economical, and scalable method for identifying and quantifying MAIT cells in virtually any biological sample.

bioinformatics↗

bioRxiv2024

Structures of transcription-translation coupling complexes at each stage of the translation cycle

In the bacterium Escherichia coli, efficient expression of protein-coding genes is achieved through physical coupling of RNA polymerase (RNAP) synthesizing an mRNA and the first ribosome translating the mRNA, with transcription elongation factors NusG and NusA bridging RNAP and ribosome in a transcription-translation complex (TTC). Recent structural studies suggest that the flexibility in NusG and NusA accommodates the changes in ribosome conformation that occur during the translation cycle, but details have been unclear. Here, we report cryo-EM structures of TTCs at each stage of the translation cycle as an actively translating ribosome approaches to a halted transcription complex. We observe sequential conversion of a loosely coupled TTC (TTC-LC) to a tightly coupled TTC (TTC-B) to a collided TTC (TTC-A) as the ribosome approaches the transcription complex. We show that flexibility of the NusG linker and NusA "pantograph" enable TTC-LC and TTC-B to accommodate ribosome conformation at each stage of the translation cycle. We show that, in TTC-A, steric clash between ribosome and RNAP upon ribosome 30S head swiveling inhibits 30S head swiveling, consistent with translation slowdown, and applies mechanical force to the trailing edge of RNAP, causing transcription termination. Our results define the structures and properties of loosely coupled, tightly coupled, and collided TTCs at each stage of the translation cycle.

molecular biology↗

bioRxiv2024

Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA

Pathway analysis is a crucial analytical phase in disease research on single-cell RNA sequencing (scRNA-seq) data, offering biological interpretations based on prior knowledge. However, currently available tools for generating cell-level pathway activity scores (PAS) exhibit computational inefficacy in large-scale scRNA-seq datasets. Besides, disease-related pathways are commonly identified by cross-condition comparisons in each cell type, neglecting the potential multicellular patterns. Here, we present single-cell pathway activity factor analysis (scPAFA), a Python library designed for large-scale single-cell dataset allowing rapid PAS computation and uncovering biologically interpretable disease-related multicellular pathway modules, which are low-dimensional representations of disease-related PAS variance in multiple cell types. Application on colorectal cancer (CRC) dataset with 371,223 cells and large-scale lupus atlas over 1.2 million cells demonstrated that scPAFA can achieve > 33-fold decreases in runtime of PAS computation and further identified reliable and interpretable multicellular pathway modules that capture the transcriptomic features of CRC tumor status and transcriptional abnormalities in lupus patients, respectively.

bioinformatics↗