RAVAR: a curated repository for rare variant-trait associations.

Rare variants contribute significantly to the genetic causes of complex traits, as they can have much larger effects than common variants and account for much of the missing heritability in genome-wide association studies. The emergence of UK Biobank scale datasets and accurate gene-level rare variant-trait association testing methods have dramatically increased the number of rare variant associations that have been detected. However, no systematic collection of these associations has been carried out to date, especially at the gene level. To address the issue, we present the Rare Variant Association Repository (RAVAR), a comprehensive collection of rare variant associations. RAVAR includes 95 047 high-quality rare variant associations (76186 gene-level and 18 861 variant-level associations) for 4429 reported traits which are manually curated from 245 publications. RAVAR is the first resource to collect and curate published rare variant associations in an interactive web interface with integrated visualization, search, and download features. Detailed gene and SNP information are provided for each association, and users can conveniently search for related studies by exploring the EFO tree structure and interactive Manhattan plots. RAVAR could vastly improve the accessibility of rare variant studies. RAVAR is freely available for all users without login requirement at http://www.ravar.bio.

AGF-PPIS: A protein-protein interaction site predictor based on an attention mechanism and graph convolutional networks.

Protein-protein interactions play an important role in various biological processes. Interaction among proteins has a wide range of applications. Therefore, the correct identification of protein-protein interactions sites is crucial. In this paper, we propose a novel predictor for protein-protein interactions sites, AGF-PPIS, where we utilize a multi-head self-attention mechanism (introducing a graph structure), graph convolutional network, and feed-forward neural network. We use the Euclidean distance between each protein residue to generate the corresponding protein graph as the input of AGF-PPIS. On the independent test dataset Test_60, AGF-PPIS achieves superior performance over comparative methods in terms of seven different evaluation metrics (ACC, precision, recall, F1-score, MCC, AUROC, AUPRC), which fully demonstrates the validity and superiority of the proposed AGF-PPIS model. The source codes and the steps for usage of AGF-PPIS are available at https://github.com/fxh1001/AGF-PPIS.

ABC portal: a single-cell database and web server for blood cells.

ABC portal (http://abc.sklehabc.com) is a database and web portal containing 198 single-cell transcriptomic datasets of development, differentiation and disorder of blood/immune cells. All the datasets were re-annotated with a manually curated and unified single-cell reference, especially for the haematopoietic stem and progenitor cells. ABC portal provides web-based interactive analysis modules, especially a comprehensive cell-cell communication analysis and disease-related gene signature analysis. Importantly, ABC portal allows customized sample selection based on a combination of several metadata for downstream analysis and comparison analysis across datasets. ABC portal also allows users to select multiple cell types for analysis in the modules. Together, ABC portal provides an interactive interface of single-cell data exploration and re-analysis with customized analysis modules for the researchers and clinicians, and will facilitate understanding of haematopoiesis and blood/immune disorders.

msBERT-Promoter: a multi-scale ensemble predictor based on BERT pre-trained model for the two-stage prediction of DNA promoters and their strengths.

BACKGROUND: A promoter is a specific sequence in DNA that has transcriptional regulatory functions, playing a role in initiating gene expression. Identifying promoters and their strengths can provide valuable information related to human diseases. In recent years, computational methods have gained prominence as an effective means for identifying promoter, offering a more efficient alternative to labor-intensive biological approaches. RESULTS: In this study, a two-stage integrated predictor called "msBERT-Promoter" is proposed for identifying promoters and predicting their strengths. The model incorporates multi-scale sequence information through a tokenization strategy and fine-tunes the DNABERT model. Soft voting is then used to fuse the multi-scale information, effectively addressing the issue of insufficient DNA sequence information extraction in traditional models. To the best of our knowledge, this is the first time an integrated approach has been used in the DNABERT model for promoter identification and strength prediction. Our model achieves accuracy rates of 96.2% for promoter identification and 79.8% for promoter strength prediction, significantly outperforming existing methods. Furthermore, through attention mechanism analysis, we demonstrate that our model can effectively combine local and global sequence information, enhancing its interpretability. CONCLUSIONS: msBERT-Promoter provides an effective tool that successfully captures sequence-related attributes of DNA promoters and can accurately identify promoters and predict their strengths. This work paves a new path for the application of artificial intelligence in traditional biology.

Utilization trend of prebiopsy multiparametric magnetic resonance imaging and its impact on prostate cancer detection: Real-world insights from a high-volume center in southwest China.

BACKGROUND: Data on the utilization and effects of prebiopsy prostate multiparametric magnetic resonance imaging (mpMRI) to support its routine use in real-world setting are still scarce. OBJECTIVE: To evaluate the change of clinical practice of prebiopsy mpMRI over time, and assess its diagnostic accuracy. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively analyzed data from 6168 patients who underwent primary prostate biopsy (PBx) between January 2011 and December 2021 and had prostate-specific antigen (PSA) values ranging from 3 to 100 ng/mL. INTERVENTION: Prebiopsy MRI at the time of PBx. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed general linear regression and to elucidate trends in the annual use of prebiopsy mpMRI and conducted multivariable logistic regression to evaluate the potential benefits of incorporating prebiopsy mpMRI for prostate cancer (PCa) detection. RESULTS AND LIMITATIONS: The utilization of prebiopsy mpMRI significantly increased from 9.2% in 2011 to 75.0% in 2021 (p < 0.001). In addition, prebiopsy mpMRI significantly reduced negative PBx by 8.6% while improving the detection of clinically significant PCa (csPCa) by 7.0%. Regression analysis showed that the utilization of prebiopsy mpMRI was significantly associated with a 48% (95% confidence interval [CI]: 1.19-1.84) and 36% (95% CI: 1.12-1.66) increased PCa detection rate in the PSA 3-10 ng/mL and 10-20 ng/mL groups, respectively; and a 34% increased csPCa detection rate in the PSA 10-20 ng/mL group (95% CI: 1.09-1.64). The retrospective design and the single center cohort constituted the limitations of this study. CONCLUSIONS: Our study demonstrated a notable rise in the utilization of prebiopsy mpMRI in the past decade. The adoption of this imaging technique was significantly associated with an increased probability of detecting prostate cancer. PATIENT SUMMARY: From 2011 to 2021, we demonstrated a steady increase in the utilization of prebiopsy mpMRI among biopsy-naïve men. We also confirmed the positive impact of prebiopsy mpMRI utilization on the detection of prostate cancer.

Enhanced Electron Transport and Mitigated Voltage Loss in Perovskite Photovoltaics Using Sb2O5@SnO2 Composite Electron Transport Layer.

The efficacy of electron transport layers (ETLs) is pivotal for optimizing the device performance of perovskite photovoltaic applications. However, colloidal dispersions of SnO2 are prone to aggregation and possess structural defects, such as terminal-hydroxyls (OHT) and oxygen vacancies (VOs), which can degrade the quality of ETLs, impede charge extraction and transport, and affect the nucleation and growth processes of the perovskite layer. In this study, the Sb(OH)4 - ions hydrolyzed from SbCl3 in colloidal dispersion can bind to defect sites and effectively stabilize the SnO2 nanocrystals are demonstrated. Upon oxidative annealing, a Sb2O5@SnO2 composite film is formed, in which the Sb2O5 not only mitigates the aforementioned defects but also broadens the energy range of unoccupied states through its dispersed conduction band. The increased electron affinity (EA) facilitates more efficient capture of photoexcited electrons from the perovskite layer, thus augmenting electron extraction and minimizing electron-hole recombination. As a result, a significant improvement in power conversion efficiency (PCE) from 22.60% to 24.54% is achieved, with an open circuit voltage (VOC) of up to 1.195 V, along with excellent stability of unsealed devices under various conditions. This study provides valuable insights for the understanding and design of ETLs in perovskite photovoltaic applications.

Epidemiological and Genomic analysis of Vibrio parahaemolyticus isolated from imported travelers at the port of Shanghai, China (2017-2019).

BACKGROUND: Vibrio parahaemolyticus is the predominant etiological agent of seafood-associated foodborne illnesses on a global scale. It is essential to elucidate the mechanisms by which this pathogen disseminates. Given the existing research predominantly concentrates on localized outbreaks, there is a pressing necessity for a comprehensive investigation to capture strains of V. parahaemolyticus cross borders. RESULTS: This study examined the frequency and genetic attributes of imported V. parahaemolyticus strains among travelers entering Shanghai Port, China, between 2017 and 2019.Through the collection of 21 strains from diverse countries and regions, Southeast Asia was pinpointed as a significant source for the emergence of V. parahaemolyticus. Phylogenetic analysis revealed clear delineation between strains originating from human and environmental sources, emphasizing that underlying genome data of foodborne pathogens is essential for environmental monitoring, food safety and early diagnosis of diseases. Furthermore, our study identified the presence of virulence genes (tdh and tlh) and approximately 120 antibiotic resistance-related genes in the majority of isolates, highlighting their crucial involvement in the pathogenesis of V. parahaemolyticus. CONCLUSIONS: This research enhanced our comprehension of the worldwide transmission of V. parahaemolyticus and its antimicrobial resistance patterns. The findings have important implications for public health interventions and antimicrobial stewardship strategies, underscoring the necessity for epidemiological surveillance of pathogen at international travel hubs.

Impact of preoperative antiviral therapy on the prognosis of hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: For chronic hepatitis B virus (HBV) infection patients, increasing evidence has demonstrated the effectiveness of expanding the indications and applicable population for antiviral therapy. However, the expanded indication of antiviral therapy for hepatocellular carcinoma (HCC) remains to be further explored. METHODS: 196 HBV-related HCC patients who received radical hepatectomy and nucleos(t)ide analogues (NAs) therapy at Sichuan Provincial People's Hospital were enrolled in this study. HCC recurrence, overall survival (OS), early virological (VR) and biochemical responses (BR) of patients were compared between different NAs therapy and the use of anti-programmed cell death protein 1 (PD-1) therapy. RESULTS: NAs therapy at different timing of surgery was a strong independent risk factor for postoperative recurrence and overall mortality of HBV-related HCC patients. Furthermore, in HCC patients who received postoperative anti-PD-1 therapy, patients with HBV DNA < 1000 copy/mL had significantly better recurrence-free survival (RFS) and OS than those with HBV DNA ≥ 1000 copy/mL (HR: 7.783; P = 0.002; HR: 6.699; P < 0.001). However, the differences of RFS and OS rates between entecavir group and tenofovir disoproxil fumarate group were not statistically significant. Similar results were also observed in the rates of early VR, BR and combined VR and BR. CONCLUSION: Timely and reasonable preoperative NAs therapy showed clinical benefit in improving the prognosis of patients with HBV-related HCC, even in the case of normal alanine aminotransferase (ALT) level and negative hepatitis e antigen (HBeAg). Furthermore, a possible synergistic effect between antiviral therapy and anti-PD-1 therapy was founded and need further verification.

Alleviating effect of vagus nerve cutting in Salmonella-induced gut infections and anxiety-like behavior via enhancing microbiota-derived GABA.

The vagus nerve, a pivotal link within the gut-brain axis, plays a critical role in maintaining homeostasis and mediating communication between the gastrointestinal tract and the brain. It has been reported that gastrointestinal infection by Salmonella typhimurium (S. typhimurium) triggers gut inflammation and manifests as anxiety-like behaviors, yet the mechanistic involvement of the vagus nerve remains to be elucidated. In this study, we demonstrated that unilateral cervical vagotomy markedly attenuated anxiety-like behaviors induced by S. typhimurium SL1344 infection in C57BL/6 mice, as evidenced by the open field test and marble burying experiment. Furthermore, vagotomy significantly diminished neuronal activation within the nucleus of the solitary tract and amygdala, alongside mitigating aberrant glial cell activation in the hippocampus and amygdala. Additionally, vagotomy notably decreases serum endotoxin levels, counters the increase in splenic Salmonella concentration, and modulates the expression of inflammatory cytokines-including IL-6, IL-1ß, and TNF-α-in both the gastrointestinal tract and brain, with a concurrent reduction in IL-22 and CXCL1 expression. This intervention also fostered the enrichment of beneficial gut microbiota, including Alistipes and Lactobacillus species, and augmented the production of gamma-aminobutyric acid (GABA) in the gut. Administration of GABA replicated the vagotomy's beneficial effects on reducing gut inflammation and anxiety-like behavior in infected mice. However, blockade of GABA receptors with picrotoxin abrogated the vagotomy's protective effects against gut inflammation, without influencing its impact on anxiety-like behaviors. Collectively, these findings suggest that vagotomy exerts a protective effect against infection by promoting GABA synthesis in the colon and alleviating anxiety-like behavior. This study underscores the critical role of the vagus nerve in relaying signals of gut infection to the brain and posits that targeting the gut-brain axis may offer a novel and efficacious approach to preventing gastrointestinal infections and associated behavioral abnormalities.

Long-term exposure to ambient ozone and adult-onset asthma: A prospective cohort study.

BACKGROUND: The association between long-term exposure to ozone (O3) and adult-onset asthma (AOA) remains inconclusive, and analysis of causality is lacking. OBJECTIVES: To examine the causal association between long-term O3 exposure and AOA. METHODS: A prospective cohort study of 362,098 participants was conducted using the UK Biobank study. Incident cases of AOA were identified using health administrative data of the National Health Services. O3 exposure at participants' residential addresses was estimated by a spatio-temporal model. Instrumental variable (IV) modelling was used to analyze the causal association between O3 exposure and AOA, by incorporating wind speed and planetary boundary layer height as IVs into time-dependent Cox model. Negative control outcome (accidental injury) was also used to additionally evaluate unmeasured confounding. RESULTS: During a mean follow-up of 11.38 years, a total of 10,973 incident AOA cases were identified. A U-shaped concentration-response relationship was observed between O3 exposure and AOA in the traditional Cox models with HR of 0.916 (95% CI: 0.888, 0.945) for O3 at low levels (<38.17 ppb), and 1.204 (95% CI: 1.168, 1.242) for O3 at high levels (≥38.17 ppb). However, in the IV analysis we only found a statistically significant association between high-level O3 exposure and AOA risk, but not for low-level O3 exposure. No significant associations between O3 exposure and accidental injury were observed. CONCLUSION: Our findings suggest a potential causal relationship between long-term exposure to high-level ambient O3 and increased risks of AOA.

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study.

The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases. However, there are currently no resources providing a comprehensive listing of gene-disease associations discovered by TWAS from published GWAS summary statistics. TWAS analyses are also difficult to conduct due to the complexity of TWAS software pipelines. To address these issues, we introduce a new resource called webTWAS, which integrates a database of the most comprehensive disease GWAS datasets currently available with credible sets of potential causal genes identified by multiple TWAS software packages. Specifically, a total of 235 064 gene-diseases associations for a wide range of human diseases are prioritized from 1298 high-quality downloadable European GWAS summary statistics. Associations are calculated with seven different statistical models based on three popular and representative TWAS software packages. Users can explore associations at the gene or disease level, and easily search for related studies or diseases using the MeSH disease tree. Since the effects of diseases are highly tissue-specific, webTWAS applies tissue-specific enrichment analysis to identify significant tissues. A user-friendly web server is also available to run custom TWAS analyses on user-provided GWAS summary statistics data. webTWAS is freely available at http://www.webtwas.net.

Associations between maternal exposure to air pollution during pregnancy and trajectories of infant growth: A birth cohort study.

OBJECTIVE: We examined the relationships between infants' growth trajectories and prenatal exposure to air pollution, which is still under-investigated. METHODS: A birth cohort study was constructed using medical records of pregnant women and infants born between 2015 and 2019 in Foshan, China. Using satellite-based spatial-temporal models, prenatal exposure to air pollutants including particulate matter with an aerodynamic dimension of < 2.5 µm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) was assessed at each woman's residence. Latent class growth modeling was used to identify trajectories of physical (body length and weight) growth and neurodevelopment, which were repeatedly measured within 1 year after birth. Logistic regression models were used to investigate the associations between prenatal exposure to air pollution and the risks of growth disorders, adjusting for an array of potential confounders. RESULTS: We identified two growth trajectories for body length [normal: 3829 (93%); retardation: 288 (7%)], three for weight [normal: 2475 (59.6%); retardation: 390 (9.4%); overgrowth: 1287 (31%)], and two for neurodevelopment [normal: 956 (66.1%); retardation: 491 (33.9%)]. For exposure over whole pregnancy, SO2 was associated with an increased risk of body length retardation (OR for per 1 µg/m3 increment: 1.09, 95%CI: 1.01-1.17); PM2.5 (OR: 1.05, 95%CI: 1.03-1.07), SO2 (OR: 1.15, 95%CI: 1.08-1.22), and NO2 (OR: 1.05, 95%CI: 1.03-1.07) were positively associated with neurodevelopmental retardation. Such associations appeared stronger for exposures over the first and second trimesters. No significant associations were detected for weight growth. CONCLUSIONS: Maternal exposure to air pollution during pregnancy was associated with higher risks of impairments in both physical growth, particularly body length, and neurodevelopment.

Fully Aromatic Self-Assembled Hole-Selective Layer toward Efficient Inverted Wide-Bandgap Perovskite Solar Cells with Ultraviolet Resistance.

Ultraviolet-induced degradation has emerged as a critical stability concern impeding the widespread adoption of perovskite solar cells (PSCs), particularly in the context of phase-unstable wide-band gap perovskite films. This study introduces a novel approach by employing a fully aromatic carbazole-based self-assembled monolayer, denoted as (4-(3,6-dimethoxy-9H-carbazol-9-yl)phenyl)phosphonic acid (MeO-PhPACz), as a hole-selective layer (HSL) in inverted wide-band gap PSCs. Incorporating a conjugated linker plays a pivotal role in promoting the formation of a dense and highly ordered HSL on substrates, facilitating subsequent perovskite interfacial interactions, and fostering the growth of uniform perovskite films. The high-quality film could effectively suppress interfacial non-radiative recombination, improving hole extraction/transport efficiency. Through these advancements, the optimized wide-band gap PSCs, featuring a band gap of 1.68 eV, attain an impressive power conversion efficiency (PCE) of 21.10 %. Remarkably, MeO-PhPACz demonstrates inherent UV resistance and heightened UV absorption capabilities, substantially improving UV resistance for the targeted PSCs. This characteristic holds significance for the feasibility of large-scale outdoor applications.

Fluorinated Polyimide Tunneling Layer for Efficient and Stable Perovskite Photovoltaics.

Despite the remarkable progress of perovskite solar cells (PSCs), challenges remain in terms of finding effective and viable strategies to enhance their long-term stability while maintaining high efficiency. In this study, a new insulating and hydrophobic fluorinated polyimide (FPI: 6FDA-6FAPB) was used as the interface layer between the perovskite layer and the hole transport layer (HTL) in PSCs. The functional groups of FPI play a pivotal role in passivating interface defects within the device. Due to its high work function, FPI demonstrates field-effect passivation (FEP) capabilities as an interface layer, effectively mitigating non-radiative recombination at the interface. Notably, the FPI insulating interface layer does not impede carrier transmission at the interface, which is attributed to the presence of hole tunneling effects. The optimized PSCs achieve an outstanding power conversion efficiency (PCE) of 24.61 % and demonstrate excellent stability, showcasing the efficacy of FPI in enhancing device performance and reliability.

Associations of Air Pollution and Genetic Risk With Incident Dementia: A Prospective Cohort Study.

Evidence on the association between air pollution and dementia is accumulating but still inconclusive, and the potential effect modification by genetics is unclear. We investigated the joint effects of air pollution exposure and genetic risk on incident dementia in a prospective cohort study, the UK Biobank study. Land use regression models were used to estimate exposure to ambient particulate matter (PM) in 3 fraction sizes (PM with diameter < 2.5 µm (PM2.5), coarse particles (PM with diameter 2.5-10 µm (PMc)), and PM with diameter < 10 µm (PM10)), PM2.5 absorbance, nitrogen dioxide levels, and nitrogen oxide levels at each individual's baseline residence. A polygenic risk score was calculated as a quantitative measure of genetic dementia risk. Incident cases of dementia were ascertained through linkage to health administrative data sets. Among the 227,840 participants included in the analysis, 3,774 incident dementia cases (including 1,238 cases of Alzheimer disease and 563 cases of vascular dementia) were identified. After adjustment for a variety of covariates, including genetic factors, positive associations were found between exposure to air pollution-particularly PM10, PM2.5 absorbance, and nitrogen dioxide-and incident all-cause dementia and Alzheimer disease but not vascular dementia. No significant interaction between air pollution and genetics was found, either on the multiplicative scale or on the additive scale. Exposure to air pollution was associated with a higher risk of developing dementia regardless of genetic risk.

Air pollution associated with incidence and progression trajectory of chronic lung diseases: a population-based cohort study.

BACKGROUND: No prior study has examined the effects of air pollution on the progression from healthy to chronic lung disease, subsequent chronic lung multimorbidity and further to death. METHODS: We used data from the UK Biobank of 265 506 adults free of chronic lung disease at recruitment. Chronic lung multimorbidity was defined as the coexistence of at least two chronic lung diseases, including asthma, chronic obstructive pulmonary disease and lung cancer. The concentrations of air pollutants were estimated using land-use regression models. Multistate models were applied to assess the effect of air pollution on the progression of chronic lung multimorbidity. RESULTS: During a median follow-up of 11.9 years, 13 863 participants developed at least one chronic lung disease, 1055 developed chronic lung multimorbidity and 12 772 died. We observed differential associations of air pollution with different trajectories of chronic lung multimorbidity. Fine particulate matter showed the strongest association with all five transitions, with HRs (95% CI) per 5 µg/m3 increase of 1.31 (1.22 to 1.42) and 1.27 (1.01 to 1.57) for transitions from healthy to incident chronic lung disease and from incident chronic lung disease to chronic lung multimorbidity, and 1.32 (1.21 to 1.45), 1.24 (1.01 to 1.53) and 1.91 (1.14 to 3.20) for mortality risk from healthy, incident chronic lung disease and chronic lung multimorbidity, respectively. CONCLUSION: Our study provides the first evidence that ambient air pollution could affect the progression from free of chronic lung disease to incident chronic lung disease, chronic lung multimorbidity and death.

Symmetry-Breaking Induced Dipole Enhancement for Efficient Spiro-Type Hole Transporting Materials: Easy Synthesis with High Stability.

Spiral cores are crucial for designing efficient hole transporting materials (HTMs) for perovskite solar cells (PSCs), owing to their no-planar 3D architecture, high thermal stability, good solubility, and beneficial solid-state morphology. A lack of facile synthetic procedures for the spiral core limited the development of novel and stable spiral HTMs. In this regard, a one-step reaction is adopted to produce several novel acceptor-embedded spiral cores containing electron-withdrawing carbonyl group embedded orthogonal spiral conformation. After coupling with triphenylamine donors, symmetry-breaking spiral HTMs with uneven charge distribution can be obtained, bearing the advantages of adjustable dipole moment and enhanced structural stability. A combined theoretical and experimental study shows that the HTM with a stronger dipole moment can easily adsorb on the surface of perovskite via electrostatic potential, and the closer distance promoted facile hole transfer from perovskite to HTMs. In the end, PSCs based on strongly polarized spiro-BC-OMe achieved efficient hole extraction and thus an improved fill factor, promoting a power conversion efficiency (PCE) of 22.15%, and a module-based PCE of 18.61% with an active area of 16.38 cm2 . This study provides a new avenue for designing HTMs with strong dipole moments for efficient PSCs.

Revealing the Enhanced Thermoelectric Properties of Controllably Doped Donor-Acceptor Copolymer: The Impact of Regioregularity.

Albeit considerable attention to the fast-developing organic thermoelectric (OTE) materials due to their flexibility and non-toxic features, it is still challenging to design an OTE polymer with superior thermoelectric properties. In this work, two "isomorphic" donor-acceptor (D-A) conjugated polymers are studied as the semiconductor in OTE devices, revealing for the first time the internal mechanism of regioregularity on thermoelectric performances in D-A type polymers. A higher molecular structure regularity can lead to higher crystalline order and mobility, higher doping efficiency, order of energy state, and thermoelectric (TE) performance. As a result, the regioregular P2F exhibits a maximum power factor (PF) of up to 113.27 µW m-1  K-2 , more than three times that of the regiorandom PRF (35.35 µW m-1  K-2 ). However, the regular backbone also implies lower miscibility with a dopant, negatively affecting TE performance. Therefore, the trade-off between doping efficiency and miscibility plays a vital role in OTE materials, and this work sheds light on the molecular design strategy of OTE polymers with state-of-the-art performances.

Goals and approaches for each processing step for single-cell RNA sequencing data.

Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene expression at the cellular level. However, due to the extremely low levels of transcripts in a single cell and technical losses during reverse transcription, gene expression at a single-cell resolution is usually noisy and highly dimensional; thus, statistical analyses of single-cell data are a challenge. Although many scRNA-seq data analysis tools are currently available, a gold standard pipeline is not available for all datasets. Therefore, a general understanding of bioinformatics and associated computational issues would facilitate the selection of appropriate tools for a given set of data. In this review, we provide an overview of the goals and most popular computational analysis tools for the quality control, normalization, imputation, feature selection and dimension reduction of scRNA-seq data.

Critical downstream analysis steps for single-cell RNA sequencing data.

Single-cell RNA sequencing (scRNA-seq) has enabled us to study biological questions at the single-cell level. Currently, many analysis tools are available to better utilize these relatively noisy data. In this review, we summarize the most widely used methods for critical downstream analysis steps (i.e. clustering, trajectory inference, cell-type annotation and integrating datasets). The advantages and limitations are comprehensively discussed, and we provide suggestions for choosing proper methods in different situations. We hope this paper will be useful for scRNA-seq data analysts and bioinformatics tool developers.