CircNetVis: an interactive web application for visualizing interaction networks of circular RNAs.

Analyzing the interactions of circular RNAs (circRNAs) is a crucial step in understanding their functional impacts. While there are numerous visualization tools available for investigating circRNA interaction networks, these tools are typically limited to known circRNAs from specific databases. Moreover, these existing tools usually require complex installation procedures which can be time-consuming and challenging for users. There is a lack of a user-friendly web application that facilitates interactive exploration and visualization of circRNA interaction networks. CircNetVis is an interactive online web application to enhance the analysis of human/mouse circRNA interactions. The tool allows three different input formats of circRNAs including circRNA IDs from CircBase, circRNA coordinates (chromosome, start position, end position), and circRNA sequences in the FASTA format. It integrates multiple interaction networks for visualization and investigation of the interplay between circRNA, microRNAs, mRNAs and RNA binding proteins. CircNetVis also enables users to interactively explore the interactions of unknown circRNAs which are not reported from previous databases. The tool can generate interactive plots and allows users to save results as output files for offline usage. CircNetVis is implemented as a web application using R-shiny and freely available for academic use at https://www.meb.ki.se/shiny/truvu/CircNetVis/ .

Endoscopic papillectomy for ampullary lesions of minor papilla.

BACKGROUND AND AIMS: Ampullary lesions (ALs) of the minor duodenal papilla are extremely rare. Endoscopic papillectomy (EP) is a routinely used treatment for AL of the major duodenal papilla, but the role of EP for minor AL has not been accurately studied. METHODS: We identified 20 patients with ALs of minor duodenal papilla in the multicentric database from the Endoscopic Papillectomy vs Surgical Ampullectomy vs Pancreatitcoduodenectomy for Ampullary Neoplasm study, which included 1422 EPs. We used propensity score matching (nearest-neighbor method) to match these cases with ALs of the major duodenal papilla based on age, sex, histologic subtype, and size of the lesion in a 1:2 ratio. Cohorts were compared by means of chi-square or Fisher exact test as well as Mann-Whitney U test. RESULTS: Propensity score-based matching identified a cohort of 60 (minor papilla 20, major papilla 40) patients with similar baseline characteristics. The most common histologic subtype of lesions of minor papilla was an ampullary adenoma in 12 patients (3 low-grade dysplasia and 9 high-grade dysplasia). Five patients revealed nonneoplastic lesions. Invasive cancer (T1a), adenomyoma, and neuroendocrine neoplasia were each found in 1 case. The rate of complete resection, en-bloc resection, and recurrences were similar between the groups. There were no severe adverse events after EP of lesions of minor papilla. One patient had delayed bleeding that could be treated by endoscopic hemostasis, and 2 patients showed a recurrence in surveillance endoscopy after a median follow-up of 21 months (interquartile range, 12-50 months). CONCLUSIONS: EP is safe and effective in ALs of the minor duodenal papilla. Such lesions could be managed according to guidelines for EP of major duodenal papilla.

Artificial Intelligence in Colorectal Cancer: From Patient Screening over Tailoring Treatment Decisions to Identification of Novel Biomarkers.

BACKGROUND: Artificial intelligence (AI) is increasingly entering and transforming not only medical research but also clinical practice. In the last 10 years, new AI methods have enabled computers to perform visual tasks, reaching high performance and thereby potentially supporting and even outperforming human experts. This is in particular relevant for colorectal cancer (CRC), which is the 3rd most common cancer type in general, as along the CRC patient journey many complex visual tasks need to be performed: from endoscopy over imaging to histopathology; the screening, diagnosis, and treatment of CRC involve visual image analysis tasks. SUMMARY: In all these clinical areas, AI models have shown promising results by supporting physicians, improving accuracy, and providing new biological insights and biomarkers. By predicting prognostic and predictive biomarkers from routine images/slides, AI models could lead to an improved patient stratification for precision oncology approaches in the near future. Moreover, it is conceivable that AI models, in particular together with innovative techniques such as single-cell or spatial profiling, could help identify novel clinically as well as biologically meaningful biomarkers that could pave the way to new therapeutic approaches. KEY MESSAGES: Here, we give a comprehensive overview of AI in colorectal cancer, describing and discussing these developments as well as the next steps which need to be taken to incorporate AI methods more broadly into the clinical care of CRC.

Redox-Responsive Gold Nanoparticles Coated with Hyaluronic Acid and Folic Acid for Application in Targeting Anticancer Therapy.

Methotrexate (MTX) has poor water solubility and low bioavailability, and cancer cells can become resistant to it, which limits its safe delivery to tumor sites and reduces its clinical efficacy. Herein, we developed novel redox-responsive hybrid nanoparticles (NPs) from hyaluronic acid (HA) and 3-mercaptopropionic acid (MPA)-coated gold NPs (gold@MPA NPs), which were further conjugated with folic acid (FA). The design of FA-HA-ss-gold NPs aimed at enhancing cellular uptake specifically in cancer cells using an active FA/HA dual targeting strategy for enhanced tumor eradication. MTX was successfully encapsulated into FA-HA-ss-gold NPs, with drug encapsulation efficiency (EE) as high as >98.7%. The physicochemical properties of the NPs were investigated in terms of size, surface charges, wavelength reflectance, and chemical bonds. MTX was released in a sustained manner in glutathione (GSH). The cellular uptake experiments showed effective uptake of FA-HA-ss-gold over HA-ss-gold NPs in the deep tumor. Moreover, the release studies provided strong evidence that FA-HA-ss-gold NPs serve as GSH-responsive carriers. In vitro, anti-tumor activity tests showed that FA-HA-ss-gold/MTX NPs exhibited significantly higher cytotoxic activity against both human cervical cancer (HeLa) cells and breast cancer (BT-20) cells compared to gold only and HA-ss-gold/MTX NPs while being safe for human embryonic kidney (HEK-293) cells. Therefore, this present study suggests that FA-HA-ss-gold NPs are promising active targeting hybrid nanocarriers that are stable, controllable, biocompatible, biodegradable, and with enhanced cancer cell targetability for the safe delivery of hydrophobic anticancer drugs.

Serine-threonine Kinase Receptor-Associated Protein is a Critical Mediator of APC Mutation-Induced Intestinal Tumorigenesis Through a Feed-Forward Mechanism.

BACKGROUND & AIMS: Inactivation of the Apc gene is a critical early event in the development of sporadic colorectal cancer (CRC). Expression of serine-threonine kinase receptor-associated protein (STRAP) is elevated in CRCs and is associated with poor outcomes. We investigated the role of STRAP in Apc mutation-induced intestinal tumor initiation and progression. METHODS: We generated Strap intestinal epithelial knockout mice (StrapΔIEC) by crossing mice containing floxed alleles of Strap (Strapfl/fl) with Villin-Cre mice. Then we generated ApcMin/+;Strapfl/fl;Vill-Cre (ApcMin/+;StrapΔIEC) mice for RNA-sequencing analyses to determine the mechanism of function of STRAP. We used human colon cancer cell lines (DLD1, SW480, and HT29) and human and mouse colon tumor-derived organoids for STRAP knockdown and knockout and overexpression experiments. RESULTS: Strap deficiency extended the average survival of ApcMin/+ mice by 80 days and decreased the formation of intestinal adenomas. Expression profiling revealed that the intestinal stem cell signature, the Wnt/ß-catenin signaling, and the MEK/ERK pathway are down-regulated in Strap-deficient adenomas and intestinal organoids. Correlation studies suggest that these STRAP-associated oncogenic signatures are conserved across murine and human colon cancer. STRAP associates with MEK1/2, promotes binding between MEK1/2 and ERK1/2, and subsequently induces the phosphorylation of ERK1/2. STRAP activated Wnt/ß-catenin signaling through MEK/ERK-induced phosphorylation of LRP6. STRAP was identified as a target of mutated Apc and Wnt/ß-catenin signaling as chromatin immunoprecipitation and luciferase assays revealed putative binding sites of the ß-catenin/TCF4 complex on the Strap promoter. CONCLUSIONS: STRAP is a target of, and is required in, Apc mutation/deletion-induced intestinal tumorigenesis through a novel feed-forward STRAP/MEK-ERK/Wnt-ß-catenin/STRAP regulatory axis.

Isoform-level quantification for single-cell RNA sequencing.

MOTIVATION: RNA expression at isoform level is biologically more informative than at gene level and can potentially reveal cellular subsets and corresponding biomarkers that are not visible at gene level. However, due to the strong 3' bias sequencing protocol, mRNA quantification for high-throughput single-cell RNA sequencing such as Chromium Single Cell 3' 10× Genomics is currently performed at the gene level. RESULTS: We have developed an isoform-level quantification method for high-throughput single-cell RNA sequencing by exploiting the concepts of transcription clusters and isoform paralogs. The method, called Scasa, compares well in simulations against competing approaches including Alevin, Cellranger, Kallisto, Salmon, Terminus and STARsolo at both isoform- and gene-level expression. The reanalysis of a CITE-Seq dataset with isoform-based Scasa reveals a subgroup of CD14 monocytes missed by gene-based methods. AVAILABILITY AND IMPLEMENTATION: Implementation of Scasa including source code, documentation, tutorials and test data supporting this study is available at Github: https://github.com/eudoraleer/scasa and Zenodo: https://doi.org/10.5281/zenodo.5712503. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparison between traumatic and atraumatic over-the-scope clips in patients with duodenal ulcer bleeding: a retrospective analysis with propensity score-based matching.

BACKGROUND AND AIMS: Over-the-scope clips (OTSCs) substantially improved the endoscopic armamentarium for the treatment of severe GI bleeding and can potentially overcome limitations of standard clips. Data indicate a superiority of OTSCs in hemostasis as first- and second-line therapy. However, the impact of the OTSC designs, in particular the traumatic (-t) or atraumatic (-a) type, in duodenal ulcer bleeding has not been analyzed so far. METHODS: This was a retrospective analysis of a prospective collected database from 2009 to 2020 of 6 German endoscopic centers. All patients who underwent emergency endoscopy and were treated using an OTSC for duodenal ulcer bleeding were included. OTSC-t and OTSC-a patients were compared by the Fisher exact test, χ2 test, or Mann-Whitney U test as appropriate. A propensity score-based 1:1 matching was performed to obtain equal distribution of baseline characteristics in both groups. RESULTS: The entire cohort comprised 173 patients (93 OTSC-a, 80 OTSC-t). Age, gender, anticoagulant therapy, Rockall score, and treatment regimen had similar distributions in the 2 groups. However, the OTSC-t group showed significantly more active bleeding ulcers (Forrest Ia/b). Matching identified 132 patients (66 in both groups) with comparable baseline characteristics. Initial bleeding hemostasis (OTSC-a, 90.9%; OTSC-t, 87.9%; P = .82) and 72-hour mortality (OTSC-a, 4.5%; OTSC-t, 6.0%; P > .99) were not significantly different, but the OTSC-t group revealed a clearly higher rate of recurrent bleeding (34.9% vs 7.6%, P < .001) and necessity of red blood cell transfusions (5.1 ± 3.4 vs 2.5 ± 2.4 concentrates, P < .001). CONCLUSIONS: For OTSC use, the OTSC-a should be the preferred option for duodenal ulcer bleeding.

Endoscopic papillectomy for ampullary lesions in patients with familial adenomatous polyposis compared with sporadic lesions: a propensity score-matched cohort.

BACKGROUND: Familial adenomatous polyposis (FAP) is a rare inherited syndrome that predisposes the patient to cancer. Treatment of FAP-related ampullary lesions is challenging and the role of endoscopic papillectomy has not been elucidated. We retrospectively analyzed the outcomes of endoscopic papillectomy in matched cohorts of FAP-related and sporadic ampullary lesions (SALs). METHODS: This retrospective multicenter study included 1422 endoscopic papillectomy procedures. Propensity score matching including age, sex, comorbidity, histologic subtype, and size was performed. Main outcomes were complete resection (R0), technical success, complications, and recurrence. RESULTS: Propensity score matching identified 202 patients (101 FAP, 101 SAL) with comparable baseline characteristics. FAP patients were mainly asymptomatic (79.2 % [95 %CI 71.2-87.3] vs. 46.5 % [95 %CI 36.6-56.4]); P < 0.001). The initial R0 rate was significantly lower in FAP patients (63.4 % [95 %CI 53.8-72.9] vs. 83.2 % [95 %CI 75.8-90.6]; P = 0.001). After repeated interventions (mean 1.30 per patient), R0 was comparable (FAP 93.1 % [95 %CI 88.0-98.1] vs. SAL 97.0 % [95 %CI 93.7-100]; P = 0.19). Adverse events occurred in 28.7 %. Pancreatitis and bleeding were the most common adverse events in both groups. Severe adverse events were rare (3.5 %). Overall, 21 FAP patients (20.8 % [95 %CI 12.7-28.8]) and 16 SAL patients (15.8 % [95 %CI 8.6-23.1]; P = 0.36) had recurrence. Recurrences occurred later in FAP patients (25 [95 %CI 18.3-31.7] vs. 2 [95 %CI CI 0.06-3.9] months). CONCLUSIONS: Endoscopic papillectomy was safe and effective in FAP-related ampullary lesions. Criteria for endoscopic resection of ampullary lesions can be extended to FAP patients. FAP patients have a lifetime risk of relapse even after complete resection, and require long-time surveillance.

Construction of a rapid electrochemical biosensor consisting of a nanozyme/aptamer conjugate for waterborne microcystin detection.

Microcystin-LR (MC-LR) is a hepatotoxin generated by the excessive proliferation of cyanobacteria, which is a threat to humans and wildlife. Therefore, rapid detection of MC-LR is an important challenge. This study describes a rapid electrochemical biosensor comprising nanozymes and aptamers. Alternating current electrothermal flow (ACEF) significantly reduced the MC-LR detection period to 10 min. We also used MnO2/MC-LR aptamer conjugates to improve the sensitivity to MC-LR detection. Here, MnO2 amplified the electrochemical signal and the aptamer showed high selectivity for MC-LR. Under the optimal conditions, the limit of detection (LOD) and selectivity in freshwater were detected using cyclic voltammetry and differential pulse voltammetry. As a result, an LOD of 3.36 pg mL-1 was observed in the linear concentration range of 10 pg mL-1 to 1 µg mL-1. This study quickly and sensitively detected MC-LR in a situation where it causes serious damage worldwide. In addition, the ACEF technology introduction is the first example of MC-LR detection, suggesting a wide range of possibilities for MC-LR biosensors.

Life expectancy and human capital: New empirical evidence.

This paper re-examines a well-established hypothesis postulating that life expectancy augments incentives for human capital accumulation, leading to global income differences. A major distinguishing feature of the current study is to estimate heterogeneous panel data models under a common factor framework, which explicitly accounts for parameter heterogeneity, unobserved common factors (UCFs), and variables' non-stationarity. In sharp contrast to most previous studies, I find that the impact of health improvements on human capital accumulation turns out to be imprecisely estimated at conventionally accepted levels of statistical significance. I demonstrate that conventional estimates of the educational returns to rising longevity are derived from estimating misspecified models at least partially due to parameter heterogeneity and the presence of UCFs.

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue.

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

Identification of Homogeneous Subgroups from Resting-State fMRI Data.

The identification of homogeneous subgroups of patients with psychiatric disorders can play an important role in achieving personalized medicine and is essential to provide insights for understanding neuropsychological mechanisms of various mental disorders. The functional connectivity profiles obtained from functional magnetic resonance imaging (fMRI) data have been shown to be unique to each individual, similar to fingerprints; however, their use in characterizing psychiatric disorders in a clinically useful way is still being studied. In this work, we propose a framework that makes use of functional activity maps for subgroup identification using the Gershgorin disc theorem. The proposed pipeline is designed to analyze a large-scale multi-subject fMRI dataset with a fully data-driven method, a new constrained independent component analysis algorithm based on entropy bound minimization (c-EBM), followed by an eigenspectrum analysis approach. A set of resting-state network (RSN) templates is generated from an independent dataset and used as constraints for c-EBM. The constraints present a foundation for subgroup identification by establishing a connection across the subjects and aligning subject-wise separate ICA analyses. The proposed pipeline was applied to a dataset comprising 464 psychiatric patients and discovered meaningful subgroups. Subjects within the identified subgroups share similar activation patterns in certain brain areas. The identified subgroups show significant group differences in multiple meaningful brain areas including dorsolateral prefrontal cortex and anterior cingulate cortex. Three sets of cognitive test scores were used to verify the identified subgroups, and most of them showed significant differences across subgroups, which provides further confirmation of the identified subgroups. In summary, this work represents an important step forward in using neuroimaging data to characterize mental disorders.

Effectiveness of Continuous Endotracheal Cuff Pressure Control for the Prevention of Ventilator-Associated Respiratory Infections: An Open-Label Randomized, Controlled Trial.

BACKGROUND: An endotracheal tube cuff pressure between 20 and 30 cmH2O is recommended to prevent ventilator-associated respiratory infection (VARI). We aimed to evaluate whether continuous cuff pressure control (CPC) was associated with reduced VARI incidence compared with intermittent CPC. METHODS: We conducted a multicenter open-label randomized controlled trial in intensive care unit (ICU) patients within 24 hours of intubation in Vietnam. Patients were randomly assigned 1:1 to receive either continuous CPC using an automated electronic device or intermittent CPC using a manually hand-held manometer. The primary endpoint was the occurrence of VARI, evaluated by an independent reviewer blinded to the CPC allocation. RESULTS: We randomized 600 patients; 597 received the intervention or control and were included in the intention to treat analysis. Compared with intermittent CPC, continuous CPC did not reduce the proportion of patients with at least one episode of VARI (74/296 [25%] vs 69/301 [23%]; odds ratio [OR] 1.13; 95% confidence interval [CI] .77-1.67]. There were no significant differences between continuous and intermittent CPC concerning the proportion of microbiologically confirmed VARI (OR 1.40; 95% CI .94-2.10), the proportion of intubated days without antimicrobials (relative proportion [RP] 0.99; 95% CI .87-1.12), rate of ICU discharge (cause-specific hazard ratio [HR] 0.95; 95% CI .78-1.16), cost of ICU stay (difference in transformed mean [DTM] 0.02; 95% CI -.05 to .08], cost of ICU antimicrobials (DTM 0.02; 95% CI -.25 to .28), cost of hospital stay (DTM 0.02; 95% CI -.04 to .08), and ICU mortality risk (OR 0.96; 95% CI .67-1.38). CONCLUSIONS: Maintaining CPC through an automated electronic device did not reduce VARI incidence. CLINICAL TRIAL REGISTRATION: NCT02966392.

Evaluation of methods to detect circular RNAs from single-end RNA-sequencing data.

BACKGROUND: Circular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data. RESULTS: In this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method's precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data. CONCLUSIONS: The results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers' strategies in circRNA analysis.

Study on the co-infection of children with severe community-acquired pneumonia.

BACKGROUD: Pneumonia is one of the leading causes of death in children under 5 years old. Viruses have historically been the most common cause of community-acquired pneumonia in children. Co-infections in severe pneumonia are more concern by clinicians. METHOD: It was a perspective and descriptive study. Real-time polymerase chain reaction (RT-PCR) is a modern test that was used to detect many new pathogens, including microbiological co-infections. RT-PCR technique was used in this study to investigate the causes of severe pneumonia. RESULTS: Through the analysis of nasopharyngeal aspiration samples from 95 children with severe community-acquired pneumonia, the positive RT-PCR rate was 90.5%. Viral-bacterial co-infection accounted for the highest proportion (43.1%), followed by bacterial co-infection (33.7%), viral infection (7.4%), bacterial infection (6.3%) and the remaining 9.5% was unknown. In the co-infections groups, the five main bacteria species detected by PCR were Streptococcus pneumoniae, Haemophilus influenzae, MRSA, Moraxella catarrhalis and Mycoplasma pneumoniae. CONCLUSION: Antibiotic treatment should focus on detected microbes in cases of severe pneumonia for having a good result.

Circall: fast and accurate methodology for discovery of circular RNAs from paired-end RNA-sequencing data.

BACKGROUND: Circular RNA (circRNA) is an emerging class of RNA molecules attracting researchers due to its potential for serving as markers for diagnosis, prognosis, or therapeutic targets of cancer, cardiovascular, and autoimmune diseases. Current methods for detection of circRNA from RNA sequencing (RNA-seq) focus mostly on improving mapping quality of reads supporting the back-splicing junction (BSJ) of a circRNA to eliminate false positives (FPs). We show that mapping information alone often cannot predict if a BSJ-supporting read is derived from a true circRNA or not, thus increasing the rate of FP circRNAs. RESULTS: We have developed Circall, a novel circRNA detection method from RNA-seq. Circall controls the FPs using a robust multidimensional local false discovery rate method based on the length and expression of circRNAs. It is computationally highly efficient by using a quasi-mapping algorithm for fast and accurate RNA read alignments. We applied Circall on two simulated datasets and three experimental datasets of human cell-lines. The results show that Circall achieves high sensitivity and precision in the simulated data. In the experimental datasets it performs well against current leading methods. Circall is also substantially faster than the other methods, particularly for large datasets. CONCLUSIONS: With those better performances in the detection of circRNAs and in computational time, Circall facilitates the analyses of circRNAs in large numbers of samples. Circall is implemented in C++ and R, and available for use at https://www.meb.ki.se/sites/biostatwiki/circall and https://github.com/datngu/Circall.

Alternating EM algorithm for a bilinear model in isoform quantification from RNA-seq data.

MOTIVATION: Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform read distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide bias correction step(s), which is based on biological considerations-such as GC content-and applied in single samples separately. The main problem is that not all biases are known. RESULTS: We have developed a novel method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xß, where the design matrix X is known and is computed based on the simplifying assumptions. In contrast XAEM considers Xß as a bilinear model with both X and ß unknown. Joint estimation of X and ß is made possible by a simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. We use an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and ß. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes. In a differential-expression analysis of a real single-cell RNA-seq dataset, XAEM achieves substantially better rediscovery rates in independent validation sets. AVAILABILITY AND IMPLEMENTATION: The method and pipeline are implemented as a tool and freely available for use at http://fafner.meb.ki.se/biostatwiki/xaem/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The transcriptome-wide landscape of molecular subtype-specific mRNA expression profiles in acute myeloid leukemia.

Molecular classification of acute myeloid leukemia (AML) aids prognostic stratification and clinical management. Our aim in this study is to identify transcriptome-wide mRNAs that are specific to each of the molecular subtypes of AML. We analyzed RNA-sequencing data of 955 AML samples from three cohorts, including the BeatAML project, the Cancer Genome Atlas, and a cohort of Swedish patients to provide a comprehensive transcriptome-wide view of subtype-specific mRNA expression. We identified 729 subtype-specific mRNAs, discovered in the BeatAML project and validated in the other two cohorts. Using unique proteomics data, we also validated the presence of subtype-specific mRNAs at the protein level, yielding a rich collection of potential protein-based biomarkers for the AML community. To enable the exploration of subtype-specific mRNA expression by the broader scientific community, we provide an interactive resource to the public.

Field- and clinically derived estimates of Wolbachia-mediated blocking of dengue virus transmission potential in Aedes aegypti mosquitoes.

The wMel strain of Wolbachia can reduce the permissiveness of Aedes aegypti mosquitoes to disseminated arboviral infections. Here, we report that wMel-infected Ae. aegypti (Ho Chi Minh City background), when directly blood-fed on 141 viremic dengue patients, have lower dengue virus (DENV) transmission potential and have a longer extrinsic incubation period than their wild-type counterparts. The wMel-infected mosquitoes that are field-reared have even greater relative resistance to DENV infection when fed on patient-derived viremic blood meals. This is explained by an increased susceptibility of field-reared wild-type mosquitoes to infection than laboratory-reared counterparts. Collectively, these field- and clinically relevant findings support the continued careful field-testing of wMel introgression for the biocontrol of Ae. aegypti-born arboviruses.

Cell-level somatic mutation detection from single-cell RNA sequencing.

MOTIVATION: Both single-cell RNA sequencing (scRNA-seq) and DNA sequencing (scDNA-seq) have been applied for cell-level genomic profiling. For mutation profiling, the latter seems more natural. However, the task is highly challenging due to the limited input materials from only two copies of DNA molecules, while whole-genome amplification generates biases and other technical noises. ScRNA-seq starts with a higher input amount, so generally has better data quality. There exists various methods for mutation detection from DNA sequencing, it is not clear whether these methods work for scRNA-seq data. RESULTS: Mutation detection methods developed for either bulk-cell sequencing data or scDNA-seq data do not work well for the scRNA-seq data, as they produce substantial numbers of false positives. We develop a novel and robust statistical method-called SCmut-to identify specific cells that harbor mutations discovered in bulk-cell data. Statistically SCmut controls the false positives using the 2D local false discovery rate method. We apply SCmut to several scRNA-seq datasets. In scRNA-seq breast cancer datasets SCmut identifies a number of highly confident cell-level mutations that are recurrent in many cells and consistent in different samples. In a scRNA-seq glioblastoma dataset, we discover a recurrent cell-level mutation in the PDGFRA gene that is highly correlated with a well-known in-frame deletion in the gene. To conclude, this study contributes a novel method to discover cell-level mutation information from scRNA-seq that can facilitate investigation of cell-to-cell heterogeneity. AVAILABILITY AND IMPLEMENTATION: The source codes and bioinformatics pipeline of SCmut are available at https://github.com/nghiavtr/SCmut. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.