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Understanding gene expression patterns across different human cell types is crucial for investigating mechanisms of cell type differentiation, disease occurrence and progression. The recent development of single-cell RNA-seq (scRNA-seq) technologies significantly boosted the characterization of cell type heterogeneities in different human tissues. However, the huge number of datasets in the public domain also posed challenges in data integration and reuse. We present Human Universal Single Cell Hub (HUSCH, http://husch.comp-genomics.org), an atlas-scale curated database that integrates single-cell transcriptomic profiles of nearly 3 million cells from 185 high-quality human scRNA-seq datasets from 45 different tissues. All the data in HUSCH were uniformly processed and annotated with a standard workflow. In the single dataset module, HUSCH provides interactive gene expression visualization, differentially expressed genes, functional analyses, transcription regulators and cell–cell interaction analyses for each cell type cluster. Besides, HUSCH integrated different datasets in the single tissue module and performs data integration, batch correction, and cell type harmonization. This allows a comprehensive visualization and analysis of gene expression within each tissue based on single-cell datasets from multiple sources and platforms. HUSCH is a flexible and comprehensive data portal that enables searching, visualizing, analyzing, and downloading single-cell gene expression for the human tissue atlas.

The goal of this study was to look into age, genetics,sex, oral mucosa diseases, and systemic diseases as potential risk factors for the geographic tongue (GT) in a Chinese population.This retrospective cross-sectional study used the demographic and medical data of 3400 patients between March 2021 and August 2021 from the Department of Oral Medicine at West China Hospital of Stomatology. Binary logistic regression was conducted to analyze the association of GT and age, fissured tongue (FT), burning mouth syndrome (BMS), oral lichen planus (OLP), gastrointestinal disorders, and hematologic disorders and to acquire the adjusted odds ratio (AOR).GT occurred in 3.6% of patients, with 15 out of 123 (12.2%) patients with GT having a family history. Binary logistic regression found age30 years (AOR: 4.4; [95% CI: 2.8-6.9]), FT (28.8 [17.1-48.4]), BMS (0.3 [0.1-0.6]), OLP (0.2 [0.0-0.5]), and gastrointestinal disorders (4.3 [2.7-6.7]) were significantly associated with GT, and GT was unrelated to recurrent aphthous ulcer (RAU) or systemic diseases such as cardiovascular diseases.In the Chinese population, GT was more prevalent in patients with30 years of age, FT, and gastrointestinal disorders, and it was less prevalent in BMS and OLP.

The etiology and pathogenesis of pemphigus vulgaris (PV) are closely related to both immune cells and epithelial cells, but the specific subtypes of immune cells involved in PV and their roles are not yet fully understood. Additionally, the specific functions and mechanisms of first-line treatment glucocorticoids on cell types of PV remain to be elucidated. We performing 5’ single-cell RNA sequencing, combined with V(D)J enrichment on buccal mucosal lesions and peripheral blood samples from treatment-naïve patients with PV, in conjunction with post-treatment peripheral blood samples obtained after oral prednisone treatment. Our findings suggest that IL-1α signaling pathway, myeloid antigen presenting cells, inflammatory CD8+ Trm, and dysfunctional CD4+ Treg are crucial in PV. Our results were also supported by immunohistochemical assays. Furthermore, our results show that prednisone has a significant impact on monocytes and MAIT, but a limited effect on CD4+ Treg. Finally, we provide CDR3 amino acid sequence data of BCR that may be used as therapeutic targets. In conclusion, this study provides a comprehensive understanding of PV, particularly in the mucosal-dominant type, and the effect of GCs on PV, which could effectively lead to the development of new therapeutic strategies.

Supplementary Figures and Legends for Supplementary Tables

Prior data have variably implicated the inactivation of the mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) complex with increased tumor sensitivity to immune checkpoint inhibitors (ICI). Herein, we examined the association between mSWI/SNF variants and clinical outcomes to ICIs. We correlated somatic loss-of-function (LOF) variants in a predefined set of mSWI/SNF genes (ARID1A, ARID1B, SMARCA4, SMARCB1, PBRM1, and ARID2) with clinical outcomes in patients with cancer treated with systemic ICIs. We identified 676 patients from Dana-Farber Cancer Institute (DFCI, Boston, MA) and 848 patients from a publicly available database from Memorial Sloan Kettering Cancer Center (MSKCC, New York, NY) who met the inclusion criteria. Multivariable analyses were conducted and adjusted for available baseline factors and tumor mutational burden. Median follow-up was 19.6 (17.6–22.0) months and 28.0 (25.0–29.0) months for the DFCI and MSKCC cohorts, respectively. Seven solid tumor subtypes were examined. In the DFCI cohort, LOF variants of mSWI/SNF did not predict improved overall survival (OS), time-to-treatment failure (TTF), or disease control rate. Only patients with renal cell carcinoma with mSWI/SNF LOF showed significantly improved OS and TTF with adjusted HRs (95% confidence interval) of 0.33 (0.16–0.7) and 0.49 (0.27–0.88), respectively, and this was mostly driven by PRBM1. In the MSKCC cohort, where only OS was captured, LOF mSWI/SNF did not correlate with improved outcomes across any tumor subtype. We did not find a consistent association between mSWI/SNF LOF variants and improved clinical outcomes to ICIs, suggesting that mSWI/SNF variants should not be considered as biomarkers of response to ICIs.

Supplementary Tables

Performance comparison between TIMER and CIBERSORT

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Recent clinical successes of cancer immunotherapy necessitate the investigation of the interaction between malignant cells and the host immune system. However, elucidation of complex tumor–immune interactions presents major computational and experimental challenges. Here, we present Tumor Immune Estimation Resource (TIMER; cistrome.shinyapps.io/timer) to comprehensively investigate molecular characterization of tumor–immune interactions. Levels of six tumor-infiltrating immune subsets are precalculated for 10,897 tumors from 32 cancer types. TIMER provides 6 major analytic modules that allow users to interactively explore the associations between immune infiltrates and a wide spectrum of factors, including gene expression, clinical outcomes, somatic mutations, and somatic copy number alterations. TIMER provides a user-friendly web interface for dynamic analysis and visualization of these associations, which will be of broad utilities to cancer researchers. Cancer Res; 77(21); e108–10. ©2017 AACR.

A high-fidelity ssDNA circularisation via the pairing of five 3′-terminal bases was developed to assist LR-LAMP for genotyping of SNPs.

The Tumor Immune Single Cell Hub 2 (TISCH2) is a resource of single-cell RNA-seq (scRNA-seq) data from human and mouse tumors, which enables comprehensive characterization of gene expression in the tumor microenvironment (TME) across multiple cancer types. As an increasing number of datasets are generated in the public domain, in this update, TISCH2 has included 190 tumor scRNA-seq datasets covering 6 million cells in 50 cancer types, with 110 newly collected datasets and almost tripling the number of cells compared with the previous release. Furthermore, TISCH2 includes several new functions that allow users to better utilize the large-scale scRNA-seq datasets. First, in the Dataset module, TISCH2 provides the cell–cell communication results in each dataset, facilitating the analyses of interacted cell types and the discovery of significant ligand–receptor pairs between cell types. TISCH2 also includes the transcription factor analyses for each dataset and visualization of the top enriched transcription factors of each cell type. Second, in the Gene module, TISCH2 adds functions for identifying correlated genes and providing survival information for the input genes. In summary, TISCH2 is a user-friendly, up-to-date and well-maintained data resource for gene expression analyses in the TME. TISCH2 is freely available at http://tisch.comp-genomics.org/.

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies in the head and neck with a poor prognosis. Oral cancer development is a multistep process involving carcinogenesis. Though significant advances in cancer immunotherapy over the years, there is lack of evidence for T-cell exhaustion during oral carcinogenesis. Clinical specimens from healthy donors and patients diagnosed with oral leukoplakia (OLK) or OSCC were collected for immunohistochemical staining with PD-L1, CD86, CD8, PD-1 and CTLA-4 antibodies. Meanwhile, chemically induced mouse models of oral carcinogenesis were constructed with 4-nitroquinolone-N-oxide induction. Exhaustion status of T cells was measured by flow cytometry for spleens and by multiplex immunohistochemistry for formalin-fixed paraffin-embedded lesions in multiple stages of oral carcinogenesis. The efficacy of PD-1 blockade with or without cisplatin treatment was evaluated on the mice in precancerous and OSCC stages. We observed higher expression of PD-1 in the human OLK and OSCC tissues compared with the normal, while low expression CTLA-4 in all oral mucosa tissues. Animal experiments showed that the exhausted CD4+ T cells existed much earlier than exhausted CD8+ T cells, and an increased ratio of stem-like exhausted T cells and partially exhausted T cells were detected in the experimental groups. Besides, the expression of immune checkpoint markers (PDCD1, CTLA4 and HAVCR2) was strongly positively correlated with cytokines (IFNG and IL-2). In summary, T-cell exhaustion plays a vital role in oral carcinogenesis, and PD-1 blockade can prevent the progression of oral carcinogenesis.

To assess the efficacy of photodynamic therapy (PDT) for oral squamous cell carcinoma (OSCC), literature on this topic from Embase, PubMed, and Web of Science were obtained and analyzed. The response and recurrence rates with 95% confidence intervals (CI) were calculated using the DerSimonia–Laird method. The pooled complete response (CR) rate from the included studies was 0.799 (95% CI: 0.708–0.867), while the overall response (OR) rate was 0.967 (95% CI: 0.902–0.989). The recurrence rate (RR) was 0.158 (95% CI: 0.090–0.264). A subgroup analysis of lesion site, photosensitizer, laser type, radiant exposure, and power density revealed no statistically significant differences. In general, PDT is effective for the treatment of early OSCC. Investigations on the influence of PDT on the survival of OSCC patients, optimization of the treatment regimen, and evaluation of response after treatment are still needed.

Proliferative verrucous leukoplakia (PVL) is characterized by a spectrum of clinicopathological features and a high risk of malignant transformation. In this study, we aimed to delineate the dynamic changes in molecular signature during PVL progression and identify the potential cell subtypes that play a key role in the premalignant evolution of PVL.We performed single-cell RNA sequencing on three biopsy samples from a large PVL lesion. These samples exhibited a histopathological continuum of PVL progression.By analyzing the transcriptome profiles of 27,611 cells from these samples, we identified ten major cell lineages and revealed that cellular remodeling occurred during the progression of PVL lesions, including epithelial, stromal, and immune cells. Epithelial cells are shifted to tumorigenic states and secretory patterns at the premalignant stage. Immune cells showed growing immunosuppressive phenotypes during PVL progression. Remarkably, two novel cell subtypes INSROur work is the first to depict the cellular landscape of PVL and speculate that disease progression may be driven by functional remodeling of multiple cell subtypes.

Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors, but also posed computational challenges on how to integrate and utilize the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly two million cells from 76 high-quality tumor datasets across 28 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, malignant cell classification, cell clustering, cell-type annotation, differential expression analysis, and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching, and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.

Prior data have variably implicated the inactivation of the mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) complex with increased tumor sensitivity to immune checkpoint inhibitors (ICI). Herein, we examined the association between mSWI/SNF variants and clinical outcomes to ICIs. We correlated somatic loss-of-function (LOF) variants in a predefined set of mSWI/SNF genes (ARID1A, ARID1B, SMARCA4, SMARCB1, PBRM1, and ARID2) with clinical outcomes in patients with cancer treated with systemic ICIs. We identified 676 patients from Dana-Farber Cancer Institute (DFCI, Boston, MA) and 848 patients from a publicly available database from Memorial Sloan Kettering Cancer Center (MSKCC, New York, NY) who met the inclusion criteria. Multivariable analyses were conducted and adjusted for available baseline factors and tumor mutational burden. Median follow-up was 19.6 (17.6–22.0) months and 28.0 (25.0–29.0) months for the DFCI and MSKCC cohorts, respectively. Seven solid tumor subtypes were examined. In the DFCI cohort, LOF variants of mSWI/SNF did not predict improved overall survival (OS), time-to-treatment failure (TTF), or disease control rate. Only patients with renal cell carcinoma with mSWI/SNF LOF showed significantly improved OS and TTF with adjusted HRs (95% confidence interval) of 0.33 (0.16–0.7) and 0.49 (0.27–0.88), respectively, and this was mostly driven by PRBM1. In the MSKCC cohort, where only OS was captured, LOF mSWI/SNF did not correlate with improved outcomes across any tumor subtype. We did not find a consistent association between mSWI/SNF LOF variants and improved clinical outcomes to ICIs, suggesting that mSWI/SNF variants should not be considered as biomarkers of response to ICIs.

The rapid accumulation of single-cell RNA-seq data has provided rich resources to characterize various human cell types. Cell type annotation is the critical step in analyzing single-cell RNA-seq data. However, accurate cell type annotation based on public references is challenging due to the inconsistent annotations, batch effects, and poor characterization of rare cell types. Here, we introduce SELINA (single cELl identity NAvigator), an integrative annotation transferring framework for automatic cell type annotation. SELINA optimizes the annotation for minority cell types by synthetic minority over-sampling, removes batch effects among reference datasets using a multiple-adversarial domain adaptation network (MADA), and fits the query data with reference data using an autoencoder. Finally, SELINA affords a comprehensive and uniform reference atlas with 1.7 million cells covering 230 major human cell types. We demonstrated the robustness and superiority of SELINA in most human tissues compared to existing methods. SELINA provided a one-stop solution for human single- cell RNA-seq data annotation with the potential to extend for other species.

Direct immunofluorescence and immune function and patients with oral lichen planusThe etiology of oral lichen planus (OLP) is unknown, our purpose was to evaluate the diagnostic value of direct immunofluorescence (DIF) and to investigate the immune functions in OLP.We enrolled 65 patients with suspected lesions of OLP and 47 controls. In all participants, clinical and serologic testing were conducted. The histopathologic and DIF tests were conducted in 65 patients. The severity of OLP was evaluated by reticular/hyperkeratotic, erosive/erythematous, ulcerative (REU) scoring system.By hematoxylin and eosin (HE) staining and DIF examination, 71.2% (42/59) were diagnosed as OLP, 28.8% (17/59) were diagnosed as non-OLP. DIF demonstrated 64.3% positive reactivity with 2 distinct distribution patterns and 8 staining patterns. Compared to the controls, serum IgA in OLP was higher (P 0.01), and serum CD3+ cells, IgM, IgE, C3 and C4 were lower (P 0.05). Pearson correlation analysis in OLP revealed correlations between REU score and IgM, IgA of DIF (r = 0.54, P = 0.026; and r = 0.56, P = 0.020, respectively), between serum IgG and IgG of DIF (r = 0.51, P = 0.038), between serum CD4+ and the ratio of CD4+/CD8+, IgM in DIF (r = -0.50, P = 0.048; and r = -0.54, P = 0.031, respectively), between serum CD8+ and IgM, IgA in DIF (r = 0.52, P = 0.038; and r = -0.50, P = 0.047, respectively).A combination of HE test and DIF is useful for the diagnosis of OLP. Compared to controls, immune changes happen to patients with OLP. There are significant associations between the OLP lesions and general cellular and humoral immune status, localized humoral immune response.

The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity in the spatial context. However, the current limitations of spatial technologies hamper the exploration of cellular localizations and interactions at single-cell level. Here, we present spatial transcriptomics deconvolution by topic modeling (STRIDE), a computational method to decompose cell types from spatial mixtures by leveraging topic profiles trained from single-cell transcriptomics. STRIDE accurately estimated the cell-type proportions and showed balanced specificity and sensitivity compared to existing methods. We demonstrate STRIDE’s utility by applying it to different spatial platforms and biological systems. Deconvolution by STRIDE not only mapped rare cell types to spatial locations but also improved the identification of spatial localized genes and domains. Moreover, topics discovered by STRIDE were associated with cell-type-specific functions, and could be further used to integrate successive sections and reconstruct the three-dimensional architecture of tissues. Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics and is publicly available at https://github.com/wanglabtongji/STRIDE.

Na Liu, Liang Zhong, Guangcheng Ni, Jiao Lin, Liang Xie, Taiwen Li, Hongxia Dan, Qianming Chen State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Chinese Academy of Medical Sciences Research Unit of Oral Carcinogenesis and Management, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, People’s Republic of ChinaCorrespondence: Hongxia Dan; Qianming ChenState Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Chinese Academy of Medical Sciences Research Unit of Oral Carcinogenesis and Management, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, People’s Republic of ChinaTel +86 28 85503480Fax +86 28 85501469Email hxdan@foxmail.com; qchen63@qq.comPurpose: Pancreatic adenocarcinoma (PAAD) is a devastating disease with high mortality and morbidity. Matrix metalloproteinase 28 (MMP28) has been associated with carcinogenesis of many human cancers. However, little is known about the potential prognostic value and underlying regulatory mechanisms of MMP28 in PAAD.Methods: The relationship between MMP28 expression level and various clinicopathological parameters was analyzed in TCGA-PAAD cohorts. MMP28-correlated genes in the TCGA-PAAD cohort were identified and enrichment analysis according to the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes was conducted using LinkedOmics. Protein–protein interaction and transcription factors-miRNA co-regulatory networks were constructed with the use of NetworkAnalyst. Then, the distribution of immune cells related to MMP28 expression in blood was analyzed using the Human Protein Atlas, and the tumor microenvironment of PAAD was analyzed by the TIMER 2.0 database. To investigate the biological function of MMP28 in PAAD, siRNA was constructed to knock down the MMP28 gene in vitro.Results: High MMP28 expression is associated with poor overall survival and disease-free survival in PAAD patients. The expression of MMP28 in PAAD is most significantly correlated with KRT19, IL1RN, and ANXA2 genes. Network analysis revealed that MIR-181 family, TAFs, and CDC6 are potential regulators of MMP28. Furthermore, naive CD4+ T cell, naive CD8+ T cell, and mucosal-associated invariant T cell enrichment in blood were correlated with MMP28 expression. Furthermore, high MMP28 expression was correlated with a decrease in B cell, naive CD4+ T cell, naive CD8+ T cell, and endothelial cell presence in the tumor microenvironment in PAAD. Finally, genetic knockdown of MMP28 could restrain the proliferation, migration, and invasion of PAAD cells.Conclusion: Our findings indicate that high MMP28 expression in PAAD is associated with cancer progression, invasion, and metastasis. Hence, MMP28 might serve as an independent prognostic biomarker and a prospective therapeutic target for PAAD.Keywords: matrix metalloproteinase 28, pancreatic adenocarcinoma, metastasis, prognosis

Background Casticin expresses multiple anti-cancer activities, whereas the effect of casticin on oral squamous cell carcinoma (OSCC) is still unclear. β-catenin signaling plays a crucial role in the epithelial-mesenchymal transition which is closely related to tumorigenesis. Herein, we aimed to study the functions of casticin on invasion and migration of OSCC, and clarify whether the effect of casticin on OSCC has a relationship with β-catenin signaling. Methods Human OSCC cell lines UM1 and HSC-3 were treated with different concentrations of casticin. The cell viability was evaluated by MTT and soft agar colony formation. Transwell assay and wound-healing assay were performed to measure the ability of cell invasion and migration. The protein expression was assessed by Western blotting. Results Casticin displayed inhibitory activities of cell viability, invasion, and migration on OSCC cell lines. Meanwhile, casticin could reverse EMT process and inhibit the expression of β-catenin in OSCC. Knock-down or overexpression of β-catenin could alter the effect of casticin on OSCC. Conclusions Casticin impaired invasion and migration of OSCC by inhibition of β-catenin and reversal of EMT and could be a potential anti-cancer bioactive agent.

Tumor-infiltrating B cells are an important component in the microenvironment with unclear anti-tumor impacts. We enhanced our previous computational algorithm TRUST to extract the B cell immunoglobulin (Ig) hypervariable regions from bulk tumor RNA-seq data. TRUST assembled over 30 million complementarity-determining region 3 (CDR3s) of the B cell heavy chain (IgH) from The Cancer Genome Atlas (TCGA). Widespread B cell clonal expansions and Ig subclass switch events were observed in diverse human cancers. Prevalent somatic copy number alterations in MICA and MICB genes related to antibody-dependent cell mediated cytotoxicity (ADCC) were identified in tumors with elevated B cell activity. IgG3-1 subclass switch interacts with the B cell receptor affinity maturation and defects in the ADCC pathway. Comprehensive pan-cancer analyses of tumor-infiltrating B cell receptor repertoires identified novel tumor immune evasion mechanisms through genetic alterations. The IgH sequences identified here are potentially useful resources for future development of immunotherapies., Editorial summary: This comprehensive pan-cancer analysis of RNA sequencing data from bulk tumors defines the landscape of tumor-infiltrating B cell receptor repertoires and highlights new mechanisms of tumor immune evasion through genetic alterations.

Tumor-infiltrating immune cells play critical roles in immune-mediated tumor rejection and/or progression, and are key targets of immunotherapies. Estimation of different immune subsets becomes increasingly important with the decreased cost of high-throughput molecular profiling and the rapidly growing amount of cancer genomics data. Here, we present Tumor IMmune Estimation Resource (TIMER), an in silico deconvolution method for inference of tumor-infiltrating immune components. TIMER takes bulk tissue gene expression profiles measured with RNA-seq or microarray to evaluate the abundance of six immune cell types in the tumor microenvironment: B cell, CD4+ T cell, CD8+ T cell, neutrophil, macrophage, and dendritic cell. We further introduce its associated webserver for convenient, user-friendly analysis of tumor immune infiltrates across multiple cancer types.

The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity in the spatial context. However, the current limitations of spatial technologies hamper the exploration of cellular localizations and interactions at single-cell level. Here, we present spatial transcriptomics deconvolution by topic modeling (STRIDE), a computational method to decompose cell types from spatial mixtures by leveraging topic profiles trained from single-cell transcriptomics. STRIDE accurately estimated the cell-type proportions and showed balanced specificity and sensitivity compared to existing methods. We demonstrated STRIDE’s utility by applying it to different spatial platforms and biological systems. Deconvolution by STRIDE not only mapped rare cell types to spatial locations but also improved the identification of spatially localized genes and domains. Moreover, topics discovered by STRIDE were associated with cell-type-specific functions and could be further used to integrate successive sections and reconstruct the three-dimensional architecture of tissues. Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics and is publicly available at https://github.com/wanglabtongji/STRIDE.

Nano-sized Y2O3:Yb3+, Er3+ phosphors were synthesized by sol-gel method and characterized by X-ray diffraction, scanning electron microscope, near-infrared and upconversion fluorescence spectroscopy. The phosphors calcined at 1100 °C for 2 h were confirmed to be cubic Y2O3 phase with well-crystallized particles. With the introduction of Ce3+ ions at proper doping concentration, the 1.534 μm emission of Er3+ was found to be greatly enhanced, while the green and red upconversion emission intensity obviously decreased. The enhancement of 1.534 μm emission could be attributed to the phonon-assisted energy transfer process between Ce3+ and Er3+ ions.

Background RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Results Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. Conclusions VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion. Electronic supplementary material The online version of this article (10.1186/s12859-018-2139-9) contains supplementary material, which is available to authorized users.

Correction for ‘High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3′-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms’ by Taiwen Li et al., Analyst, 2022, https://doi.org/10.1039/d2an01042a.

In this paper, an all-solid-state Nd:YVO4 laser with peak synchronize output of 1064/1342 nm dual-wavelength Q-switched pulse is designed. Double-cavity structure with single Nd:YVO4 crystal and double RbTiOPO4 (RTP) electro-optic (EO) Q-switch is built. At repetition frequency of 10 kHz, taking the trigger time of EO Q-switch at 1342 nm as reference, at the delay time of EO Q-switch at 1064 nm as 1.3 μs, the pulse peak synchronize dual-wavelength laser is obtained, and the pulse power is 1.63 W and 1.63 W with the width is 55.64 ns and 105.2 ns respectively. The beam quality is M x 2 =1.61 , M x 2 =1.64 and M x 2 =1.43 , M y 2 = 1.54 , respectively.