Mental health of pregnant women during the SARS-CoV-2 pandemic in France: Evolution of self-perceived psychological state during the first lockdown, and anxiety frequency two months after the lockdown ended.

Previous pandemics and related lockdowns have had a deleterious impact on pregnant women's mental health. We studied the impact of the SARS-CoV-2/Covid-19 pandemic and France's first lockdown on pregnant women's mental health. A cross-sectional study was conducted in July 2020 using a web-questionnaire completed by 500 adult women who were pregnant during the first lockdown in France (March-May 2020). Questions focused on their self-perceived psychological state and affects they felt before and during the lockdown and anxiety symptomatology (HAD) two months after it ended. A robust variance Poisson regression model was used to estimate adjusted prevalence ratios (aPR) for anxiety and self-perceived psychological state evolution. One in five respondents (21.1%) reported psychological deterioration during lockdown. Associated determinants were: i) little or no social support (self-perceived) (aRP = 1.77, 95%CI[1.18-2.66]), ii) increased workload (1.65, [1.02-2.66]), and iii) poor/moderate knowledge about SARS-CoV-2 transmission (1.60, [1.09-2.35]). Seven percent of women reporting psychological deterioration had access to professional psychological support during lockdown, while 19% did not despite wanting it. Women reported heightened powerlessness (60.3%), frustration (64%) and fear (59.2%) during lockdown. One in seven respondents (14.2%, 95%CI[10.9-18.2]) had anxiety symptoms. Determinants associated: i) at least one pregnancy-related pathology (aPR = 1.82, 95%CI[1.15-2.88]), ii) overweightness or obesity (1.61, [1.07-2.43]), iii) one child under the age of six years in the household during the lockdown (3.26, [1.24-8.53]), iv) little or no social support (self-perceived) during the lockdown (1.66, [1.07-2.58]), v) friend or relatives diagnosed with Covid-19 or with symptoms of the disease (1.66; [1.06-2.60]), vi) no access to medication for psychological distress (2.86, [1.74-4.71]), and vii) unsuccessfully seeking exchanges with healthcare professionals about their pregnancy during the pandemic (1.66, [1.08-2.55]). Our results can guide prevention and support policies for pregnant women during pandemics, current or future, with or without lockdowns. Preventing perinatal mental health problems is essential to ensure a supportive environment for the child's development.

Hospitalization for COVID-19 is associated with a higher risk of subsequent hospitalization for psychiatric disorders: A French nationwide longitudinal study comparing hospitalizations for COVID-19 and for other reasons.

INTRODUCTION: Although COVID-19 has been associated with psychiatric symptoms in patients, no study to date has examined the risk of hospitalization for psychiatric disorders after hospitalization for this disease. OBJECTIVE: We aimed to compare the proportions of hospitalizations for psychiatric disorders in the 12 months following either hospitalization for COVID-19 or hospitalization for another reason in the adult general population in France during the first wave of the current pandemic. METHODS: We conducted a retrospective longitudinal nationwide study based on the national French administrative healthcare database. RESULTS: Among the 2,894,088 adults hospitalized, 96,313 (3.32%) were admitted for COVID-19. The proportion of patients subsequently hospitalized for a psychiatric disorder was higher for COVID-19 patients (11.09 vs. 9.24%, OR = 1.20 95%CI 1.18-1.23). Multivariable analyses provided similar results for a psychiatric disorder of any type and for psychotic and anxiety disorders (respectively, aOR = 1.06 95%CI 1.04-1.09, aOR = 1.09 95%CI 1.02-1.17, and aOR = 1.11 95%CI 1.08-1.14). Initial hospitalization for COVID-19 in intensive care units and psychiatric history were associated with a greater risk of subsequent hospitalization for any psychiatric disorder than initial hospitalization for another reason. DISCUSSION: Compared with hospitalizations for other reasons, hospitalizations for COVID-19 during the first wave of the pandemic in France were associated with a higher risk of hospitalization for a psychiatric disorder during the 12 months following initial discharge. This finding should encourage clinicians to increase the monitoring and assessment of psychiatric symptoms after hospital discharge for COVID-19, and to propose post-hospital care, especially for those treated in intensive care.

Hospitalised traumatic brain injury victims in France: An analysis of the French hospital discharge database for 2011-2016.

BACKGROUND: Traumatic brain injury (TBI) is a major public health problem because of its severity and frequency. No recent national epidemiological study on TBI victims is currently available in France. OBJECTIVE: This study aimed to quantify and characterise TBI victims and analyse temporal trends. METHODS: French hospitalisation data were used in this study. All hospitalised patients residing in France with at least one International Classification of Disease, 10th revision, code S06.0 to S06.9 during 2011-2016 were selected. Incidence and hospital case-fatality rates were calculated. Quasi-Poisson models were used to analyse temporal trends. RESULTS: In 2016, the incidence rate was 230.6/100,000 people, higher among men than women regardless of age. Incidence and hospital case-fatality rates were also higher among older than younger people. Incidence rates increased during 2011-2016, mainly due to the higher incidence rate with age ≥65 years than younger age. During 2011-2016, hospital case-fatality rates decreased, mainly due to the decrease in the older age group (≥65 years old). CONCLUSIONS: To our knowledge, this is the first national study in France to provide recent data on hospitalised TBI victims. Our study shows that TBI is a major public health concern in France. As a priority, older people represent a risk group that should be targeted with preventive actions because they have both the highest incidence and case-fatality rates and had the largest increase in incidence rates over the study period.

Clinical, pathological and loss of heterozygosity differences in Wilms tumors between Asian and non-Asian children.

Wilms tumor demonstrates significant interethnic epidemiological, histological and outcome differences, and is rare and poorly studied among Asians. We compared the clinicopathological, and loss of heterozygosity (LOH) profile and survival outcomes of Asian and non-Asian patients with Wilms tumor. Clinical charts and histological slides from patients with malignant renal tumors over a period of 20 years were retrospectively reviewed. We adapted a genotyping assay to determine 1p36 and 16q21-22 LOH in formalin-fixed paraffin-embedded (FFPE) specimens, and compared these characteristics between Asian and non-Asian patients. Fifty-three (79.1%) Asian and 14 (20.9%) non-Asian patients had Wilms tumors. Compared to non-Asians, Asians were younger (mean 4.6 and 4.0 years, respectively), had more equal gender distribution (female: male = 1.8 and 1.0, respectively), fewer tumors with unfavorable histology (25.0% and 4.1%, respectively, p = 0.05), and less advanced disease at presentation, yet similar nodal metastases rates (16.7% and 18.4%, respectively). No Asian patients had bilateral tumors. Our adapted genotyping assay accurately determined LOH in FFPE specimens <10 years post-fixation. Among 30 Asian patients, 1p and 16q LOH were each detected in 5 (16.7%) patients, respectively-similar to rates reported in other ethnicities. Yet after similar treatment with National Wilms Tumor Study regimens, 15-year event-free and overall survival for Asian patients was 95.7% and 96.3% respectively. In summary, despite similar nodal metastasis and LOH rates, Asian patients had fewer unfavorable histology tumors, lower-stage disease, and better survival outcomes. The bases for these differences and implications on treatment strategy for these patients warrant further study.

Biological significance and prognostic relevance of peripheral blood neutrophil-to-lymphocyte ratio in soft tissue sarcoma.

Peripheral blood indices of systemic inflammation such as the neutrophil-lymphocyte ratio (NLR) have been shown to be prognostic in various cancers. We aim to investigate the clinical significance of these indices in patients with soft tissue sarcoma (STS). Seven hundred and twelve patients with available blood counts at diagnosis and/or metastatic relapse were retrospectively examined. An optimal cutoff for NLR-high (>2.5) in predicting overall survival (OS) was determined using receiver operating curve analyses. Survival analyses were performed using the Kaplan-Meier method and multivariate Cox proportional models. Our results show that NLR was significantly higher in patients with distant metastasis at diagnosis (n = 183) compared to those without (n = 529) (median: 4.36 vs 2.85, p < 0.0001). Progression of localized disease at diagnosis to metastatic relapse within the same patients was associated with an interval increase in NLR (median: 3.21 vs 3.74, p = 0.0003). In multivariate analysis, NLR-high was the only consistent factor independently associated with both worse OS (HR 1.53, 95% CI 1.10-2.13, p = 0.0112) and relapse-free survival (HR 1.41, 95% CI 1.08-1.85, p = 0.0125) in localized disease, as well as OS (HR 1.82, 95% CI 1.16-2.85, p = 0.0087) in metastatic/unresectable disease. In conclusion, high NLR is an independent marker of poor prognosis among patients with STS.

Treatment and outcomes of melanoma in Asia: Results from the National Cancer Centre Singapore.

BACKGROUND: Acral melanoma (AM) and mucosal melanoma (MM) make up more than half of melanomas in Asia but comprise only 5% of cases in Caucasians, where cutaneous melanoma (CM) predominates. AM and MM are thought to be genetically and biologically distinct from CM. We report the characteristics and outcomes of melanoma patients from the National Cancer Centre Singapore. METHODS: Case records of 210 patients treated between 2002 and 2014 were reviewed. RESULTS: Median follow-up was 2.5 years. CM, AM and MM made up of 37.6%, 33.8% and 16.2% of cases, respectively, with 6.2% each having ocular melanoma and unknown primary. Caucasians made up 16.2% of patients, accounting for 36.7% of CM but only 2.8 of AM and 2.9% of MM. Patients with MM (2.9% stage I, 14.7% stage IV) presented with higher American Joint Committee on Cancer (AJCC) stage than those with AM (16.9% stage I, 5.6% stage IV) or CM (24.1% stage I, 8.9% stage IV) (P = 0.01). Median overall survival (OS) was 5.7 years for all patients, and 1.0 year for metastatic disease. Considering stage I-III disease, multivariable Cox regression analysis demonstrated age ≥60 years and higher stage to be independent adverse prognostic factors for RFS and OS. Sentinel lymph node biopsy, undertaken for 56 stage I-III patients (25 AM, 31 CM) did not influence outcome. CONCLUSION: Our study reinforces the known unique clinicopathologic features of melanomas in Asians where AM and MM predominate. Age and stage remain the most critical prognostic factors across all subtypes.

Use of medical administrative data for the surveillance of psychotic disorders in France.

BACKGROUND: Psychotic disorders are among the most severe psychiatric disorders that have great effects on the individuals and the society. For surveillance of chronic low prevalence conditions such as psychotic disorders, medical administrative databases can be useful due to their large coverage of the population, their continuous availability and low costs with possibility of linkage between different databases. The aims of this study are to identify the population with psychotic disorders by different algorithms based on the French medical administrative data and examine the prevalence and characteristics of this population in 2014. METHODS: The health insurance system covers the entire population living in France and all reimbursements of ambulatory care in private practice are included in a national health insurance claim database, which can be linked with the national hospital discharge databases. Three algorithms were used to select most appropriately persons with psychotic disorders through data from hospital discharge databases, reimbursements for psychotropic medication and full insurance coverage for chronic and costly conditions. RESULTS: In France in 2014, estimates of the number of individuals with psychotic disorders were 469,587 (54.6% males) including 237,808 with schizophrenia (63.6% males). Of those, 77.0% with psychotic disorders and 70.8% with schizophrenia received exclusively ambulatory care. Prevalence rates of psychotic disorders were 7.4 per 1000 inhabitants (8.3 in males and 6.4 in females) and 3.8 per 1000 inhabitants (4.9 in males and 2.6 in females) for schizophrenia. Prevalence of psychotic disorders reached a maximum of 14 per 1000 in males between 35 and 49 years old then decreased with age while in females, the highest rate of 10 per 1000 was reached at age 50 without decrease with advancing age. No such plateau was observed in schizophrenia. DISCUSSION: This study is the first in France using an exhaustive sample of medical administrative data to derive prevalence rates for psychotic disorders. Although only individuals in contact with healthcare services were included, the rates were congruent with reported estimates from systematic reviews. The feasibility of this study will allow the implementation of a national surveillance of psychotic disorders essential for healthcare management and policy planning.

Germline Mutations in Cancer Predisposition Genes are Frequent in Sporadic Sarcomas.

Associations of sarcoma with inherited cancer syndromes implicate genetic predisposition in sarcoma development. However, due to the apparently sporadic nature of sarcomas, little attention has been paid to the role genetic susceptibility in sporadic sarcoma. To address this, we performed targeted-genomic sequencing to investigate the prevalence of germline mutations in known cancer-associated genes within an Asian cohort of sporadic sarcoma patients younger than 50 years old. We observed 13.6% (n = 9) amongst 66 patients harbour at least one predicted pathogenic germline mutation in 10 cancer-associated genes including ATM, BRCA2, ERCC4, FANCC, FANCE, FANCI, MSH6, POLE, SDHA and TP53. The most frequently affected genes are involved in the DNA damage repair pathway, with a germline mutation prevalence of 10.6%. Our findings suggests that genetic predisposition plays a larger role than expected in our Asian cohort of sporadic sarcoma, therefore clinicians should be aware of the possibility that young sarcoma patients may be carriers of inherited mutations in cancer genes and should be considered for genetic testing, regardless of family history. The prevalence of germline mutations in DNA damage repair genes imply that therapeutic strategies exploiting the vulnerabilities resulting from impaired DNA repair may be promising areas for translational research.

Cellular adhesiveness and cellulolytic capacity in Anaerolineae revealed by omics-based genome interpretation.

BACKGROUND: The Anaerolineae lineage of Chloroflexi had been identified as one of the core microbial populations in anaerobic digesters; however, the ecological role of the Anaerolineae remains uncertain due to the scarcity of isolates and annotated genome sequences. Our previous metatranscriptional analysis revealed this prevalent population that showed minimum involvement in the main pathways of cellulose hydrolysis and subsequent methanogenesis in the thermophilic cellulose fermentative consortium (TCF). RESULTS: In further pursuit, five high-quality curated draft genomes (>98 % completeness) of this population, including two affiliated with the inaccessible lineage of SBR1031, were retrieved by sequence-based multi-dimensional coverage binning. Comparative genomic analyses revealed versatile genetic capabilities for carbohydrate-based fermentative lifestyle including key genes catalyzing cellulose hydrolysis in Anaerolinea phylotypes. However, the low transcriptional activities of carbohydrate-active genes (CAGs) excluded cellulolytic capability as the selective advantage for their prevalence in the community. Instead, a substantially active type VI pili (Tfp) assembly was observed. Expression of the tight adherence protein on the Tfp indicated its function for cellular attachment which was further testified to be more likely related to cell aggregation other than cellulose surface adhesion. Meanwhile, this Tfp structure was found not contributing to syntrophic methanogenesis. Members of the SBR1031 encoded key genes for acetogenic dehydrogenation that may allow ethanol to be used as a carbon source. CONCLUSION: The common prevalence of Anaerolineae in anaerobic digesters should be originated from advantageous cellular adhesiveness enabled by Tfp assembly other than its potential as cellulose degrader or anaerobic syntrophs.

Brain metastasis in sarcoma: Does metastasectomy or aggressive multi-disciplinary treatment improve survival outcomes.

AIM: Brain metastasis is rare in sarcoma. Prognostic factors, optimal management strategies and therapeutic outcomes of such patients are not well studied. We aimed to evaluate the incidence, clinical characteristics and treatment outcomes of parenchymal brain metastasis in sarcoma patients. METHODS: This is a single center retrospective analysis. Overall survival (OS) was calculated from the time of diagnosis of brain metastasis to time of death. RESULTS: Sixteen patients (2.1%) with complete electronic medical records treated at our institution from 2002 to 2010 were identified. Median age was 52 years; 88% had additional sites of metastases. Eight different subtypes of soft tissue and bone sarcoma were identified. Eighty-one percent of the patients developed metachronous brain metastasis at a median of 14 months after initial sarcoma diagnosis. Thirty-eight percent of patients had solitary brain metastasis and 44% underwent aggressive therapy for brain metastasis, defined as either surgical resection or multimodality treatment. The remaining 56% received conservative treatment (either whole brain radiation alone, chemotherapy alone or best supportive care). Median OS for the entire cohort was 3.5 months (95% CI 1.1-6.3 months). A trend toward improved OS was observed with an aggressive treatment approach, 3.7 months versus 1.2 months (P = 0.077) and the usage of chemotherapy (P = 0.071). CONCLUSION: Brain metastasis in sarcoma is rare, usually coexists with significant systemic disease and is associated with a grave prognosis. Use of chemotherapy and an aggressive treatment approach in well-selected patients may be associated with improved survival. Prospective studies are needed to confirm these findings.

misFinder: identify mis-assemblies in an unbiased manner using reference and paired-end reads.

BACKGROUND: Because of the short read length of high throughput sequencing data, assembly errors are introduced in genome assembly, which may have adverse impact to the downstream data analysis. Several tools have been developed to eliminate these errors by either 1) comparing the assembled sequences with some similar reference genome, or 2) analyzing paired-end reads aligned to the assembled sequences and determining inconsistent features alone mis-assembled sequences. However, the former approach cannot distinguish real structural variations between the target genome and the reference genome while the latter approach could have many false positive detections (correctly assembled sequence being considered as mis-assembled sequence). RESULTS: We present misFinder, a tool that aims to identify the assembly errors with high accuracy in an unbiased way and correct these errors at their mis-assembled positions to improve the assembly accuracy for downstream analysis. It combines the information of reference (or close related reference) genome and aligned paired-end reads to the assembled sequence. Assembly errors and correct assemblies corresponding to structural variations can be detected by comparing the genome reference and assembled sequence. Different types of assembly errors can then be distinguished from the mis-assembled sequence by analyzing the aligned paired-end reads using multiple features derived from coverage and consistence of insert distance to obtain high confident error calls. CONCLUSIONS: We tested the performance of misFinder on both simulated and real paired-end reads data, and misFinder gave accurate error calls with only very few miscalls. And, we further compared misFinder with QUAST and REAPR. misFinder outperformed QUAST and REAPR by 1) identified more true positive mis-assemblies with very few false positives and false negatives, and 2) distinguished the correct assemblies corresponding to structural variations from mis-assembled sequence. misFinder can be freely downloaded from https://github.com/hitbio/misFinder.

Phylogeny-structured carbohydrate metabolism across microbiomes collected from different units in wastewater treatment process.

BACKGROUND: With respect to global priority for bioenergy production from plant biomass, understanding the fundamental genetic associations underlying carbohydrate metabolisms is crucial for the development of effective biorefinery process. Compared with gut microbiome of ruminal animals and wood-feed insects, knowledge on carbohydrate metabolisms of engineered biosystems is limited. RESULTS: In this study, comparative metagenomics coupled with metabolic network analysis was carried out to study the inter-species cooperation and competition among carbohydrate-active microbes in typical units of wastewater treatment process including activated sludge and anaerobic digestion. For the first time, sludge metagenomes demonstrated rather diverse pool of carbohydrate-active genes (CAGs) comparable to that of rumen microbiota. Overall, the CAG composition correlated strongly with the microbial phylogenetic structure across sludge types. Gene-centric clustering analysis showed the carbohydrate pathways of sludge systems were shaped by different environmental factors, including dissolved oxygen and salinity, and the latter showed more determinative influence of phylogenetic composition. Eventually, the highly clustered co-occurrence network of CAGs and saccharolytic phenotypes, revealed three metabolic modules in which the prevalent populations of Actinomycetales, Clostridiales and Thermotogales, respectively, play significant roles as interaction hubs, while broad negative co-exclusion correlations observed between anaerobic and aerobic microbes, probably implicated roles of niche separation by dissolved oxygen in determining the microbial assembly. CONCLUSIONS: Sludge microbiomes encoding diverse pool of CAGs was another potential source for effective lignocellulosic biomass breakdown. But unlike gut microbiomes in which Clostridiales, Lactobacillales and Bacteroidales play a vital role, the carbohydrate metabolism of sludge systems is built on the inter-species cooperation and competition among Actinomycetales, Clostridiales and Thermotogales.

A Simple Algorithm for Finding All k-Edge-Connected Components.

The problem of finding k-edge-connected components is a fundamental problem in computer science. Given a graph G = (V, E), the problem is to partition the vertex set V into {V1, V2,…, Vh}, where each Vi is maximized, such that for any two vertices x and y in Vi, there are k edge-disjoint paths connecting them. In this paper, we present an algorithm to solve this problem for all k. The algorithm preprocesses the input graph to construct an Auxiliary Graph to store information concerning edge-connectivity among every vertex pair in O(Fn) time, where F is the time complexity to find the maximum flow between two vertices in graph G and n = ∣V∣. For any value of k, the k-edge-connected components can then be determined by traversing the auxiliary graph in O(n) time. The input graph can be a directed or undirected, simple graph or multigraph. Previous works on this problem mainly focus on fixed value of k.

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html.

Time trends in pulmonary embolism mortality in France, 2000-2010.

BACKGROUND: Pulmonary Embolism (PE) is a potentially fatal complication of venous thrombosis. Recent and comprehensive estimates of PE incidence and mortality are scarce. Moreover, while contemporary mortality trends of PE would enable the evaluation of prevention and quality of care, such data are lacking. The aim of this study was to provide nationwide estimations of PE mortality and time trends in France between 2000 and 2010. METHODS: Mortality data were obtained from the French Epidemiology Center on medical causes of death. Mortality rates were calculated with PE as an underlying or one of multiple causes of death. The annual percentage changes were assessed using a Poisson regression model. Age-standardized PE mortality rates were also assessed. RESULTS: In 2010, the overall age-adjusted PE mortality rate was 21.0 per 100000. This rate was 30% higher in men than in women and decreased by 3% per year between 2000 and 2010. Over this period, PE mortality declined in men and women over 55 years but only slightly decreased in patients younger than 55. Cancer, obesity, osteopathies and complications of surgery were often coded as the underlying causes of death when PE was an associated cause of death recorded on certificate. DISCUSSION: This study is the first to provide a contemporary and exhaustive nationwide estimation of PE mortality and time trends in France. The observed decrease in PE mortality between 2000 and 2010 is encouraging, but further efforts in prevention are needed to ensure that this reduction is widespread in all age groups.

IDBA-MTP: A Hybrid Metatranscriptomic Assembler Based on Protein Information.

Metatranscriptomic analysis provides information on how a microbial community reacts to environmental changes. Using next-generation sequencing (NGS) technology, biologists can study the microbe community by sampling short reads from a mixture of mRNAs (metatranscriptomic data). As most microbial genome sequences are unknown, it would seem that de novo assembly of the mRNAs is needed. However, NGS reads are short and mRNAs share many similar regions and differ tremendously in abundance levels, making de novo assembly challenging. The existing assembler, IDBA-MT, designed specifically for the assembly of metatranscriptomic data and performs well only on high-expressed mRNAs. This article introduces IDBA-MTP, which adopts a novel approach to metatranscriptomic assembly that makes use of the fact that there is a database of millions of known protein sequences associated with mRNAs. How to effectively use the protein information is nontrivial given the size of the database and given that different mRNAs might lead to proteins with similar functions (because different amino acids might have similar characteristics). IDBA-MTP employs a similarity measure between mRNAs and protein sequences, dynamic programming techniques, and seed-and-extend heuristics to tackle the problem effectively and efficiently. Experimental results show that IDBA-MTP outperforms existing assemblers by reconstructing 14% more mRNAs.

PERGA: a paired-end read guided de novo assembler for extending contigs using SVM and look ahead approach.

Since the read lengths of high throughput sequencing (HTS) technologies are short, de novo assembly which plays significant roles in many applications remains a great challenge. Most of the state-of-the-art approaches base on de Bruijn graph strategy and overlap-layout strategy. However, these approaches which depend on k-mers or read overlaps do not fully utilize information of paired-end and single-end reads when resolving branches. Since they treat all single-end reads with overlapped length larger than a fix threshold equally, they fail to use the more confident long overlapped reads for assembling and mix up with the relative short overlapped reads. Moreover, these approaches have not been special designed for handling tandem repeats (repeats occur adjacently in the genome) and they usually break down the contigs near the tandem repeats. We present PERGA (Paired-End Reads Guided Assembler), a novel sequence-reads-guided de novo assembly approach, which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds using paired-end reads and different read overlap size ranging from Omax to Omin to resolve the gaps and branches. By constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. When the correct extension cannot be determined, PERGA will try to extend the contig by all feasible extensions and determine the correct extension by using look-ahead approach. Many difficult-resolved branches are due to tandem repeats which are close in the genome. PERGA detects such different copies of the repeats to resolve the branches to make the extension much longer and more accurate. We evaluated PERGA on both Illumina real and simulated datasets ranging from small bacterial genomes to large human chromosome, and it constructed longer and more accurate contigs and scaffolds than other state-of-the-art assemblers. PERGA can be freely downloaded at https://github.com/hitbio/PERGA.

Sequence assembly using next generation sequencing data--challenges and solutions.

Sequence assembling is an important step for bioinformatics study. With the help of next generation sequencing (NGS) technology, high throughput DNA fragment (reads) can be randomly sampled from DNA or RNA molecular sequence. However, as the positions of reads being sampled are unknown, assembling process is required for combining overlapped reads to reconstruct the original DNA or RNA sequence. Compared with traditional Sanger sequencing methods, although the throughput of NGS reads increases, the read length is shorter and the error rate is higher. It introduces several problems in assembling. Moreover, paired-end reads instead of single-end reads can be sampled which contain more information. The existing assemblers cannot fully utilize this information and fails to assemble longer contigs. In this article, we will revisit the major problems of assembling NGS reads on genomic, transcriptomic, metagenomic and metatranscriptomic data. We will also describe our IDBA package for solving these problems. IDBA package has adopted several novel ideas in assembling, including using multiple k, local assembling and progressive depth removal. Compared with existence assemblers, IDBA has better performance on many simulated and real sequencing datasets.

MetaCluster-TA: taxonomic annotation for metagenomic data based on assembly-assisted binning.

BACKGROUND: Taxonomic annotation of reads is an important problem in metagenomic analysis. Existing annotation tools, which rely on the approach of aligning each read to the taxonomic structure, are unable to annotate many reads efficiently and accurately as reads (~100 bp) are short and most of them come from unknown genomes. Previous work has suggested assembling the reads to make longer contigs before annotation. More reads/contigs can be annotated as a longer contig (in Kbp) can be aligned to a taxon even if it is from an unknown species as long as it contains a conserved region of that taxon. Unfortunately existing metagenomic assembly tools are not mature enough to produce long enough contigs. Binning tries to group reads/contigs of similar species together. Intuitively, reads in the same group (cluster) should be annotated to the same taxon and these reads altogether should cover a significant portion of the genome alleviating the problem of short contigs if the quality of binning is high. However, no existing work has tried to use binning results to help solve the annotation problem. This work explores this direction. RESULTS: In this paper, we describe MetaCluster-TA, an assembly-assisted binning-based annotation tool which relies on an innovative idea of annotating binned reads instead of aligning each read or contig to the taxonomic structure separately. We propose the novel concept of the 'virtual contig' (which can be up to 10 Kb in length) to represent a set of reads and then represent each cluster as a set of 'virtual contigs' (which together can be total up to 1 Mb in length) for annotation. MetaCluster-TA can outperform widely-used MEGAN4 and can annotate (1) more reads since the virtual contigs are much longer; (2) more accurately since each cluster of long virtual contigs contains global information of the sampled genome which tends to be more accurate than short reads or assembled contigs which contain only local information of the genome; and (3) more efficiently since there are much fewer long virtual contigs to align than short reads. MetaCluster-TA outperforms MetaCluster 5.0 as a binning tool since binning itself can be more sensitive and precise given long virtual contigs and the binning results can be improved using the reference taxonomic database. CONCLUSIONS: MetaCluster-TA can outperform widely-used MEGAN4 and can annotate more reads with higher accuracy and higher efficiency. It also outperforms MetaCluster 5.0 as a binning tool.

DDGni: dynamic delay gene-network inference from high-temporal data using gapped local alignment.

MOTIVATION: Inferring gene-regulatory networks is very crucial in decoding various complex mechanisms in biological systems. Synthesis of a fully functional transcriptional factor/protein from DNA involves series of reactions, leading to a delay in gene regulation. The complexity increases with the dynamic delay induced by other small molecules involved in gene regulation, and noisy cellular environment. The dynamic delay in gene regulation is quite evident in high-temporal live cell lineage-imaging data. Although a number of gene-network-inference methods are proposed, most of them ignore the associated dynamic time delay. RESULTS: Here, we propose DDGni (dynamic delay gene-network inference), a novel gene-network-inference algorithm based on the gapped local alignment of gene-expression profiles. The local alignment can detect short-term gene regulations, that are usually overlooked by traditional correlation and mutual Information based methods. DDGni uses 'gaps' to handle the dynamic delay and non-uniform sampling frequency in high-temporal data, like live cell imaging data. Our algorithm is evaluated on synthetic and yeast cell cycle data, and Caenorhabditis elegans live cell imaging data against other prominent methods. The area under the curve of our method is significantly higher when compared to other methods on all three datasets. AVAILABILITY: The program, datasets and supplementary files are available at http://www.jjwanglab.org/DDGni/.