bluuebunny/crossref_metadata_2025_split huggingface dataset:
WhatsHap: fast and accurate read-based phasing
Authors: Martin Marcel , Patterson Murray , Garg Shilpa , O Fischer Sarah , Pisanti Nadia , Klau Gunnar W , Schöenhuth Alexander , Marschall Tobias 
Published: November 2016

AbstractRead-based phasing allows to reconstruct the haplotypes of a sample purely from sequencing reads. While phasing is an important step for answering questions about population genetics, compound heterozygosity, and to aid in clinical decision making, there has been a lack of accurate, usable and standards-based software.WhatsHap is a production-ready tool for highly accurate read-based phasing. It was designed from the beginning to leverage third-generation sequencing technologies, whose long reads can span many variants and are therefore ideal for phasing. WhatsHap works also well with second-generation data, is easy to use and will phase not only SNVs, but also indels and other variants. It is unique in its ability to combine read-based with pedigree-based phasing, allowing to further improve accuracy if multiple related samples are provided.
True causal effect size heterogeneity is not required to explain trans-ethnic differences in GWAS signals
Authors: Zanetti Daniela , Weale Michael E. 
Published: November 2016

AbstractThrough genome-wide association studies (GWASs), researchers have identified hundreds of genetic variants associated with particular complex traits. Previous studies have compared the pattern of association signals across different populations in real data, and these have detected differences in the strength and sometimes even the direction of GWAS signals. These differences could be due to a combination of (1) lack of power (insufficient sample sizes); (2) minor allele frequency (MAF) differences (again affecting power); (3) linkage disequilibrium (LD) differences (affecting power to ‘tag’ the causal variant); and (4) true differences in causal variant effect sizes (defined by relative risks).In the present work, we sought to assess whether the first three of these reasons are sufficient on their own to explain the observed incidence of trans-ethnic differences in replications of GWAS signals, or whether the fourth reason is also required. We simulated case-control data of European, Asian and African ancestry, drawing on observed MAF and LD patterns seen in the 1000-Genomes reference dataset and assuming the true causal relative risks were the same in all three populations.We found that a combination of Euro-centric SNP selection and between-population differences in LD, accentuated by the lower SNP density typical of older GWAS panels, was sufficient to explain the rate of trans-ethnic differences previously reported, without the need to assume between-population differences in true causal SNP effect size. This suggests a cross-population consistency that has implications for our understanding of the interplay between genetics and environment in the aetiology of complex human diseases.
Automating Morphological Profiling with Generic Deep Convolutional Networks
Authors: Pawlowski Nick , Caicedo Juan C , Singh Shantanu , Carpenter Anne E , Storkey Amos 
Published: November 2016

AbstractMorphological profiling aims to create signatures of genes, chemicals and diseases from microscopy images. Current approaches use classical computer vision-based segmentation and feature extraction. Deep learning models achieve state-of-the-art performance in many computer vision tasks such as classification and segmentation. We propose to transfer activation features of generic deep convolutional networks to extract features for morphological profiling. Our approach surpasses currently used methods in terms of accuracy and processing speed. Furthermore, it enables fully automated processing of microscopy images without need for single cell identification.
Habitat preference predicts genetic diversity and population divergence in Amazonian birds
Authors: Harvey Michael G. , Aleixo Alexandre , Ribas Camila C. , Brumfield Robb T. 
Published: November 2016

ABSTRACTThe ecological traits of organisms may predict important evolutionary parameters such as genetic diversity, population genetic structure, and demographic history. Making these ecological-evolutionary links is difficult because robust, comparable genetic estimates are required from many species with differing ecologies. In Amazonian birds, differences in habitat preference are an important component of ecological diversity. A subset of Amazonian birds is restricted to forest edge and open forest along floodplains, whereas another subset occurs only in the interior of tall, upland forest. Here, we examine the link between habitat and evolutionary metrics using 20 pairs of closely related and co-distributed bird species in which one member of the pair occurs primarily in forest edge and floodplains, and the other occurs in upland forest interior. We use standardized geographic sampling and genomic data from the same set of 2,416 independent markers to estimate genetic diversity, population structure, and demographic history in each species. We find that species of upland forest have higher genetic diversity, greater divergence across the landscape, more genetically distinct populations, and deeper gene histories than floodplain species. Our results reveal that species ecology in the form of habitat preference is an important predictor of genetic diversity and divergence and suggest that floodplain and upland avifaunas in the Amazon may be on separate evolutionary trajectories and require different conservation strategies.
Structural Modeling of Chromatin Integrates Genome Features and Reveals Chromosome Folding Principle
Authors: Xie Wen Jun , Meng Luming , Liu Sirui , Zhang Ling , Cai Xiaoxia , Gao Yi Qin 
Published: November 2016

AbstractHow chromosomes fold into 3D structures and how genome functions are affected or even controlled by their spatial organization remain challenging questions. Hi-C experiment has provided important structural insights for chromosome, and Hi-C data are used here to construct the 3D chromatin structure which are characterized by two spatially segregated chromatin compartments A and B. By mapping a plethora of genome features onto the constructed 3D chromatin model, we show vividly the close connection between genome properties and the spatial organization of chromatin. We are able to dissect the whole chromatin into two types of chromatin domains which have clearly different Hi-C contact patterns as well as different sizes of chromatin loops. The two chromatin types can be respectively regarded as the basic units of chromatin compartments A and B, and also spatially segregate from each other as the two chromatin compartments. Therefore, the chromatin loops segregate in the space according to their sizes, suggesting the excluded volume or entropic effect in chromatin compartmentalization as well as chromosome positioning. Taken together, these results provide clues to the folding principles of chromosomes, their spatial organization, and the resulted clustering of many genome features in the 3D space.
Smooth Quantile Normalization
Authors: Hicks Stephanie C , Okrah Kwame , Paulson Joseph N , Quackenbush John , Irizarry Rafael A , Corrada Bravo Héctor 
Published: November 2016

AbstractBetween-sample normalization is a critical step in genomic data analysis to remove systematic bias and unwanted technical variation in high-throughput data. Global normalization methods are based on the assumption that observed variability in global properties is due to technical reasons and are unrelated to the biology of interest. For example, some methods correct for differences in sequencing read counts by scaling features to have similar median values across samples, but these fail to reduce other forms of unwanted technical variation. Methods such as quantile normalization transform the statistical distributions across samples to be the same and assume global differences in the distribution are induced by only technical variation. However, it remains unclear how to proceed with normalization if these assumptions are violated, for example if there are global differences in the statistical distributions between biological conditions or groups, and external information, such as negative or control features, is not available. Here we introduce a generalization of quantile normalization, referred to assmooth quantile normalization(qsmooth), which is based on the assumption that the statistical distribution of each sample should be the same (or have the same distributional shape) within biological groups or conditions, but allowing that they may differ between groups. We illustrate the advantages of our method on several high-throughput datasets with global differences in distributions corresponding to different biological conditions. We also perform a Monte Carlo simulation study to illustrate the bias-variance tradeoff of qsmooth compared to other global normalization methods. A software implementation is available fromhttps://github.com/stephaniehicks/qsmooth.
Predicting Enhancer-Promoter Interaction from Genomic Sequence with Deep Neural Networks
Authors: Singh Shashank , Yang Yang , Póczos Barnabás , Ma Jian 
Published: November 2016

AbstractIn the human genome, distal enhancers are involved in regulating target genes through proxi-mal promoters by forming enhancer-promoter interactions. Although recently developed high-throughput experimental approaches have allowed us to recognize potential enhancer-promoter interactions genome-wide, it is still largely unclear to what extent the sequence-level information encoded in our genome help guide such interactions. Here we report a new computational method (named “SPEID”) using deep learning models to predict enhancer-promoter interactions based on sequence-based features only, when the locations of putative enhancers and promoters in a particular cell type are given. Our results across six different cell types demonstrate that SPEID is effective in predicting enhancer-promoter interactions as compared to state-of-the-art methods that only use information from a single cell type. As a proof-of-principle, we also applied SPEID to identify somatic non-coding mutations in melanoma samples that may have reduced enhancer-promoter interactions in tumor genomes. This work demonstrates that deep learning models can help reveal that sequence-based features alone are sufficient to reliably predict enhancer-promoter interactions genome-wide.
Analyzing relationships between project team compositions and green building certification in green building projects
Authors: Cheng Jack C.P. , Venkataraman Vignesh 
Published: November 2016

Purpose
Literature on organizational analysis identified that project participants have a certain impact on the project outcome. However, there is no study that identifies the impact of project teams and individual project participants on a green building project. The purpose of this paper is to analyze the impact of green building project teams on green building certification.

Design/methodology/approach
Project information, project team information, and green building certification grade were collected using the Canadian green building database. Project team data were analyzed and organizations were ranked based on their green building project experience and collaborations with experienced green building organizations. The page rank algorithm is used to calculate the rank of organizations in order to identify the impact of organizational rank on the final green building certification grade of a project.

Findings
The results show a positive relationship between the green building certification grade and the number of organizations with more green building experience in a project team. The results also show that not having experienced key organizations such as owners, designers, and contractors will likely lead to a lower green building certification grade.

Originality/value
Impact of project teams on green building projects has not been studied before. This study used an innovative method to analyze green building project teams and to investigate the importance of green building project experience. The findings of this study provided evidence to support the influence of project team compositions in green building projects. The results presented in this paper can help project owners and managers during project team formation for successful execution of green building projects.
Risk disclosure, cost of capital and bank performance
Authors: Nahar Shamsun , Azim Mohammad , Anne Jubb Christine 
Published: November 2016

PurposeThis study aims to examine the relationship among corporate risk disclosure, cost of equity capital and performance within banking institutions in a developing country setting. The authors argue that corporate risk disclosure reduces the cost of capital as investors attain better information and have confidence in the business and that less risk disclosure may generate ambiguity for potential stakeholders.Design/methodology/approachThis study uses the population of all 30 listed banks on the Dhaka Stock Exchange, Bangladesh, for the years 2006 to 2012 and uses three-stage least-squares simultaneous equations to deal with endogeneity issues.FindingsThere is evidence that Bangladesh has voluntarily adopted the International Financial Reporting Standard 7 – Financial Instruments: Disclosures (IFRS 7) and Basel II: Market Discipline and that these standards enhance risk disclosure even where compliance is not compulsory. The cost of capital is found to be negatively associated with risk disclosure, which has an inverse relationship with bank performance.Originality/valueThis study provides a link between risk disclosure, cost of capital and performance. It fills a gap in the literature by providing a longitudinal study of risk disclosure in the banking sector of Bangladesh. This research also highlights the importance of appropriate risk disclosure for banks and suggests its importance in the process of fulfilling stakeholders’ demands.
Related party transactions and accounting quality in Greece
Authors: El-Helaly Moataz 
Published: November 2016

Purpose
The purpose of this paper is to investigate the relationship between related party transactions (RPTs) and accounting quality for the firms listed on the Athens Stock Exchange.

Design/methodology/approach
This paper compares accounting quality across two groups of firms. The first group contains firms that conduct material RPTs and the second group contains firms that do not conduct material RPTs. Accounting quality is measured using different proxies of earnings management. Four earnings management proxies are used, three metrics for earnings smoothing and one for managing earnings towards a target.

Findings
The results of the current study do not suggest that firms with significant RPTs exhibit less accounting quality compared to non-RPTs firms.

Research limitations/implications
The results support the argument that RPTs are conventional transactions that are mainly conducted for business purposes.

Originality/value
This paper contributes to the literature by examining the effect of RPTs on accounting quality in Greece and whether firms that conduct RPTs exhibit less accounting quality or not.
Political connections and earnings quality
Authors: Harymawan Iman , Nowland John 
Published: November 2016

Purpose
The purpose of this study is to investigate how the earnings quality of politically connected firms is affected by changes in political stability and government effectiveness in a developing country.

Design/methodology/approach
This study uses a sample of 2,073 firm-year observations from 349 firms listed on the Indonesian Stock Exchange from 2003 to 2012 to examine how political stability and government effectiveness affect the earnings quality of politically connected firms, relative to non-politically connected firms. A two-stage model is used to address self-selection issues in the choice of firms to establish political connections.

Findings
This study finds that increased government effectiveness reduces the benefits of political connections, requiring politically connected firms to be more responsive to market pressures and resulting in higher earnings quality. However, increased political stability enhances the certainty of benefits from political connections, reducing the need for politically connected firms to respond to market pressures and resulting in lower earnings quality.

Research limitations/implications
For policymakers, these results indicate that different dimensions of political and economic development can affect the incentives of firms with political connections in different ways.

Originality/value
This study finds that the earnings quality of politically connected firms increases as government effectiveness improves, but it decreases as the political environment becomes more stable.
The motivations of earnings management and financial aggressiveness in American firms listed on the NASDAQ 100
Authors: Neifar Souhir , Halioui Khamoussi , Ben Abdelaziz Fouad 
Published: November 2016

Purpose
The purpose of this paper is to examine the motivations of earnings management and financial aggressiveness levels in the big 100 companies listed on the NASDAQ 100 after the 2007 financial crisis.

Design/methodology/approach
This paper uses two samples. The first contains 471 observations of 100 companies listed on the NASDAQ 100 for the period 2008-2012 and is used to examine the motivations of earnings management. The second represents 282 observations of companies listed on the NASDAQ 100 that use financial aggressiveness. The authors use a panel data model to analyze the effects of four explanatory variables (corporate governance structure, CEO compensation, CEO characteristics and audit fees) on both earnings management and financial aggressiveness levels.

Findings
The results of the investigation show the significant impact of corporate governance structure, CEO compensation, CEO characteristics and audit fees on reducing the earnings management and financial aggressiveness levels.

Research limitations/implications
The findings can be valuable to both investors and researchers. For researchers, the present work may help in explaining the motivations of earnings management and financial aggressiveness practices used by large American firms after the 2007 US financial crisis. For investors, this study serves to highlight the critical importance of corporate governance, CEO compensation and CEO characteristics in limiting such behaviors. Thus, investors are recommended to account for such variables in order to make effective investment decisions. As an extension to this study, researchers might consider other CEO psychological variables. Other market indices could also be considered in order to generalize and validate the results of the research.

Practical implications
Investors must take into consideration the corporate governance structure and ask for supplementary information about CEO characteristics to ensure better investment decisions.

Originality/value
In this paper, and in contrast to previous research, the authors test the impact of corporate governance structure, CEO compensation, CEO characteristics and audit fees together on the level of both earnings management and financial aggressiveness behavior for large US non-financial firms after the 2007 financial crisis. The authors show that older CEOs use less earnings management and financial aggressiveness. The findings can be valuable to investors, managers and regulators because they have implications for their interactive decision-making process.
Electronic word-of-mouth and information overload in an experiential service industry
Authors: Furner Christopher Paul , Zinko Robert , Zhu Zhen 
Published: November 2016

Purpose
Trust and purchase intent are established, dependent variables in electronic commerce research. Recent studies have highlighted the importance of online product reviews in the development of purchase intention, which has led to the development of a substantial research effort in the realm of electronic word-of-mouth (e-WOM). The purpose of this paper is to incorporate e-WOM, information processing and decision-making theories to propose a model of the development of trust and purchase intention based on online product reviews, and incorporate information overload as a moderating factor.

Design/methodology/approach
This study tests the hypotheses using a scenario-based experiment. In total, 157 working adults were asked to read three hotel reviews of different information load. Upon completion, they were then asked to respond to Likert-based questions regarding their trust in the review and purchase intention.

Findings
An inverted U-shaped relationship exists between information load and both trust and purchase intention, where low-information load is ineffective at fostering trust and purchase intention, moderate information load is effective at fostering trust and purchase intention, and high-information load is less effective than moderate information load at fostering trust and purchase intention.

Research limitations/implications
Although the authors supported the inverted U-shaped relationship between information load and two outcomes, the authors only tested three different review lengths, resulting in limited precision, it is not clear where the inflection point is (i.e. exactly how many words results in information overload). Future studies might both seek more precision, and also consider more consumer characteristics, such as risk propensity.

Practical implications
Review platform operators with a stake in encouraging a sale should prioritize and highlight reviews of moderate length (which can be assessed automatically via word count), and consider restricting new reviews of products to minimum and maximum word counts.

Originality/value
This study enhances the relevant and growing body of online review research by: bringing uncertainty reduction theory to bear on the consumer’s information search efforts; using information overload, an important construct from classic information processing and decision-making literature to explain consumer behavior; and identifying a review characteristics (information load) which influences consumer attitudes about a review (trust) and the product (purchase intention). Finally, this study enhances research understanding of a specific experiential service: hospitality.