Using screen video capture software to aide and inform cognitive interviewing

Web-based surveys are a salient tool in the repertoire of social and behavioral scientists. The increase in web-based surveys is understandable considering the distinct advantages offered, including: (a) lower costs and reduced labor time, (b) ability to directly transfer data into statistical packages (reducing coding errors), (c) customization options enabling more attractive presentation, (d) ability to reduce respondent burden by embedding skip patterns, and (e) access to larger sample sizes in different geographic regions. It is important to note, however, that administering web-based surveys also introduces distinct sources of error (e.g., coverage, sampling and non-response). Regardless of format (e.g., paper-and-pencil or web-based), specific, prescribed steps must be followed when constructing an instrument in order to reduce survey error and lend credence to the data collected before subsequent analysis is performed. One of those crucial stages integral to the pretesting process is cognitive interviewing. Cognitive interviewing is a qualitative process, encompassing two main techniques: think aloud interviewing and verbal probing. Collectively, these two methods seek to (a) produce information on what the respondent is thinking while answering the questions, (b) the cognitive processes used to answer the questions, and (c) how the respondent answers the questions. The purpose of this article is to provide a practical guide outlining how Camtasia, a screen video capture software, can aide and inform the cognitive interview process

Parental origin of sequence variants associated with complex diseases

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldEffects of susceptibility variants may depend on from which parent they are inherited. Although many associations between sequence variants and human traits have been discovered through genome-wide associations, the impact of parental origin has largely been ignored. Here we show that for 38,167 Icelanders genotyped using single nucleotide polymorphism (SNP) chips, the parental origin of most alleles can be determined. For this we used a combination of genealogy and long-range phasing. We then focused on SNPs that associate with diseases and are within 500 kilobases of known imprinted genes. Seven independent SNP associations were examined. Five-one with breast cancer, one with basal-cell carcinoma and three with type 2 diabetes-have parental-origin-specific associations. These variants are located in two genomic regions, 11p15 and 7q32, each harbouring a cluster of imprinted genes. Furthermore, we observed a novel association between the SNP rs2334499 at 11p15 and type 2 diabetes. Here the allele that confers risk when paternally inherited is protective when maternally transmitted. We identified a differentially methylated CTCF-binding site at 11p15 and demonstrated correlation of rs2334499 with decreased methylation of that site.info:eu-repo/grantAgreement/EC/FP7/21807

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits : A Multi-Ethnic Meta-Analysis of 45,891 Individuals

J. Kaprio, S. Ripatti ja M.-L. Lokki työryhmien jäseniä.Peer reviewe

AptaCluster – A Method to Cluster HT-SELEX Aptamer Pools and Lessons from Its Application

Systematic Evolution of Ligands by EXponential Enrichment (SELEX) is a well established experimental procedure to identify aptamers - synthetic single-stranded (ribo)nucleic molecules that bind to a given molecular target. Recently, new sequencing technologies have revolutionized the SELEX protocol by allowing for deep sequencing of the selection pools after each cycle. The emergence of High Throughput SELEX (HT-SELEX) has opened the field to new computational opportunities and challenges that are yet to be addressed. To aid the analysis of the results of HT-SELEX and to advance the understanding of the selection process itself, we developed AptaCluster. This algorithm allows for an efficient clustering of whole HT-SELEX aptamer pools; a task that could not be accomplished with traditional clustering algorithms due to the enormous size of such datasets. We performed HT-SELEX with Interleukin 10 receptor alpha chain (IL-10RA) as the target molecule and used AptaCluster to analyze the resulting sequences. AptaCluster allowed for the first survey of the relationships between sequences in different selection rounds and revealed previously not appreciated properties of the SELEX protocol. As the first tool of this kind, AptaCluster enables novel ways to analyze and to optimize the HT-SELEX procedure. Our AptaCluster algorithm is available as a very fast multiprocessor implementation upon request