An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Do Spontaneous Trait Inferences Influence Behavioral Intentions?

Character traits are spontaneously inferred from observing peopleâ??s behavior. This inference process is called a spontaneous trait inference. Although spontaneous trait inference effects are robust and well replicated, little research has examined what perceivers do with the inferences they make. A pilot study and two experiments examined whether spontaneous trait inferences led to differences in two behavioral intentions: friending and aggression. The savings in relearning paradigm was used to measure spontaneous trait inferences. Participants were exposed to trait implying descriptions or neutral descriptions of targets. After a filler task, participants completed a social media friending questionnaire and a modified voodoo doll task. They then learned target-trait pairings, completed a filler task, and completed a cued recall measure for the target-trait pairings. Spontaneous trait inferences were found across all experiments. Participants recalled implied traits more than control traits. As predicted, there was consistent support that spontaneous trait inferences led to differences in behavioral intentions. When participants made positive trait inferences, they were more likely to friend those targets on social media (Pilot Study & amp; Experiment 1). Participants were also less likely to friend targets they made negative trait inferences of (Experiment 2). When participants made negative trait inferences, they were more likely to aggress toward those targets by administering â??bad shots of karmaâ?? in a modified voodoo doll task (all experiments), especially when those targets performed behaviors directed toward the perceiver (Experiment 2). Implications of these results are discussed in the context of stereotype formation and extensions to discrimination

The Influence (Or Lack Thereof) Of Stereotypes On Spontaneous Trait Inferences

Research has shown that people spontaneously make trait inferences from observing others perform behaviors. The present research presents two experiments that examined the influence of stereotypes on spontaneous trait inferences. Experiment 1 utilized the recognition probe paradigm, a traditional method of assessing spontaneous trait inferences. Experiment 2 controlled for potential biases (e.g. priming effects and linguistic properties) by modifying the recognition probe paradigm. Results showed support for spontaneous trait inferences only with the traditional recognition probe paradigm. Stereotypes only influenced the accuracy of spontaneous trait inferences with the traditional recognition probe paradigm. The current results suggest that the traditional recognition probe paradigm does not account for priming effect nor linguistic properties that influence the detection of spontaneous trait inferences