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The impact of short tandem repeat variation on gene expression.
Short tandem repeats (STRs) have been implicated in a variety of complex traits in humans. However, genome-wide studies of the effects of STRs on gene expression thus far have had limited power to detect associations and provide insights into putative mechanisms. Here, we leverage whole-genome sequencing and expression data for 17 tissues from the Genotype-Tissue Expression Project to identify more than 28,000 STRs for which repeat number is associated with expression of nearby genes (eSTRs). We use fine-mapping to quantify the probability that each eSTR is causal and characterize the top 1,400 fine-mapped eSTRs. We identify hundreds of eSTRs linked with published genome-wide association study signals and implicate specific eSTRs in complex traits, including height, schizophrenia, inflammatory bowel disease and intelligence. Overall, our results support the hypothesis that eSTRs contribute to a range of human phenotypes, and our data should serve as a valuable resource for future studies of complex traits
Taking the bite out of automated naming of characters in TV video
We investigate the problem of automatically labelling appearances of characters in TV or film material
with their names. This is tremendously challenging due to the huge variation in imaged appearance of each character and the weakness and ambiguity of available annotation. However, we demonstrate that high precision can be achieved by combining multiple sources of information, both visual and textual. The principal novelties that we introduce are: (i) automatic generation of time stamped character annotation by aligning subtitles and transcripts; (ii) strengthening the supervisory information by identifying
when characters are speaking. In addition, we incorporate complementary cues of face matching and clothing matching to propose common annotations for face tracks, and consider choices of classifier which can potentially correct errors made in the automatic extraction of training data from the weak textual annotation. Results are presented on episodes of the TV series ‘‘Buffy the Vampire Slayer”
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