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Tools and best practices for data processing in allelic expression analysis.

ABSTRACT: Allelic expression analysis has become important for integrating genome and transcriptome data to characterize various biological phenomena such as cis-regulatory variation and nonsense-mediated decay. We analyze the properties of allelic expression read count data and technical sources of error, such as low-quality or double-counted RNA-seq reads, genotyping errors, allelic mapping bias, and technical covariates due to sample preparation and sequencing, and variation in total read depth. We provide guidelines for correcting such errors, show that our quality control measures improve the detection of relevant allelic expression, and introduce tools for the high-throughput production of allelic expression data from RNA-sequencing data.

SUBMITTER: Castel SE

PROVIDER: S-EPMC4574606 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Tools and best practices for data processing in allelic expression analysis.

Castel Stephane E SE Levy-Moonshine Ami A Mohammadi Pejman P Banks Eric E Lappalainen Tuuli T

Genome biology 20150917

Allelic expression analysis has become important for integrating genome and transcriptome data to characterize various biological phenomena such as cis-regulatory variation and nonsense-mediated decay. We analyze the properties of allelic expression read count data and technical sources of error, such as low-quality or double-counted RNA-seq reads, genotyping errors, allelic mapping bias, and technical covariates due to sample preparation and sequencing, and variation in total read depth. We pro ...[more]

PMID: 26381377

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Project description:BackgroundInternet-based risk assessment tools offer a potential avenue for people to learn about their cancer risk and adopt risk-reducing behaviors. However, little is known about whether internet-based risk assessment tools adhere to scientific evidence for what constitutes good risk communication strategies. Furthermore, their quality may vary from a user experience perspective.ObjectiveThis study aims to understand the extent to which current best practices in risk communication have been applied to internet-based cancer risk assessment tools.MethodsWe conducted a search on August 6, 2019, to identify websites that provided personalized assessments of cancer risk or the likelihood of developing cancer. Each website (N=39) was coded according to standardized criteria and focused on 3 categories: general website characteristics, accessibility and credibility, and risk communication formats and strategies.ResultsSome best practices in risk communication were more frequently adhered to by websites. First, we found that undefined medical terminology was widespread, impeding comprehension for those with limited health literacy. For example, 90% (35/39) of websites included technical language that the general public may find difficult to understand, yet only 23% (9/39) indicated that medical professionals were their intended audience. Second, websites lacked sufficient information for users to determine the credibility of the risk assessment, making it difficult to judge the scientific validity of their risk. For instance, only 59% (23/39) of websites referenced the scientific model used to calculate the user's cancer risk. Third, practices known to foster unbiased risk comprehension, such as adding qualitative labels to quantitative numbers, were used by only 15% (6/39) of websites.ConclusionsLimitations in risk communication strategies used by internet-based cancer risk assessment tools were common. By observing best practices, these tools could limit confusion and cultivate understanding to help people make informed decisions and motivate people to engage in risk-reducing behaviors.

Dataset Information

Tools and best practices for data processing in allelic expression analysis.

Publications

Tools and best practices for data processing in allelic expression analysis.

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