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Category | B |
---|---|
Domain name | bbseq.us |
IP | 160.202.100.57 |
Country by IP | US |
Web server type | IIS |
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BBSeq ~ Yi-Hui Zhou A Powerful and Flexible Approach to the Analysis of RNA Sequence Count Data. Yi- Hui Zhou Department of Biostatistics, University of North Carolina Key features: Designed for the differential expression analysis of the RNA-Seq Count data. Use Beta-Binomial model to consider the overdispersion of the count data. Visit website
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BBSeq has been tuned to correspond to the tpical data structure of RNA-Seq count data, which typically is based on millions of reads and thousands of genes/transcripts. BBSeq is currently in beta evaluation form, and subject to continual improvement in the interface. 2 Preparation At a minimum, BBSeq requires a count data matrix and a predictor ... Visit website
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BBSeq (Beta-Binomial modeling of the overdispersion of the RNA-seq count data)is used to identify differential expression in high-throughput count data, such as RNAseq count data which is derived from next-generation sequencing machines. Our modeling design is very flexible. Visit website
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This vignette describes how to use BBSeq to evaluate differential expression using count data and to measure the effect of design variables or covariates. BBSeq has been tuned to correspond to the tpical data structure of RNA-Seq count data, which typically is based on millions of reads and thousands of genes/transcripts. BBSeq is currently in beta evaluation form, and subject to … Visit website
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