ArticleStatistics and its interface
A penalized likelihood approach for robust estimation of isoform expression.
Article in Statistics and its interface. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision.Briefings in bioinformatics · 2021Article
- AIDE: annotation-assisted isoform discovery with high precision.Genome research · 2019Article
- OMGene: mutual improvement of gene models through optimisation of evolutionary conservation.BMC genomics · 2018Article
- Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq.PLoS computational biology · 2017Article
- Detecting circular RNAs: bioinformatic and experimental challenges.Nature reviews. Genetics · 2016Review
- A Unified Model for Joint Normalization and Differential Gene Expression Detection in RNA-Seq Data.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Ultra high-throughput sequencing of transcriptomes (RNA-Seq) has enabled the accurate estimation of gene expression at individual isoform level. However, systematic biases introduced during the sequencing and mapping processes as well as incompleteness of the transcript annotation databases may cause the estimates of isoform abundances to be unreliable, and in some cases, highly inaccurate. This paper introduces a penalized likelihood approach to detect and correct for such biases in a robust manner. Our model extends those previously proposed by introducing bias parameters for reads. An L1 penalty is used for the selection of non-zero bias parameters. We introduce an efficient algorithm for model fitting and analyze the statistical properties of the proposed model. Our experimental studies on both simulated and real datasets suggest that the model has the potential to improve isoform-specific gene expression estimates and identify incompletely annotated gene models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.