Data-based filtering for replicated high-throughput transcriptome sequencing experiments

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Data-based filtering for replicated high-throughput transcriptome sequencing experiments

MOTIVATION RNA sequencing is now widely performed to study differential expression among experimental conditions. As tests are performed on a large number of genes, stringent false-discovery rate control is required at the expense of detection power. Ad hoc filtering techniques are regularly used to moderate this correction by removing genes with low signal, with little attention paid to their ...

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HTSFilter: Independent data-based filtering for replicated transcriptome sequencing experiments

This vignette illustrates the use of the HTSFilter package to filter replicated data from transcriptome sequencing experiments (e.g., RNA sequencing data) for a variety of different data classes: matrix , data.frame, CountDataSet (the S4 class associated with the DESeq package), and the S3 classes associated with the edgeR package (DGEList , DGEExact , DGEGLM , and DGELRT ).

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HTSFilter: Data-based filtering for replicated transcriptome sequencing experiments

This vignette illustrates the use of the HTSFilter package to filter replicated data from transcriptome sequencing experiments (e.g., RNA sequencing data) for a variety of different data classes: matrix , data.frame, CountDataSet (the S4 class associated with the DESeq package), the S3 classes associated with the edgeR package (DGEList , DGEExact , DGEGLM , and DGELRT ), and the S4 class associ...

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Filtering data from high-throughput experiments based on measurement reliability.

In the context of the plethora of data currently generated in molecular biology, the paper by Bourgon et al. in PNAS (1) is pivotal, because it shows that an initial data filter can appropriately increase the detection power of a high-throughput experiment. Bourgon et al. (1) showed that filtering on overall variance outperforms filtering on overall mean, but they do not address two weaknesses ...

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Tools for mapping high-throughput sequencing data

MOTIVATION A ubiquitous and fundamental step in high-throughput sequencing analysis is the alignment (mapping) of the generated reads to a reference sequence. To accomplish this task, numerous software tools have been proposed. Determining the mappers that are most suitable for a specific application is not trivial. RESULTS This survey focuses on classifying mappers through a wide number of c...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2013

ISSN: 1460-2059,1367-4803

DOI: 10.1093/bioinformatics/btt350