Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples

Wagner, Günter P.; Kin, Koryu; Lynch, Vincent J.

doi:10.1007/s12064-012-0162-3

Cited by 1,799 publications

(1,447 citation statements)

References 7 publications

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“…In our analysis, we quantify RNA expression profiles from ENCODE Illumina sequencing 5 in terms of tpm (transcripts per million transcripts) based on the frequency of RNA sequencing (RNA-seq) reads mapped to a genomic feature 6 . The FANTOM5 data 7 is from CAGE (Cap Analysis Gene Expression) sequences and is quantified as tags per million, which is quantitatively equivalent to tpm based on Illumina RNA-seq.…”

Section: Resultsmentioning

confidence: 99%

The statistical geometry of transcriptome divergence in cell-type evolution and cancer

Liang

Forrest²,

Wagner

2015

Nat Commun

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In evolution, body plan complexity increases due to an increase in the number of individualized cell types. Yet, there is very little understanding of the mechanisms that produce this form of organismal complexity. One model for the origin of novel cell types is the sister cell-type model. According to this model, each cell type arises together with a sister cell type through specialization from an ancestral cell type. A key prediction of the sister cell-type model is that gene expression profiles of cell types exhibit tree structure. Here we present a statistical model for detecting tree structure in transcriptomic data and apply it to transcriptomes from ENCODE and FANTOM5. We show that transcriptomes of normal cells harbour substantial amounts of hierarchical structure. In contrast, cancer cell lines have less tree structure, suggesting that the emergence of cancer cells follows different principles from that of evolutionary cell-type origination.

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Section: Resultsmentioning

confidence: 99%

The statistical geometry of transcriptome divergence in cell-type evolution and cancer

Liang

Forrest²,

Wagner

2015

Nat Commun

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“…The number of reads in genes was counted using the program HTSeqcount (Anders et al 2015). The relative expression was then calculated as transcripts per million (TPM) (Wagner et al 2012). For comparison, differential expression analyses were conducted using DESeq2 package from Bioconductor (Gentleman et al 2004;Love et al 2014).…”

Section: Sequencing Of Complementary Dnas (Cdnas) (Rna-seq)mentioning

confidence: 99%

Regulation of Hyphal Growth and N-Acetylglucosamine Catabolism by Two Transcription Factors in Candida albicans

Naseem

Min

Spitzer³

et al. 2017

Genetics

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The amino sugar N-acetylglucosamine (GlcNAc) is increasingly recognized as an important signaling molecule in addition to its well-known structural roles at the cell surface. In the human fungal pathogen Candida albicans, GlcNAc stimulates several responses including the induction of the genes needed for its catabolism and a switch from budding to filamentous hyphal growth. We identified two genes needed for growth on GlcNAc (RON1 and NGS1) and found that mutants lacking these genes fail to induce the genes needed for GlcNAc catabolism. NGS1 was also important for growth on other sugars, such as maltose, but RON1 appeared to be specific for GlcNAc. Both mutants could grow on nonfermentable carbon sources indicating that they do not affect mitochondrial function, which we show is important for growth on GlcNAc but not for GlcNAc induction of hyphal morphogenesis. Interestingly, both the ron1D and ngs1D mutants were defective in forming hyphae in response to GlcNAc, even though GlcNAc catabolism is not required for induction of hyphal morphogenesis. The ron1D mutant showed a partial defect in forming hyphae, which was surprising since it displayed an elevated level of filamentous cells under noninducing conditions. The ron1D mutant also displayed an elevated basal level of expression of genes that are normally upregulated during hyphal growth. Consistent with this, Ron1 contains an Ndt80-like DNA-binding domain, indicating that it regulates gene expression. Thus, Ron1 is a key new component of the GlcNAc response pathway that acts as both an activator and a repressor of hyphal morphogenesis.

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“…The traditional R/FPKM 8, 9 (reads/fragments per kilobase per million reads) has been largely superseded by the TPM 10 (transcripts per million), since the latter is more consistent across libraries. Regardless, both of these units attempt to “correct for” sequencing depth and feature length and thus do not reflect the influence of these on quantification uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

2015

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High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Several different quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that while the presence of differential isoform usage can lead to inflated false discovery rates in differential expression analyses on simple count matrices and transcript-level abundance estimates improve the performance in simulated data, the difference is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

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Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples

Cited by 1,799 publications

References 7 publications

The statistical geometry of transcriptome divergence in cell-type evolution and cancer

The statistical geometry of transcriptome divergence in cell-type evolution and cancer

Regulation of Hyphal Growth and N-Acetylglucosamine Catabolism by Two Transcription Factors in Candida albicans

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

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