2011
DOI: 10.1186/1471-2105-12-s10-s5
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Evaluation of the coverage and depth of transcriptome by RNA-Seq in chickens

Abstract: BackgroundRNA-Seq is the recently developed high-throughput sequencing technology for profiling the entire transcriptome in any organism. It has several major advantages over current hybridization-based approach such as microarrays. However, the cost per sample by RNA-Seq is still prohibitive for most laboratories. With continued improvement in sequence output, it would be cost-effective if multiple samples are multiplexed and sequenced in a single lane with sufficient transcriptome coverage. The objective of … Show more

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Cited by 97 publications
(91 citation statements)
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“…Our results are in general agreement with Wang et al (2011) that 30-40 million reads is sufficient to be technically precise in measuring gene expression for most genes, which is not surprising given the methods used. We and Wang et al (2011) used raw count data, rather than the ''fragments per kilobase of exon model per million mapped reads'' (FPKM) normalized data as implemented in the Cufflinks software others, 2010, 2012).…”
Section: Discussionsupporting
confidence: 80%
See 2 more Smart Citations
“…Our results are in general agreement with Wang et al (2011) that 30-40 million reads is sufficient to be technically precise in measuring gene expression for most genes, which is not surprising given the methods used. We and Wang et al (2011) used raw count data, rather than the ''fragments per kilobase of exon model per million mapped reads'' (FPKM) normalized data as implemented in the Cufflinks software others, 2010, 2012).…”
Section: Discussionsupporting
confidence: 80%
“…We and Wang et al (2011) used raw count data, rather than the ''fragments per kilobase of exon model per million mapped reads'' (FPKM) normalized data as implemented in the Cufflinks software others, 2010, 2012). The mathematical derivations necessary for sample size computation depend on using a valid model for the count data, a task that is tractable for the raw count data but would be much more difficult after the per-isoform scaling of FPKM.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…(ii) Sequencing efforts in the range of 5-20 M mapped reads per sample provide sufficient depth to accurately quantify gene expression across a broad range of expression levels in diverse eukaryotic transcriptomes (Tarazona et al 2011;Wang et al 2011;Hart et al 2013;Vijay et al 2013;Ching et al 2014;Liu et al 2014;Williams et al 2014). For example, Hart et al (2013) examined expression distributions for 127 RNAseq experiments (six replicated studies; human and zebrafish), finding that 10 M mapped reads were sufficient to cover approximately 90% of transcripts with >10 reads in a range of biosamples (cell lines, tissue/organ and population comparisons).…”
Section: More Sequence Is Not Necessarily Bettermentioning
confidence: 99%
“…2). Here, given the relatively low cost of sequencing, pilot work can be expanded to obtain~100 M paired-end reads (>100 bp), recommended in the current literature as sufficient to capture the majority of RNAs expressed in eukaryotic samples (Wang et al 2011;Francis et al 2013;Vijay et al 2013;Wolf 2013). …”
Section: Designing Better Rna-seq Experimentsmentioning
confidence: 99%