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RNA sequencing and transcriptome arrays analyses show opposing results for alternative splicing in patient derived samples

Overview of attention for article published in BMC Genomics, June 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

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Title
RNA sequencing and transcriptome arrays analyses show opposing results for alternative splicing in patient derived samples
Published in
BMC Genomics, June 2017
DOI 10.1186/s12864-017-3819-y
Pubmed ID
Authors

Petr V. Nazarov, Arnaud Muller, Tony Kaoma, Nathalie Nicot, Cristina Maximo, Philippe Birembaut, Nhan L. Tran, Gunnar Dittmar, Laurent Vallar

Abstract

RNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study. Both platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays. This reduced the number of differentially expressed genes and genes with predictive potential for RNA-seq compared to microarray data. Analysis of this variability revealed a lack of reads for short and low abundant genes; lncRNAs, being shorter and less abundant RNAs, were found especially susceptible to this issue. A major difference between the two platforms was uncovered by analysis of alternatively spliced genes. Investigation of differential exon abundance showed insufficient reads for many exons and exon junctions in RNA-seq while the detection on the array platform was more stable. Nevertheless, we identified 207 genes which undergo alternative splicing and were consistently detected by both techniques. Despite the fact that the results of gene expression analysis were highly consistent between Human Transcriptome Arrays and RNA-seq platforms, the analysis of alternative splicing produced discordant results. We concluded that modern microarrays can still outperform sequencing for standard analysis of gene expression in terms of reproducibility and cost.

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X Demographics

The data shown below were collected from the profiles of 63 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 113 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 27%
Researcher 16 14%
Student > Master 10 9%
Student > Bachelor 8 7%
Student > Postgraduate 6 5%
Other 16 14%
Unknown 27 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 27 24%
Agricultural and Biological Sciences 27 24%
Medicine and Dentistry 11 10%
Computer Science 8 7%
Immunology and Microbiology 3 3%
Other 4 4%
Unknown 33 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 45. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 May 2020.
All research outputs
#903,850
of 24,884,310 outputs
Outputs from BMC Genomics
#117
of 11,097 outputs
Outputs of similar age
#18,752
of 322,642 outputs
Outputs of similar age from BMC Genomics
#5
of 217 outputs
Altmetric has tracked 24,884,310 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,097 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 322,642 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 217 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.