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Detection of internal exon deletion with exon Del.

Guo Y, Zhao S, Lehmann BD, Sheng Q, Shaver TM, Stricker TP, Pietenpol JA, Shyr Y - BMC Bioinformatics (2014)

Bottom Line: Such deletions have potentially significant biological meaning, and they are often too short to be considered copy number variation.Further comparisons with multiple sequencing-based CNV tools showed that ExonDel is capable of detecting unique IEDs not found by other CNV tools.ExonDel is an efficient way to screen for novel and known IEDs using exome sequencing data.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt Ingram Cancer Center, Center for Quantitative Sciences, 2220 Pierce Ave, 549 Preston Research Building, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu.

ABSTRACT

Background: Exome sequencing allows researchers to study the human genome in unprecedented detail. Among the many types of variants detectable through exome sequencing, one of the most over looked types of mutation is internal deletion of exons. Internal exon deletions are the absence of consecutive exons in a gene. Such deletions have potentially significant biological meaning, and they are often too short to be considered copy number variation. Therefore, to the need for efficient detection of such deletions using exome sequencing data exists.

Results: We present ExonDel, a tool specially designed to detect homozygous exon deletions efficiently. We tested ExonDel on exome sequencing data generated from 16 breast cancer cell lines and identified both novel and known IEDs. Subsequently, we verified our findings using RNAseq and PCR technologies. Further comparisons with multiple sequencing-based CNV tools showed that ExonDel is capable of detecting unique IEDs not found by other CNV tools.

Conclusions: ExonDel is an efficient way to screen for novel and known IEDs using exome sequencing data. ExonDel and its source code can be downloaded freely at https://github.com/slzhao/ExonDel.

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Related in: MedlinePlus

Using data from all 16 samples, we show that depth drops for exons with low and high GC content.
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Fig1: Using data from all 16 samples, we show that depth drops for exons with low and high GC content.

Mentions: The depth coverage of Illumina sequencing data can be influenced by GC content [7]. Many sequencing-based tools have taken the GC content’s effect on depth into consideration. We also observed similar bias based on analysis of exon depth (Figure 1). To minimize the effect of GC-content bias on depth, we applied standardization of depth by GC content followed by median correction, a method described in [8]. The GC content was adjusted by the following formula, where ri are the read counts of the ith exon, and mGC is the median read counts of all exons that have the same GC content as the ith exon. In Yoon et al.’s original implementation, ri is the read counts of the ith 100 bp window because copy number was under consideration instead of exons.Figure 1


Detection of internal exon deletion with exon Del.

Guo Y, Zhao S, Lehmann BD, Sheng Q, Shaver TM, Stricker TP, Pietenpol JA, Shyr Y - BMC Bioinformatics (2014)

Using data from all 16 samples, we show that depth drops for exons with low and high GC content.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4288651&req=5

Fig1: Using data from all 16 samples, we show that depth drops for exons with low and high GC content.
Mentions: The depth coverage of Illumina sequencing data can be influenced by GC content [7]. Many sequencing-based tools have taken the GC content’s effect on depth into consideration. We also observed similar bias based on analysis of exon depth (Figure 1). To minimize the effect of GC-content bias on depth, we applied standardization of depth by GC content followed by median correction, a method described in [8]. The GC content was adjusted by the following formula, where ri are the read counts of the ith exon, and mGC is the median read counts of all exons that have the same GC content as the ith exon. In Yoon et al.’s original implementation, ri is the read counts of the ith 100 bp window because copy number was under consideration instead of exons.Figure 1

Bottom Line: Such deletions have potentially significant biological meaning, and they are often too short to be considered copy number variation.Further comparisons with multiple sequencing-based CNV tools showed that ExonDel is capable of detecting unique IEDs not found by other CNV tools.ExonDel is an efficient way to screen for novel and known IEDs using exome sequencing data.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt Ingram Cancer Center, Center for Quantitative Sciences, 2220 Pierce Ave, 549 Preston Research Building, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu.

ABSTRACT

Background: Exome sequencing allows researchers to study the human genome in unprecedented detail. Among the many types of variants detectable through exome sequencing, one of the most over looked types of mutation is internal deletion of exons. Internal exon deletions are the absence of consecutive exons in a gene. Such deletions have potentially significant biological meaning, and they are often too short to be considered copy number variation. Therefore, to the need for efficient detection of such deletions using exome sequencing data exists.

Results: We present ExonDel, a tool specially designed to detect homozygous exon deletions efficiently. We tested ExonDel on exome sequencing data generated from 16 breast cancer cell lines and identified both novel and known IEDs. Subsequently, we verified our findings using RNAseq and PCR technologies. Further comparisons with multiple sequencing-based CNV tools showed that ExonDel is capable of detecting unique IEDs not found by other CNV tools.

Conclusions: ExonDel is an efficient way to screen for novel and known IEDs using exome sequencing data. ExonDel and its source code can be downloaded freely at https://github.com/slzhao/ExonDel.

Show MeSH
Related in: MedlinePlus