cFinder: definition and quantification of multiple haplotypes in a mixed sample

BMC Research Notes

Christian Gabriel¹  Thomas Lion³  Peter Valent²  Sandra Preuner-Stix³  Stephan Dreiseitl⁴  Johannes Pröll¹  Karin Wiesinger¹  Agnes Barna¹  Julia Hafenscher¹  Norbert Niklas¹ 

[1] Red Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, Linz, 4017, Austria;Division of Hematology and Hemostaseology, Department of Medicine I, Ludwig Boltzmann Cluster Oncology, Medical University of Vienna, Vienna, Austria;Children’s Cancer Research Institute, Vienna, Austria;University of Applied Sciences Upper Austria, Softwarepark 11, Hagenberg, 4232, Austria

关键词: Software;    Next-generation sequencing;    Clone quantification;    Haplotype identification;    Mixed sample;   

Others  :  1230308
DOI  :  10.1186/s13104-015-1382-7

 received in 2014-07-11, accepted in 2015-08-24,  发布年份 2015

【 摘 要 】

Background

Next-generation sequencing allows for determining the genetic composition of a mixed sample. For instance, when performing resistance testing for BCR-ABL1 it is necessary to identify clones and define compound mutations; together with an exact quantification this may complement diagnosis and therapy decisions with additional information. Moreover, that applies not only to oncological issues but also determination of viral, bacterial or fungal infection. The efforts to retrieve multiple haplotypes (more than two) and proportion information from data with conventional software are difficult, cumbersome and demand multiple manual steps.

Results

Therefore, we developed a tool called cFinder that is capable of automatic detection of haplotypes and their accurate quantification within one sample. BCR-ABL1 samples containing multiple clones were used for testing and our cFinder could identify all previously found clones together with their abundance and even refine some results. Additionally, reads were simulated using GemSIM with multiple haplotypes, the detection was very close to linear (R ²  = 0.96). Our aim is not to deduce haploblocks over statistics, but to characterize one sample’s composition precisely. As a result the cFinder reports the connections of variants (haplotypes) with their readcount and relative occurrence (percentage). Download is available at http://sourceforge.net/projects/cfinder/.

Conclusions

Our cFinder is implemented in an efficient algorithm that can be run on a low-performance desktop computer. Furthermore, it considers paired-end information (if available) and is generally open for any current next-generation sequencing technology and alignment strategy. To our knowledge, this is the first software that enables researchers without extensive bioinformatic support to designate multiple haplotypes and how they constitute to a sample.

【 授权许可】

   
2015 Niklas et al.

【 图 表 】

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