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

Niklas N, Hafenscher J, Barna A, Wiesinger K, Pröll J, Dreiseitl S, Preuner-Stix S, Valent P, Lion T, Gabriel C - BMC Res Notes (2015)

Bottom Line: 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.As a result the cFinder reports the connections of variants (haplotypes) with their readcount and relative occurrence (percentage).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.

View Article: PubMed Central - PubMed

Affiliation: Red Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. norbert.niklas@o.roteskreuz.at.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

Workflow for using cFinder. Sequencing data is aligned against a reference sequence by a user defined tool (blue) and result is loaded in sam or ace format (together with optional annotation information) into cFinder, where variant detection is accomplished and optional filtering can be performed. After selection of desired variants clones are automatically calculated and presented for further evaluation
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Fig1: Workflow for using cFinder. Sequencing data is aligned against a reference sequence by a user defined tool (blue) and result is loaded in sam or ace format (together with optional annotation information) into cFinder, where variant detection is accomplished and optional filtering can be performed. After selection of desired variants clones are automatically calculated and presented for further evaluation

Mentions: All tasks after the initial loading step run in linear time (target region size or coverage), the workflow is summarized in Fig. 1.Fig. 1


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

Niklas N, Hafenscher J, Barna A, Wiesinger K, Pröll J, Dreiseitl S, Preuner-Stix S, Valent P, Lion T, Gabriel C - BMC Res Notes (2015)

Workflow for using cFinder. Sequencing data is aligned against a reference sequence by a user defined tool (blue) and result is loaded in sam or ace format (together with optional annotation information) into cFinder, where variant detection is accomplished and optional filtering can be performed. After selection of desired variants clones are automatically calculated and presented for further evaluation
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4562109&req=5

Fig1: Workflow for using cFinder. Sequencing data is aligned against a reference sequence by a user defined tool (blue) and result is loaded in sam or ace format (together with optional annotation information) into cFinder, where variant detection is accomplished and optional filtering can be performed. After selection of desired variants clones are automatically calculated and presented for further evaluation
Mentions: All tasks after the initial loading step run in linear time (target region size or coverage), the workflow is summarized in Fig. 1.Fig. 1

Bottom Line: 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.As a result the cFinder reports the connections of variants (haplotypes) with their readcount and relative occurrence (percentage).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.

View Article: PubMed Central - PubMed

Affiliation: Red Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. norbert.niklas@o.roteskreuz.at.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus