Evidence map›Paper›PMID 26346608›Full record

ArticleBMC research notes2015

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

Norbert Niklas, Julia Hafenscher, Agnes Barna, Karin Wiesinger, Johannes Pröll, Stephan Dreiseitl, Sandra Preuner-Stix, Peter Valent, Thomas Lion, Christian Gabriel

Abstract read
In one paragraph

Article in BMC research notes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. SorghumFDB: sorghum functional genomics database with multidimensional network analysis.Database : the journal of biological databases and curation · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Norbert NiklasRed Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. norbert.niklas@o.roteskreuz.at.
Julia HafenscherRed Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. jbhafenscher@gmail.com.
Agnes BarnaRed Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. agnes.barna@o.roteskreuz.at.
Karin WiesingerRed Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. karin.wiesinger@o.roteskreuz.at.
Johannes PröllRed Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. johannes.proell@o.roteskreuz.at.
Stephan DreiseitlUniversity of Applied Sciences Upper Austria, Softwarepark 11, 4232, Hagenberg, Austria. stephan.dreiseitl@fh-hagenberg.at.
Sandra Preuner-StixChildren's Cancer Research Institute, Vienna, Austria. sandra.preuner-stix@ccri.at.
Peter ValentDivision of Hematology and Hemostaseology, Department of Medicine I, Ludwig Boltzmann Cluster Oncology, Medical University of Vienna, Vienna, Austria. peter.valent@meduniwien.ac.at.
Thomas LionChildren's Cancer Research Institute, Vienna, Austria. thomas.lion@ccri.at.
Christian GabrielRed Cross Transfusion Service for Upper Austria, Krankenhausstraße 7, 4017, Linz, Austria. christian.gabriel@o.roteskreuz.at.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext-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.

resultsTherefore, 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/.

conclusionsOur 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.

Indexed as

AlgorithmsGenetic VariationComputational BiologyHaplotypesHumansReproducibility of ResultsSequence AlignmentSequence Analysis, DNASoftware

Identifiers

PMID26346608
PMCPMC4562109

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.