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chevron_left Driver mutation prioritization Quality control Variant visualization Genome viewers Quality control GWAS data visualization Gene visualization Interpretation Non-coding driver mutation detection Depth of coverage Read alignment visualization chevron_right
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BasePlayer specifications

Information


Unique identifier OMICS_17485
Name BasePlayer
Software type Application/Script
Interface Graphical user interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
License GNU Affero General Public License version 3
Computer skills Basic
Stability Stable
Source code URL https://codeload.github.com/rkataine/BasePlayer/zip/master
Maintained Yes

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Publications for BasePlayer

BasePlayer in pipelines

 (2)
2017
PMCID: 5397753
PMID: 28427458
DOI: 10.1186/s40246-017-0102-x

[…] short-indel variants were then called using gatk haplotypecaller., the snv and indel variants in the exome sequencing data were analyzed with an in-house developed analysis and visualization tool (baseplayer, katainen et al., manuscript in preparation). a minimum coverage of four reads and the mutated allele present in at least 20% of the reads was required to call a variant. the variants […]

2017
PMCID: 5673974
PMID: 29109480
DOI: 10.1038/s41598-017-15076-3

[…] as grch37 coordinates 22:29065455–29066124. to examine whether the novel candidate insertions were detected by wgs or not, we performed a thorough visual inspection of the paired-end read data using baseplayer., in order to compare ldi-pcr nanopore sequencing results to wgs data we performed local assembly of the wgs data. we selected those chimeric reads and discordant read pairs that aligned […]


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BasePlayer in publication

PMCID: 5871010
PMID: 29522538
DOI: 10.1371/journal.pgen.1007200

[…] step was done to exclude low allelic fraction artefacts in regions prone to sequencing errors. only variants within the targeted region of nimblegen seqcap ez exome library v3 kit were analyzed., baseplayer [] was utilized to visualize and analyze the data (allele frequency and quality filtering, allelic imbalance, gene annotation, and calculation of variant statistics). variant filtering […]


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BasePlayer institution(s)
Genome-Scale Biology Research Program, Research Programs Unit, University of Helsinki, Finland; Department of Medical and Clinical Genetics, Medicum, University of Helsinki, Finland; Department of Computer Science and Helsinki Institute for Information Technology, University of Helsinki, Finland
BasePlayer funding source(s)
This work was supported by grants from the Biomedicum Helsinki Foundation; Cancer Society of Finland; Emil Aaltonen Foundation; the Sigrid Juselius Foundation; Academy of Finland (Finnish Center of Excellence Program 2012–2017) [250345]; the European Research Council (ERC) [268648]; a European Union Framework Programme 7 Collaborative Project (SYSCOL) [258236]; the Nordic Information for Action eScience Center (NIASC); and a Nordic Center of Excellence financed by NordForsk [62721].

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