EBCall statistics

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Citations per year

Number of citations per year for the bioinformatics software tool EBCall
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Tool usage distribution map

This map represents all the scientific publications referring to EBCall per scientific context
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Protocols

EBCall specifications

Information


Unique identifier OMICS_00084
Name EBCall
Alternative name Empirical Baysian mutation Calling
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Target tumor sample, target normal sample and list of normal reference samples.
Input format BAM
Output data The position of the candidate mutation, the reference base for that position, he alternated sequence for the mutation candidate, sequencing depth for positive strand or both tumor and normal samples, the mismatch rates computed in the tumor and normal samples, the ratio of variant reads aligned to positive strand for the tumor and normal samples, sequencing depths for that position for the tumor and normal samples, he number of supporting variant read in the tumor and normal samples p-value, the minus logarithm of p-value of the EBCall for positive and negative strand, respectively, he minus logarithm of the p-value by Fisher's exact test and the estimated parameter values of Beta-Binominal sequencing model for that variant.
Operating system Unix/Linux
Programming languages C++, Perl, R, Shell (Bash)
Computer skills Advanced
Stability Stable
Requirements
samtools, The VGAM package for R
Maintained Yes

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Versioning


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Documentation


Maintainers


  • person_outline Satoru Miyano
  • person_outline Yuichi Shiraishi
  • person_outline Seishi Ogawa
  • person_outline EBCall Team

Publication for Empirical Baysian mutation Calling

EBCall citations

 (12)
library_books

A review of somatic single nucleotide variant calling algorithms for next generation sequencing data

2018
Comput Struct Biotechnol J
PMCID: 5852328
PMID: 29552334
DOI: 10.1016/j.csbj.2018.01.003

[…] iant callers abandon the diploidy assumption and model joint allele frequencies (fT,fN) instead of joint genotypes (GT,GN). The allele frequency analysis approach is taken by Strelka, MuTect, LoFreq, EBCall, deepSNV, LoLoPicker, and MuSE , , , , , , . Strelka's core algorithm consists of two steps. First, the posterior probabilities of VAFs in tumor and normal, noted as P(fT,fN|DT,DN), are estimat […]

library_books

Identification of Single Nucleotide Non coding Driver Mutations in Cancer

2018
Front Genet
PMCID: 5801294
PMID: 29456552
DOI: 10.3389/fgene.2018.00016

[…] en developed to identify somatic SNVs, including: (1) those that separately call SNVs in tumor and normal samples and then identify tumor-specific SNVs by comparison, such as GATK (), GATKcan (), and EBCall (); and (2) those that concurrently analyze tumor-normal samples using heuristic methods or statistical models, such as MuTect (), VarScan (, ), and Strelka () (Table ). While the first type of […]

library_books

Comprehensive benchmarking of SNV callers for highly admixed tumor data

2017
PLoS One
PMCID: 5636151
PMID: 29020110
DOI: 10.1371/journal.pone.0186175

[…] ify such germline cancer mutations may lead to imprecise treatment recommendations. MuTect should therefore be combined with a HaplotyperCaller analysis of the normal (germline) sample. Also Strelka, EBCall and QuadGT are reliable, but slightly less sensitive alternatives to MuTect for whole exome analyses. Targeted gene panel data exhibit higher coverage than exome data and should thus be used to […]

library_books

Variational inference for rare variant detection in deep, heterogeneous next generation sequencing data

2017
BMC Bioinformatics
PMCID: 5244592
PMID: 28103803
DOI: 10.1186/s12859-016-1451-5

[…] ncreasingly used to estimate unobserved quantities such as variant allele frequency given observed genomic sequencing data.GATK [] and SAMTools [] use a naive Bayesian decision rule to call variants. EBCall models sequencing errors based on a Beta-Binomial distribution, where the parameters and latent variables are estimated from a set of non-paired normal sequencing samples []. However, the error […]

library_books

Comprehensive mutational analysis of primary and relapse acute promyelocytic leukemia

2016
Leukemia
PMCID: 4972641
PMID: 27063598
DOI: 10.1038/leu.2016.69

[…] ide/bp_step.php?p=1), by performing Indel Realignment and Base Quality Recalibration. Minimum mapping quality of 15 was considered for variant calling. Somatic variants were called using two methods: ebCall and VarScan2 (version 2.3.8). Mutations supported by either <5 reads or those supported by reads in only one direction were excluded. Also, variants with variant allele frequencies <0.05 were d […]

library_books

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data

2016
PLoS One
PMCID: 4803342
PMID: 27002637
DOI: 10.1371/journal.pone.0151664

[…] encing relating to the question of necessity of validation of findings from exome sequencing studies. In studies based on exome sequencing only, typically with a relatively low coverage, we recommend EBCall and Virmid as they return very few calls that cannot be validated by targeted deep sequencing.In summary, our data reveals major differences among the nine studied somatic variant callers. EBCa […]


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EBCall institution(s)
Laboratory of DNA Information Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo, Minato-ku, Tokyo, Japan; Cancer Genomics Project, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Hematology/Oncology, Gunma Children’s Medical Center, Gunma, Japan

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