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Empirical Baysian mutation Calling EBCall

Detects somatic mutations. EBCall is a statistical framework using a massively parallel sequencing of the cancer genome and explicitly taking into account prior information of sequencing errors. The software is able to detect a series of somatic mutations that have allele frequencies of <10% with a high degree of accuracy, thereby identifying sub-clonal structures of cancer cells that cannot otherwise be found.

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EBCall classification

EBCall specifications

Software type:
Package/Module
Restrictions to use:
None
Input format:
BAM
Operating system:
Unix/Linux
Computer skills:
Advanced
Requirements:
samtools, The VGAM package for R
Interface:
Command line interface
Input data:
Target tumor sample, target normal sample and list of normal reference samples.
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.
Programming languages:
C++, Perl, R, Shell (Bash)
Stability:
Stable
Maintained:
Yes

EBCall distribution

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EBCall support

Documentation

Maintainers

  • Satoru Miyano <>
  • Yuichi Shiraishi <>
  • Seishi Ogawa <>
  • EBCall Team <>

Credits

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Publications

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

Link to literature

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