title: Vindel: a simple pipeline for checking indel redundancy.
abstract: BACKGROUND
  With the advance of next generation sequencing (NGS) technologies, a large number of insertion and deletion (indel) variants have been identified in human populations. Despite much research into variant calling, it has been found that a non-negligible proportion of the identified indel variants might be false positives due to sequencing errors, artifacts caused by ambiguous alignments, and annotation errors.
  
  
  RESULTS
  In this paper, we examine indel redundancy in dbSNP, one of the central databases for indel variants, and develop a standalone computational pipeline, dubbed Vindel, to detect redundant indels. The pipeline first applies indel position information to form candidate redundant groups, then performs indel mutations to the reference genome to generate corresponding indel variant substrings. Finally the indel variant substrings in the same candidate redundant groups are compared in a pairwise fashion to identify redundant indels. We applied our pipeline to check for redundancy in the human indels in dbSNP. Our pipeline identified approximately 8% redundancy in insertion type indels, 12% in deletion type indels, and overall 10% for insertions and deletions combined. These numbers are largely consistent across all human autosomes. We also investigated indel size distribution and adjacent indel distance distribution for a better understanding of the mechanisms generating indel variants.
  
  
  CONCLUSIONS
  Vindel, a simple yet effective computational pipeline, can be used to check whether a set of indels are redundant with respect to those already in the database of interest such as NCBI's dbSNP. Of the approximately 5.9 million indels we examined, nearly 0.6 million are redundant, revealing a serious limitation in the current indel annotation. Statistics results prove the consistency of the pipeline on indel redundancy detection for all 22 chromosomes. Apart from the standalone Vindel pipeline, the indel redundancy check algorithm is also implemented in the web server http://bioinformatics.cs.vt.edu/zhanglab/indelRedundant.php .
authors.affiliation: Department of Computer Science, Virginia Tech, Blacksburg, VA, 24061, USA. zli04@vt.edu.
authors.forename: Zhiyi
authors.initials: Z
authors.lastname: Li
authors.affiliation: Department of Statistics, Virginia Tech, Blacksburg, VA, 24061, USA. xwwu@vt.edu.
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Wu
authors.affiliation: Department of Computer Science, Virginia Tech, Blacksburg, VA, 24061, USA. binhe@vt.edu.
authors.forename: Bin
authors.initials: B
authors.lastname: He
authors.affiliation: Department of Computer Science, Virginia Tech, Blacksburg, VA, 24061, USA. lqzhang@vt.edu.
authors.forename: Liqing
authors.initials: L
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D054643:INDEL Mutation; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software