SOAPindel: Efficient identification of indels from short paired reads

Abstract

We present a new approach to indel calling that explicitly exploits that indel differences between a reference and a se-quenced sample make the mapping of reads less efficient. We assign all unmapped reads with a mapped partner to their expected genomic positions and then perform extensive de novo assembly on the regions with many unmapped reads to resolve homozygous, heterozygous, and complex indels by exhaustive traversal of the de Bruijn graph. The method is implemented in the software SOAPindel and provides a list of candidate indels with quality scores. We compare SOAPindel to Dindel, Pindel, and GATK on simulated data and find similar or better performance for short indels (<10 bp) and higher sensitivity and specificity for long indels. A validation experiment suggests that SOAPindel has a false-positive rate of ~10% for long indels (>5 bp), while still providing many more candidate indels than other approaches. [Supplemental material is available for this article.] Calling indels from the mapping of short paired-end sequences to a reference genome is much more challenging than SNP calling because the indel by itself interferes with accurate mapping and therefore indels up to a few base pairs in size are allowed in the most popular mapping approaches (Li et al. 2008; Li and Durbin 2009; Li et al. 2009). The most powerful indel calling approach would be to perform de novo assembly of each genome and identify indels by alignment of genomes. However, this is compu-tationally daunting and requires very high sequencing coverage. Therefore, local approaches offer more promise. Recent approaches exploit the paired-end information to perform local realignment of poorly mapped pairs, thus allowing for longer indels (Ye et al. 2009; Homer and Nelson 2010; McKenna et al. 2010; Albers et al. 2011). One such approach, Dindel, maps reads to a set of candidate haplotypes obtained from mapping or from external information. It uses a probabilistic framework that naturally integrates various sources of sequencing errors and was found to have high specificity for identification of indels of sizes up to half the read length (Albers et al. 2011). Deletions longer than that can be called using split read approaches such as implemented in Pindel (Ye et al. 2009). Long insertions remain problematic because short reads will not span them and a certain amount of de novo assembly is required. Our approach, implemented in SOAPindel, performs full local de novo assembly of regions where reads appear to map poorly as indicated by an excess of paired-end reads where only one of the mates maps. The idea is to collect all unmapped reads at their expected genomic positions, then perform a local assembly of the regions with a high density of such reads and finally align these assemblies to the reference. A related idea has recently been published by Carnevali et al. (2012), but their approach is designed for a different sequencing method, and software is not available for comparison. While conceptually simple, our approach is sensitive to v...

GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly

“…Some methods apply targeted assembly to validate the breakpoint calls (e.g., Manta [Chen et al 2016], SVMerge [Wong et al 2010], TIGRA [Chen et al 2014]). Windowed breakpoint assembly has been used (e.g., SOAPindel [Li et al 2013], DISCOVAR [Weisenfeld et al 2014]), but detection is limited to events smaller than the window size. Whole-genome de novo assembly has also been used for variant calling (e.g., Cortex [Iqbal et al 2012]), but its use has been limited, in part due to the computational expense compared to alignment-based approaches.…”

Computational Errors and Biases in Short Read Next Generation Sequencing

“…represented, while long are underrepresented [86,87], thus creating an accuracy dependence on a homo-polymer length. Most typical error for the pyrosequencing-type technologies is also indel.…”

“…Identifying indels from NGS is known to be very challenging [87], because 'indel by itself interferes with accurate mapping' . To map indels accurately, Pair-End (PE) information is utilised [88].…”

Structural Variation Detection from Next Generation Sequencing

“…This method has been applied in the 1000 Genomes Project and provided high quality breakpoint information. In the literature, we have also found other packages adopting the local assembly method, shown in Table 1, such as BreaKmer [36], HYDRA [37], SOAPindel [38] and NovelSeq [39].…”