Academic Journal
Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels
| Title: | Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels |
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| Authors: | Maria Zanti, Kyriaki Michailidou, Maria A. Loizidou, Christina Machattou, Panagiota Pirpa, Kyproula Christodoulou, George M. Spyrou, Kyriacos Kyriacou, Andreas Hadjisavvas |
| Source: | BMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021) |
| Publisher Information: | BMC, 2021. |
| Publication Year: | 2021 |
| Collection: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| Subject Terms: | Next-generation sequencing (NGS), Germline NGS data analysis, Variant calling, Alignment, Interval padding, Pipeline comparison, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| More Details: | Abstract Background Next-generation sequencing (NGS) represents a significant advancement in clinical genetics. However, its use creates several technical, data interpretation and management challenges. It is essential to follow a consistent data analysis pipeline to achieve the highest possible accuracy and avoid false variant calls. Herein, we aimed to compare the performance of twenty-eight combinations of NGS data analysis pipeline compartments, including short-read mapping (BWA-MEM, Bowtie2, Stampy), variant calling (GATK-HaplotypeCaller, GATK-UnifiedGenotyper, SAMtools) and interval padding (null, 50 bp, 100 bp) methods, along with a commercially available pipeline (BWA Enrichment, Illumina®). Fourteen germline DNA samples from breast cancer patients were sequenced using a targeted NGS panel approach and subjected to data analysis. Results We highlight that interval padding is required for the accurate detection of intronic variants including spliceogenic pathogenic variants (PVs). In addition, using nearly default parameters, the BWA Enrichment algorithm, failed to detect these spliceogenic PVs and a missense PV in the TP53 gene. We also recommend the BWA-MEM algorithm for sequence alignment, whereas variant calling should be performed using a combination of variant calling algorithms; GATK-HaplotypeCaller and SAMtools for the accurate detection of insertions/deletions and GATK-UnifiedGenotyper for the efficient detection of single nucleotide variant calls. Conclusions These findings have important implications towards the identification of clinically actionable variants through panel testing in a clinical laboratory setting, when dedicated bioinformatics personnel might not always be available. The results also reveal the necessity of improving the existing tools and/or at the same time developing new pipelines to generate more reliable and more consistent data. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1471-2105 |
| Relation: | https://doaj.org/toc/1471-2105 |
| DOI: | 10.1186/s12859-021-04144-1 |
| Access URL: | https://doaj.org/article/2504d4d34e724e00946dd853e8e06165 |
| Accession Number: | edsdoj.2504d4d34e724e00946dd853e8e06165 |
| Database: | Directory of Open Access Journals |
| ISSN: | 14712105 |
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| DOI: | 10.1186/s12859-021-04144-1 |
| Published in: | BMC Bioinformatics |
| Language: | English |