Search

We present a lightweight tool for clonotyping and measurable residual disease (MRD) assessment in monoclonal lymphoproliferative disorders. It is a translational method that enables computational detection of rearranged immunoglobulin heavy chain gene sequences. • The swigh-score clonotyping tool emphasizes parallelization and applicability across sequencing platforms. • The algorithm is based on an adaptation of the Smith-Waterman algorithm for local alignment of reads generated by 2nd and 3rd generation of sequencers.For method validation, we demonstrate the targeted sequences of immunoglobulin heavy chain genes from diagnostic bone marrow using serial dilutions of CD138+ plasma cells from a patient with multiple myeloma. Sequencing libraries from diagnostic samples were prepared for the three sequencing platforms, Ion S5 (Thermo Fisher Scientific), MiSeq (Illumina), and MinION (Oxford Nanopore), using the LymphoTrack assay. Basic quality filtering was performed, and a Smith-Waterman-based swigh-score algorithm was developed in shell and C for clonotyping and MRD assessment using FASTQ data files. Performance is demonstrated across the three different sequencing platforms.

Sequencing the exome is quickly becoming the preferred method for discovering disease-inducing mutations. While obtaining data sets is a straightforward procedure, the subsequent analysis and interpretation of the data is a limiting step for clinical applications. Thus, while the initial mutation and variant calling can be performed by a bioinformatician or trained researcher, the output from robust packages such as MuTect and GATK is not directly informative for the general life scientists. In attempt to obviate this problem we have created complementary Wolfram scripts, which enable easy downstream annotation and selection, presented here in the perspective of hematological relevance. It also provides the researcher with the opportunity to extend the analysis by having a full-fledged programming and analysis environment of Mathematica at hand. In brief, post-processing is performed by: • Mapping of germ line and somatic variants to coding regions, and defining variant sets within Mathematica. • Processing of variants in variant effect predictor. • Extended annotation, relevance scoring and defining focus areas through the provided functions.