LymphoTrack® Software 

Overview

Reliable, purpose-built analysis software for identification of gene rearrangements and somatic hypermutation status

LymphoTrack Software is a companion bioinformatics solution developed to analyze next-generation sequencing (NGS) data generated by Invivoscribe’s LymphoTrack Assays.  Designed under ISO 13485 design controls, the software applies proprietary alignment and filtering algorithms to identify clonal rearrangements and provide information for the determination of somatic hypermutation status with high accuracy and reproducibility.

Since its first release for T-cell receptor gamma (TRG) analysis, the LymphoTrack brand has expanded to include assays for immunoglobulin heavy chain (IGH FR1/2/3 and Leader), kappa (IGK), and T-cell receptor beta (TRB) genes.  Modern versions of the software support the Illumina® MiSeq™ platform.

Frequently Asked Questions (FAQs) 

General Overview & Functionality

High-level understanding of what the software does and why it’s used

How Does the Software Work?

(Explains the workflow from FASTQ input to report generation)

LymphoTrack Software automatically processes paired, raw sequencing files (FASTQ.GZ) to:

  • Align reads to germline reference databases
  • Identify and group identical sequences in the Read Summary
  • Merge highly similar rearrangements in the Merged Read Summary
  • Calculate sequence frequencies and generate publication-ready reports (PDF and TSV outputs)

All sequences are presented in the forward (+) orientation, and rigorous quality filters ensure that only high-confidence reads contribute to clonality assessment.  Because of these strict quality standards, some reads may be filtered out if they fail alignment or quality thresholds.

Why Choose LymphoTrack?

(Outlines the core advantages and key features)

LymphoTrack Software streamlines analysis of B- and T-cell gene rearrangements, assisting with clonality detection and determining somatic hypermutation status from NGS data, delivering accurate, standardized, and reproducible results.  Optimized for Illumina® MiSeq™, it automates sequence demultiplexing, quality checks, and report generation, providing secure, user-friendly, and validated performance to support confident data interpretation.

Key Features

  •  Comprehensive analysis — Supports IGH, IGK, TRB, and TRG gene targets
  • Converts FASTQ data to annotated, visualized results
  • Generates both human-readable reports and machine-readable data tables
  • Rigorous quality filtering; ensures consistent, reproducible results across runs

Data Processing & Alignment Behavior

Focuses on how reads are processed, filtered, and reported

No.  Read counts represent a combination of plus and minus strand reads, all normalized to the + orientation.

Sequences may be excluded if they fail minimum quality thresholds or lack assignable V- or J-genes.  The Unique Reads output file provides confirmation for all reads that pass quality filters.

If there are very few or zero total reads analyzed according to the Read Summary, make sure the correct analysis mode, or target, is selected (i.e., Leader, IGH FR1, IGH FR2, IGH FR3, IGK, TRB or TRG) when running the LymphoTrack Software.  If there seems to be a lower number of total reads than expected, compare the size of the FASTQ files being analyzed with the size of the FASTQ files present on the MiSeq instrument.  If the MiSeq instrument has larger files, then re-transfer the sequence data to ensure analysis of the full dataset.

The MiSeq sequencer displays different messages when processing the sequencing data.  One message may state Sequencing Complete, and another may later state Analysis Complete.  Transferring the FASTQ data between these two messages may result in an incomplete analysis.

The LymphoTrack Software aligns the top 200 reads during analysis, but the Read Summary only reports sequencing reads that have aligned to a V- or J- gene found in the reference.  If a read cannot align to the reference, it is omitted from the Read Summary.

The reasons for a non-alignment to the reference are numerous, but usually focus on a problem with the sample, leading to a large amount of non-specific amplification to occur.  This event can stem from low numbers of target cells in the sample, improper PCR conditions, or low-quality sample types, such as fragmented FFPE.  To reduce the chance of these events, please follow the assay-specific Instructions for Use precisely.

To assign a read to a specific V- and/or J-gene, a minimum quality threshold must be attained during the alignment.  If the alignment is poor, a confident assignment cannot be made and is instead labeled None.   A read cannot be assigned None for both V- and J-genes, as these would not be reported.

Output Files & Interpretation

Describe specific output file types and how to interpret them

The answer varies depending which software version is being used:

  • +  The Merged Read Summary generated by LymphoTrack Software – MiSeq v2.4.x is a table that groups the top 10–500 sequences that differ by ≤ 2 nucleotides (in length or base composition), representing the same clonal rearrangement.
  •    +  
  • +  However, additional analysis parameters selected in LymphoTrack Software v3.0.x are applied during analysis and reflected in the resulting output files.  Thus, the Merged Read Summary output file provides the same type of data as compared to the previous software version output; however, the maximum mismatch allowance selected prior to analysis will be applied, merging sequences that differ by ≤ 0, 1, 2, or 3 nucleotides.

The “disappearing” read may have been merged with a read ranked above it, or it is possible the alignment of this read was exceptionally poor.  During the merging process, reads in the read summary are aligned with those in the unique reads file; however, reads in the read summary have been oriented to match the alignment to the reference and are possibly in the anti-sense orientation compared to the reference gene.  This happens only when the alignment is so poor and when a sense or anti-sense alignment is nearly equivalent, and the anti-sense alignment was slightly better. In cases such as these, it is best to ignore the read entirely. 

Any observed discordance can be attributed to minor differences in the reference database, alignment algorithms, and/or coding languages used. 

Performance & Runtime

Addresses questions about speed, resource usage and computational efficiency

The log file provides a breakdown of how long each step is taking. Following the line INFO: Decompressing files, there is another line that states how many files and how much time the decompression used. This number will be in milliseconds.  If decompression takes several hours, check if the target files are on a fileserver.  Typically, running any I/O intensive process like decompression over a network will be much slower.  If possible, copy the files over to the local computer, or decompress the files directly before running this software.  Verify that the compressed and decompressed files do not exist in the same folder; the software will not proceed if both FASTQ and FASTQ.GZ files are in the target folder.

If the subsequent parsing and analysis steps are taking a long time, the FASTQ files may be very large.  Examples of large FASTQ files would include when less than 24 indices are included on a single MiSeq run and as a result, the samples sequenced have a larger depth of coverage.  A second example would be if the library is unbalanced and contains a higher proportion of a sample with one index versus the proportion of samples with other indexes.  The predicted run-time stated in this IFU assumes a 24-index run with balanced libraries.

Quality Metrics & Run Evaluation

Helps users interpret sequencing quality and determine whether a run passed or failed

The run Q30 is calculated in real time during the base-calling process.  At this point, no other data processing has taken place, such as de-multiplexing and adapter trimming.  This means that any sequence from a poor quality index or occurring outside of the adapter sequence is contributing to the Q30 score.  Sequences found outside of the adapter sequence are typically low quality, and this scenario happens often with primer dimers.  If a library has a significant amount of primer dimers, this can cause a drop in Run Q30.  As a secondary check, the LymphoTrack Software output displays the index Q30 score as calculated from all trimmed reads in that index.  If an index Q30 score also fails the Illumina specification, consider that index to have failed. 

Troubleshooting & Best Practices

For information related to troubleshooting (error codes, system configuration, file permissions, etc.), click below.

LymphoTrack Software Troubleshooting Guide

Disclaimer

LymphoTrack Software is for RESEARCH USE ONLY (RUO);  not intended for diagnostic purposes.