Table 1 Nex-StoCT II workgroup recommendations

General

Informaticians should be involved in all steps of informatics pipeline design, optimization and validation.

Primary analysis

Nex-StoCT I workgroup recommendations for test validation and quality-control procedures in primary analysis are published¹.

Secondary analysis

Laboratories should use the commercially available indexes and protocols recommended by the platform manufacturers if they can be optimized and validated for the intended clinical application (p. 19 of Supplementary Note).

Laboratories should use indexes that differ by more than a single base in the same reaction or lane (p. 20 of Supplementary Note).

Laboratories should discard reads with mismatched indexes (p. 21 of Supplementary Note).

Samples should be indexed as soon as possible and before targeted capture (p. 21 of Supplementary Note).

The fidelity of de-multiplexing should be assessed and validated to ensure the correct assignment of sequence reads to patient samples (p. 21 of Supplementary Note).

The assembly accession and version number should be documented for each alignment to enable traceability in both informatics workflow and result reporting (p. 24 of Supplementary Note).

Laboratories should evaluate a combination of aligners or the same aligner with different settings to effectively identify the types of variants targeted (p. 27 of Supplementary Note).

Laboratories should use the software's default settings initially and modify them (with validation) only when appropriate for the clinical application(s) (p. 28 of Supplementary Note).

Changes to default settings and subsequent optimization should be performed in consultation with an informatician (p. 28 of Supplementary Note).

Reads should be aligned to the reference assembly to minimize off-target or forced alignments, unless methods to ensure the optimal alignment to targeted regions of the genome have been developed (p. 30 of Supplementary Note).

More than one variant caller should be evaluated to identify the combination of settings and/or software able to detect the spectrum of variants targeted by the intended clinical application, and the suitability of a variant caller for the platform should be considered (pp. 35–36 of Supplementary Note).

Real and simulated data should be used for optimization of variant and genotype calling (p. 36 of Supplementary Note).

Simulated data should not be used in place of data derived from patient samples for optimization and validation of the informatics pipeline (p. 36 of Supplementary Note).

Well-characterized reference materials and tools such as those developed by the GeT-RM, the Genome in a Bottle Consortium and similar efforts should be used for test development, optimization and validation (pp. 36–37 of Supplementary Note).

Tertiary analysis and other considerations

The choice of annotation tools should be based on the types of sequence variants that need to be detected by the clinical test and on the strengths and limitations of the software used to detect particular variant types. Annotation and filtration tools should be integrated into the informatics pipeline to enable seamless automation and must be validated (pp. 40–41 of Supplementary Note).

Until reliable, medically curated databases are available, data used to annotate variants for clinical assessments should be carefully evaluated to ensure that they are supported by sufficient evidence (p. 42 of Supplementary Note).

Laboratory professionals should recognize differences in approaches to variant filtration and consider these in the design of the informatics pipeline (p. 43 of Supplementary Note).

Where possible, the laboratory should consider using more than one prediction program, with each taking a different approach to predicting pathogenicity (p. 45 of Supplementary Note).

Filtration algorithms should utilize databases containing reported pathogenic variants (for example, HGMD) to minimize the possibility of disease-associated variants being inappropriately filtered (p. 46 of Supplementary Note).

The methods selected for annotating a sequence must be evaluated to demonstrate that variant attributes are properly assigned (p. 46 of Supplementary Note).

A revision to a database or analysis algorithm used by a laboratory may affect the annotation process; consequently, the data analysis pipeline must be re-validated before the adoption of any updated data sources or software (p. 47 of Supplementary Note).

If Web-based tools are unable to provide version control, the software or data sets should be brought in-house so version changes can be documented (p. 47 of Supplementary Note).

Clinical assessment for disease association should be done by personnel with relevant clinical expertise. In some instances, this may be a collaborative activity undertaken by the laboratory professional and others (for instance, physicians, genetic counselors and/or informaticians) (p. 50 of Supplementary Note).

Laboratories should consider three essential questions when assessing variants that are identified during the annotation and prioritization process: first, whether the variant(s) disrupts the normal function of the gene; second, whether the variant(s) is associated with or predisposes a patient to a disease or has other health-related implications (for example, carrier status); and third, whether the variant(s) has relevance to the patient's clinical presentation and indication for testing (p. 51 of Supplementary Note).

Pathogenic variants and variants of uncertain significance should be reported for heritable conditions. Reporting of benign variants is not recommended (p. 52 of Supplementary Note).

The laboratory should establish strategies to reclassify or to monitor the reclassification of variants as new data become available to inform the analysis of findings (p. 52 of Supplementary Note).

The informatics pipeline must be re-validated before the adoption of any new, updated or re-optimized software or databases (p. 54 of Supplementary Note).

A new effort should be initiated to establish a 'clinical-grade' VCF or equivalent file-format specification to facilitate the interoperability of clinical laboratory and health information technology systems. This will facilitate data sharing among laboratories, with proficiency-testing programs for quality assurance, with databases that are used to support variant interpretation and for other purposes (the CDC established such a workgroup in 2013) (p. 57 of Supplementary Note).