Mobile Genome Express (MGE): A comprehensive automatic genetic analyses pipeline with a mobile device

Abstract

The development of next-generation sequencing (NGS) technology allows to sequence whole exomes or genome. However, data analysis is still the biggest bottleneck for its wide implementation. Most laboratories still depend on manual procedures for data handling and analyses, which translates into a delay and decreased efficiency in the delivery of NGS results to doctors and patients. Thus, there is high demand for developing an automatic and an easy-to-use NGS data analyses system. We developed comprehensive, automatic genetic analyses controller named Mobile Genome Express (MGE) that works in smartphones or other mobile devices. MGE can handle all the steps for genetic analyses, such as: sample information submission, sequencing run quality check from the sequencer, secured data transfer and results review. We sequenced an Actrometrix control DNA containing multiple proven human mutations using a targeted sequencing panel, and the whole analysis was managed by MGE, and its data reviewing program called ELECTRO. All steps were processed automatically except for the final sequencing review procedure with ELECTRO to confirm mutations. The data analysis process was completed within several hours. We confirmed the mutations that we have identified were consistent with our previous results obtained by using multi-step, manual pipelines.

Fig 1. Workflow of MGE from sequencer to final result delivery.

(a) Users access to the Sequencing instrument (e.g. Ion Torrent PGM) by using MGE smartphone application, to select a sequencing run/s to analyze. Then users’ server accesses to the Sequencer and downloads the corresponding data as selected on the smartphone. (b) Automatically, the Sequencing machine sends the data to MGE database. Then, the MGE variant-calling tool runs. Next, the variant calling output data is ready for user can check the sample result with MGE review page, including the sample’s status and comments. After the reviewer curation, result is submitted. (c) Users can download the result in spreadsheet file from users’ server to their smartphone.

Fig 2. Sample submission form for analyzing sequencing data in MGE.

After the user access the sequencer with MGE smartphone application and selects the samples to be analyzed, the app will guide the user through to verify the data imported into the submission form. The data can be modified into MGE database if needed. (a) First page of the submission form. Because the users use their own panel and chip size, there are sections where they can fill-in the information about the samples, which gets inserted into MGE database. (b) The second page of the submission form is managed to get detailed experiment information such as DNA extraction method as well as DNA quantity and quality control method used (Nanodrop, Picogreen or qPCR). (c) Third page. The sample type information can also be recorded for further analysis and evaluation of sequencing data quality.

Fig 3. Review of sequencing data in ELECTRO (MGE).

(a) ELECTRO’s web interface, the MGE original sequencing data review web page. (b) Variant curation page. Important information is displayed per each variant. MGE reflects this information on final result screen on user’s smartphone and spreadsheet file. (c) Review of raw sequencing data on IGV plugin within the ELECTRO-MGE interface. Csm id: MGE own ID for a mutation; css id: MGE own ID for a sample; cosmic id: COSMIC ID; gene: Gene symbol (HGVS); CDS: CDS nomenclature of each variant; Amino Acid Change: amino acidic nomenclature of each variant; # of COSMIC samples: number of positive records of the variant in COSMIC database; # of mutation Reads: number of sequencing reads with variant allele; # of Wildtype reads: number of sequencing reads with reference allele; VAF: variant allele frequency; Report flag (true = 1): Present decision of a mutation, 1 = true mutation, 0 = false mutation; Homopolymer status: region within a homopolymer region (Y = yes, N = no); Location: genomic coordinates (chr#:start_nt) of the variant.

Fig 4. Example of sequencing results output from MGE.

MGE shows the sample results on its smartphone application. Users can check (a) comments from bioinformatics analyst, (b-c) mutation and coverage reports of the sample, and (d) quality matric PDF from PGM server. All these reports get generated automatically by a smartphone and MGE server. Users can also check the status of their samples analyzing progress on a smartphone. The server will update the messages depending on the status of the progress, such as: “Running”, “Coverage completed”, “Reviewing”, and “Analysis done”.