FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads

Abstract

We have developed a computational method that counts the frequencies of unique k-mers in FASTQ-formatted genome data and uses this information to infer the genotypes of known variants. FastGT can detect the variants in a 30x genome in less than 1 hour using ordinary low-cost server hardware. The overall concordance with the genotypes of two Illumina “Platinum” genomes is 99.96%, and the concordance with the genotypes of the Illumina HumanOmniExpress is 99.82%. Our method provides k-mer database that can be used for the simultaneous genotyping of approximately 30 million single nucleotide variants (SNVs), including >23,000 SNVs from Y chromosome. The source code of FastGT software is available at GitHub (https://github.com/bioinfo-ut/GenomeTester4/).

Alignment-free sequence comparison: benefits, applications, and tools

“…These genomic alterations are typically detected by genotype calling on mapped reads (e.g., Samtools mpileup [ 89 ] and GATK HaplotypeCaller [ 90 ]). However, alignment-free tools (FastGT [ 73 ] and LAVA [ 71 ]) allow for genotyping of known variants directly from next-generation sequencing data, based on k -mer analysis. Since these methods are 1–2 orders of magnitude faster than traditional mapping-based detection, they seem to be ideally suited for clinical applications, where sequencing data from a large number of individuals need to be processed in a timely manner.…”

Ak-mer-based method for the identification of phenotype-associated genomic biomarkers and predicting phenotypes of sequenced bacteria

“…‘PhenotypeSeeker prediction’ uses the regression model generated by ‘PhenotypeSeeker modeling’ to conduct fast phenotype predictions on input samples (Fig 1). Using gmer_counter from the FastGT package [17], the tool searches the samples only for the k -mers used as parameters in the regression model. Predictions are then made based on the presence or absence of these k -mers.…”

MALVA: genotyping by Mapping-free ALlele detection of known VAriants

“…More precisely, we will analyze whether the k-mers of a given signature are present in the reads and use such information as an hint of the presence of the allele. Unlike other approaches [27], Definition 2 admits the presence of the alleles of multiple variants in a single signature, allowing MALVA to manage variants that are not k-isolated. Indeed, the set of signatures of an allele represents all the genomic regions where the allele appears in the genomes encoded by the VCF file.…”

“…Their strategy is to create a dictionary for both the reference genome and the SNP list that maps each k-mer to the positions at which it appears, and then to call variants from the reads by evaluating k-mers frequency. FastGT [27] is yet another k-mer-based method to genotype sequencing data: it strongly relies on a pre-compiled database of bi-allelic SNVs and corresponding k-mers, obtained by subjecting the k-mers that overlap known SNVs to several filtering steps. Such filters remove from the database the SNPs for which unique k-mers (i.e., not occurring elsewhere in the reference genome) are not observed, those that are closely located (i.e., that are less than k bases apart), and others: after the filtering steps, only 64% of bi-allelic SNVs survive and are therefore identifiable.…”