Skip to main content
Advertisement

< Back to Article

Fig 1.

Overview of FlexTyper.

FlexTyper has three primary components: query generation, read indexing, and searching against the FM-index. Query generation includes the capacity to translate VCF files into query files given a reference genome file (e.g. Genome Fasta), or to directly create queries from fasta sequences including pathogen genome sequences. Modules VCF2Query.py and Fasta2Query.py facilitate this process. The second component involves creating an FM-index of the raw reads, after optional preprocessing steps. The third component searches the queries against the FM-index to produce output files with counts of query sequences within the query files.

More »

Fig 1 Expand

Fig 2.

Query Search Workflow.

Workflow for query search against the FM-index, starting with input queries and settings defined in Settings.ini file. In this figure, the example shows a centered search with ignoreNonUniqueKmers enabled. 1) K-mer generation has two modes centered search and sliding search. For a centered search, the position of interest lies in the middle of the query, and k-mers are designed to overlap that central position with defined length (k) and step (s). 2) If the ignore-duplicates option is set, k-mers collated from the query set are filtered to remove any k-mers which were found in multiple query sequences. 3) The filtered k-mers are then searched for within a single FM-index (left two panels) or multiple indexes (right two panels) of the read set. This can be done using single (top two panels) or multiple (bottom two panels) threads. 4) The results corresponding to a position within the FM-index are then translated back into reads, with hits on reverse complement reads assigned to the primary read, and collapsed into a set for each query. The final counts are reported per query.

More »

Fig 2 Expand

Fig 3.

Mixed Viral Analysis.

Detection of pathogen sequences in five synthetic patient RNA-seq datasets (Patient 1–5; rows), each with different levels of spiked-in viruses (EBV, HIV-1, U21941, and FR751039; columns), expected values shown as black vertical bars. As Centrifuge and Kraken2 are unable to delineate between the two HPV substrains (U21941 and FR751039), a combined count at the HPV level is tabulated.

More »

Fig 3 Expand

Fig 4.

WGS Genotyping using FlexTyper.

A) FlexTyper read count compared to the total coverage from BAM file over SNP sites represented on the CytoScanHD microarray. B) Histogram showing the delta, (Δ = FlexTyper—BamCoverage), in read count for both the alternate (red) and reference (blue) alleles. C) Histogram of the same delta as B) but with an extended axis from 100–2000, showing the frequency of over-counting for sites using FlexTyper. D) Scatter plot showing the delta (Δ = FlexTyper—BamCoverage) on the y-axis, plotted across chromosome 1 on the x-axis. E) Principal component analysis showing projection of FlexTyper-derived SNP genotypes from nine individuals of Asian (green), African (red) and European (purple) ancestry. Squares denote FlexTyper genotypes, points denote existing data from the 1000 Genomes project provided by Peddy. F) Sex-typing for these Polaris samples showing the ratio of heterozygous to homozygous sites on the X chromosome (y-axis) for individuals for the defined sexes as male (right) and female (left). Each individual is labeled as green (correctly sex-labeled) or red (incorrectly labeled).

More »

Fig 4 Expand

Fig 5.

Explorative uses of FlexTyper.

Two examples of the creative uses of FlexTyper within challenging regions. A) Density plots of counts for the African contigs for the children from the three populations (left to right AFR, EAS, EUR). B) Scatterplot comparing the African contig counts for the AFR child against the EUR child (pink) and the EAS child (teal). C) Heatmap in log-scale for population-specific contigs, clustered by sample similarity (columns) and contig count similarity (rows). D) Heatmap showing the log10 transform of the sum of k-mer counts per gene, with genes as rows, and samples as columns. The two alleles, KIR3DS1 and KIR3DL1 are labeled as rows on the left side. E) Overlayed histograms for the 9 samples, showing the frequency of the FlexTyper k-mer count for the KIR3DS1 allele. F) Overlayed histogram showing the frequency of the FlexTyper k-mer count for the KIR3DL1 allele.

More »

Fig 5 Expand