Metagenomic Read Mapping Service¶
The Metagenomic Read Mapping Service uses KMA to align reads against antibiotic resistance genes, virulence factors, or other custom sets of genes.
Using the Metagenomic Read Mapping Service¶
The Metagenomic Read Mapping submenu option under the Services main menu (Metagenomics category) opens the Metagenomic Read Mapping Service input form (shown below). Note: You must be logged into PATRIC to use this service.
Metagenomic Read Mapping Service Menu
Metagenomic Read Mapping Service Input Form
Paired read library¶
Read File 1 & 2: Many paired read libraries are given as file pairs, with each file containing half of each read pair. Paired read files are expected to be sorted such that each read in a pair occurs in the same Nth position as its mate in their respective files. These files are specified as READ FILE 1 and READ FILE 2. For a given file pair, the selection of which file is READ 1 and which is READ 2 does not matter.
Single read library¶
Read File: FASTQ file containing reads.
Read files to be mapped.
Predefined Gene Set Name: A pre-built set of genes against which reads are mapped. Two options are available:
- CARD - Antibiotic resistence gene set from the Comprehensive Antibiotic Resistance Database
- VFDB - Virulence factor gene set from the Virulence Factor Database
Output Folder: Workspace folder where the results will be saved.
Output Name: User-provided name used to uniquely identify results.
Metagenomic Read Mapping Service Output Files
The Metagenomic Read Mapping Service generates several files that are deposited in the Private Workspace in the designated Output Folder. These include
- MetagenomicReadMappingReport.html - A web-browser-friendly report that summarizes the results of the service (see description and image below).
- kma.aln - The consensus alignment of the reads against their template.
- kma.frag.gz - Mapping information on each mapped read, columns are: read, number of equally well mapping templates, mapping score, start position, end position (w.r.t. template), the choosen template.
- kma.fsa - The consensus sequences drawn from the alignments.
- kma.res - A result overview giving the most common statistics for each mapped template.
- kma.mat.gz - Base counts on each position in each template, (only if “-matrix” is enabled).
Metagenomic Read Mapping Report Output¶
KMA Read Mapping Report
This page is a web-friendly report that summarizes the output of MKA. It provides a link to the input data, an interactive chart view (see description below), and a table of the reference genes mapped. The columns in the table are as follows:
- Template - Identifier of the template (reference gene) sequence that match the query reads. Clicking on any of the template identifiers in the first column will open a Specialty Gene List View that shows all the genes in PATRIC that have BLAT hits to the same template gene.
- Function - Template gene function.
- Genome: Genome that contains template gene. Clicking on the name in the Genome column will open a new tab that shows the Genome List view, which shows all the genomes in PATRIC that fall under the same taxonomy of the selected name.
- Score - Global alignment score of the template.
- Expected - Expected alignment score if all mapping reads where smeared over all templates in the database.
- Template_length - Template gene length in nucleotides.
- Template_Identity - Percent identity between the query and template sequence, over the length of the matching query sequence
- Template_Coverage - Percent of the template that is covered by the query
- Query_Identity - Percent identity between the query and template sequence, over the length of the matching query sequence
- Query_Coverage - Length of the matching query sequnce divided by the template length
- Depth - Number of times the template has been covered by the query.
- q_value - Quantile from McNemars test, to test whether the current template is a significant hit.
- p_value - p-vaue corresponding to the obtained q_value
- Kent, W. James. “BLAT—the BLAST-like alignment tool.” Genome research 12.4 (2002): 656-664.
- Jia, Baofeng, et al. “CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database.” Nucleic acids research (2016): gkw1004.
- Liu, Bo, et al. “VFDB 2019: a comparative pathogenomic platform with an interactive web interface.” Nucleic acids research 47.D1 (2018): D687-D692.
- Philip T.L.C. Clausen, Frank M. Aarestrup & Ole Lund, “Rapid and precise alignment of raw reads against redundant databases with KMA”, BMC Bioinformatics, 2018;19:307.