Analysis of Short Tandem Repeat (STR) Massively Parallel Sequencing (MPS) Data
Block length of the missing motif.
Extract STR region information
Combined extract STR region information.
Combined extract STR region information.
Extract STR region information of the reverse complement DNA strand.
Find neighbours
Find neighbours
Find stutters
Find stutters
Genotype list
Assigns genotype.
Assigns genotype.
Idenfities the noise.
Idenfities the noise.
Identify the STR regions of a fastq-file or ShortReadQ-object.
Identify the STR regions of a fastq-file or ShortReadQ-object.
Control function for identifySTRRegions
Identify the STR regions of a fastq-file or ShortReadQ-object.
Merge genotypeIdentifiedList and stringCoverageList.
Merge genotypeIdentifiedList and stringCoverageList.
Merge noiseIdentifiedList and stringCoverageList.
Merge noiseIdentifiedList and stringCoverageList.
A neighbour list
Noise list
Quality score to probability
Convert probability to quality score
Get string coverage STR identified objects.
Get string coverage STR identified objects.
Get string coverage STR identified objects.
Get string coverage STR identified objects.
String coverage coontrol object
Get string coverage STR identified objects.
Combined stringCoverage- and genotypeIdentifiedList
A string coverage list
Combined stringCoverage- and noiseIdentifiedList
Workflow function
Batch wrapper for the workflow function
Collect stutters files
Workflow default options
Loading, identifying, aggregating, manipulating, and analysing short tandem repeat regions of massively parallel sequencing data in forensic genetics. 'STRMPS' can work with the package 'STRaitRazoR' (an R interface to the 'STRaitRazor' commandline tool) for added speed. 'STRaitRazoR' only works on linux and can found at <https://github.com/svilsen/STRaitRazoR>. The analyses and framework implemented in this package relies on the papers of Vilsen et al. (2017) <doi:10.1016/j.fsigen.2017.01.017> and Vilsen et al. (2018) <doi:10.1016/j.fsigen.2018.04.003>. Lastly, note that the parallelisation in the package relies on mclapply() and, thus, speed-ups will only be seen on UNIX based systems.