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Microhaplotypes (MHs) consisting of multiple SNPs and indels on short stretches of DNA are new and interesting loci for forensic genetic investigations. In this study, we analysed 74 previously defined MHs in two of the populations that our laboratory provides with forensic genetic services, Danes and Greenlanders. In addition to the 229 SNPs that originally made up the 74 MHs, 66 SNPs and 3 indels were identified in the two populations, and 45 of these variants were included in new definitions of the MHs, whereas 24 SNPs were considered rare and of little value for case work. The average effective number of alleles (Ae) was 3.2, 3.0, and 2.6 in Danes, West Greenlanders, and East Greenlanders, respectively. High levels of linkage disequilibrium were observed in East Greenlanders, which reflects the characteristics of this population that has a small size, and signs of admixture and substructure. Pairwise kinship simulations of full siblings, half-siblings, first cousins, and unrelated individuals were performed using allele frequencies from MHs, STRs and SNPs from Danish and Greenlandic populations. The MH panel outperformed the currently used STR and SNP marker sets and was able to differentiate siblings from unrelated individuals with a 0% false positive rate and a 1.1% false negative rate using an LR threshold of 10,000 in the Danish population. However, the panel was not able to differentiate half-siblings or first cousins from unrelated individuals. The results generated in this study will be used to implement MHs as investigative markers for relationship testing in our laboratory

High throughput sequencing of multiplexed PCR amplicons with Short Tandem Repeats (STRs) requires software solutions that sort the information and allow a comprehensive overview of the results without overwhelming the data analyst with details. Here, we present an updated version (2.0) of the STR analysis tool STRinNGS. It is freely available as a Docker image or zip file ready for downloading. STRinNGS predicts genotypes using criteria for read depth, noise, flanking region lengths, mismatches in the flanking regions, locus balance, and heterozygote balance. Warning flags highlight suspicious genotypes as well as suspicious sequences that are not identified as either noise or alleles in the result table used for the manual analysis. STRinNGS analyses both the STR and the flanking regions, and names the alleles according to the STRidER guidelines as well as an in-house nomenclature that also include variants in the flanking regions. Furthermore, STRinNGS generates files with analysed data in a format that may be uploaded directly to the STRidER database. We re-analysed 627 sample files from eight different MiSeq FGx runs with STRinNGS v2.0. The samples were previously typed with the ForenSeq™ Signature Prep Kit and analysed with STRinNGS v1.0 and the Universal Analysis Software. Apart from three poorly performing loci with large heterozygote imbalances (Penta E and D22S1045) or frequent single nucleotide errors (DYS461), only 58 genotype calls (0.2 %) had to be manually corrected and only 14 genotype calls were discordant with the previous analyses. The discordant calls were primarily caused by manual oversights and in every case, the STRinNGS v2.0 analysis was correct.