A complete pipeline enables haplotyping and phasing macrohaplotype in long sequencing reads for polyploidy samples and a multi-source DNA mixture.

Macrohaplotype combines multiple types of phased DNA variants, increasing forensic discrimination power. High-quality long-sequencing reads, for example, PacBio HiFi reads, provide data to detect macrohaplotypes in multiploidy and DNA mixtures. However, the bioinformatics tools for detecting macrohaplotypes are lacking. In this study, we developed a bioinformatics software, MacroHapCaller, in which targeted loci (i.e., short TRs [STRs], single nucleotide polymorphisms, and insertion and deletions) are genotyped and combined with novel algorithms to call macrohaplotypes from long reads. MacroHapCaller uses physical phasing (i.e., read-backed phasing) to identify macrohaplotypes, and thus it can detect multi-allelic macrohaplotypes for a given sample. MacroHapCaller was validated with data generated from our designed targeted PacBio HiFi sequencing pipeline, which sequenced ∼8-kb amplicon regions harboring 20 core forensic STR loci in human benchmark samples HG002 and HG003. MacroHapCaller also was validated in whole-genome long-read sequencing data. Robust and accurate genotyping and phased macrohaplotypes were obtained with MacroHapCaller compared with the known ground truth. MacroHapCaller achieved a higher or consistent genotyping accuracy and faster speed than existing tools HipSTR and DeepVar. MacroHapCaller enables efficient macrohaplotype analysis from high-throughput sequencing data and supports applications using discriminating macrohaplotypes.

Análisis de 27 marcadores STR del cromosoma Y en poblaciones de la selva del Perú / Analysis of 27 STR markers of the chromosome Y in the population of the jungle from Peru

Introducción: los marcadores de repeticiones cortas en tándem del cromosoma Y (Y-STR) se ubican en la región no recombinante del cromosoma Y, su herencia es por vía paterna, no son detectables en el ADN femenino. Estas propiedades hacen de los Y-STR una herramienta útil en las investigaciones forenses, como las agresiones sexuales, paternidades y otros delitos violentos; asimismo son útiles en estudios genealógicos y evolutivos. El objetivo de la investigación es ampliar la evidencia científica de la distribución por regiones o país de los haplotipos del cromosoma sexual Y, estudios similares en poblaciones peruanas son escasas debido al número menor de polimorfismos Y-STR de uso frecuente en genética forense y de poblaciones. Material y métodos: en la investigación se analizaron 141 muestras de ADN de la selva del Perú, de las que 104 muestras corresponden a la región de Iquitos (Loreto), 29 muestras son Awajun (Amazonas) y 8 muestras de Tambopata (Madre de Dios). Las muestras fueron procesadas empleando PCR directa con el kit Yfiler™ Plus PCR Amplification para 27 STR, los productos amplificados fueron analizados por electroforesis capilar en el Applied Biosystem™ 3500XL Genetic Analyzer y los datos obtenidos se importaron al software GeneMapper® ID-X v1.5 para generar los perfiles genéticos. Con los resultados obtenidos se realizó el análisis estadístico y la estructura poblacional. Resultados: de las 141 muestras se obtuvieron 106 haplotipos únicos. La diversidad genética para cada marcador Y-STR estuvo entre 0,317 y 0,919. La diversidad haplotípica para la muestra total fue de 0,9906. El estudio registra que los haplotipos Y-STR estudiados presentaron elevado polimorfismo en la población analizada y, por lo tanto, son de gran utilidad en estudios forenses de identificación humana, así como en genética de poblaciones cuando se investigan grupos o individuos de América Latina. (AU)

Y-chromosome-specific short tandem repeat (Y-STR) markers reside on the non-recombinant portion of the Y chromosome, their inheritance is paternal, they are not detectable in female DNA. These properties make Y-STRs a useful tool in forensic investigations such as sexual assault, parenting, and other violent crimes; likewise they are also useful in genealogical and evolutionary studies. The objective of the research is to expand the scientific evidence of the distribution by region or country of the Y sex chromosome haplotypes. Similar studies in Peruvian populations are scarce due to the smaller number of Y-STR polymorphisms frequently used in Forensic and Population Genetics. Material and method: In the investigation, 141 DNA samples from the jungle of Peru were analyzed, of which comprised of 104 samples from Iquitos region (Loreto), 29 samples from Awajun (Amazonas) and 8 samples from Tambopata (Madre de Dios). The samples were processed using direct PCR with the Yfiler™ Plus PCR Amplification kit for 27 STRs, the amplified products were analyzed by capillary electrophoresis on the Applied Biosystem™ 3500XL Genetic Analyzer, and the data obtained was imported into the GeneMapper® ID-X v1.5 software to generate the genetic profiles. With the results obtained, the statistical analysis and the population structure were carried out. Results: Of the 141 samples, 106 unique haplotypes were observed. Gene diversities for each Y-STR marker ranged from 0.317 to 0.919. The haplotype diversity for the total sample was 0.9906. This study supports that the Y-STR haplotypes in this population are highly polymorphic in the analyzed population and, therefore, are very useful in forensic studies of human identification, as well as in population genetics when investigating groups or individuals from Latin America. (AU)

Unraveling crime scenes strand by strand: the forensic odyssey of Bruce Budowle.

Bruce Budowle speaks to Ashling Cannon, Journal Development Editor for BioTechniques, about advancements & challenges in forensic science. Budowle completed his doctorate in genetics at Virginia Tech (VA, USA) formally known as Virginia Polytechnic Institute and State University. He then went on to complete a postdoctoral fellowship at the University of Alabama at Birmingham (AL, USA) to study genetic risk factors for acute lymphocytic leukemia, diabetes and melanoma. Budowle was early in his career and hadn't spent much time in forensics at this stage, but in 1982 an advert caught his eye for a job with the FBI to develop genetic marker systems to identify people who have left biological evidence at crime scenes. Budowle spent 26 years with the FBI and helped develop a plethora of genetic analysis methods. In 1985, it became a reality that DNA could be a signature for identifying people, and there were huge developments in DNA forensic analysis. In 2009, Budowle moved into academia and went to the University of North Texas Health Science Center (TX, USA), eventually becoming the Director of the Center for Human Identification, where he oversaw missing person and traditional crime cases, taught students and carried out fundamental and applied research. Budowle feels incredibly lucky to have had the resources, opportunities and academic infrastructure to learn and develop his knowledge. Budowle recently retired from academia and now spends his time building capacity for DNA forensics applications in Africa through the Department of Justice, with a well-established program known as the International Criminal Investigative Training Assistance Program (ICITAP) as well as with the non-government organization (NGO) DNAforAfrica.

TRcaller: a novel tool for precise and ultrafast tandem repeat variant genotyping in massively parallel sequencing reads.

Calling tandem repeat (TR) variants from DNA sequences is of both theoretical and practical significance. Some bioinformatics tools have been developed for detecting or genotyping TRs. However, little study has been done to genotyping TR alleles from long-read sequencing data, and the accuracy of genotyping TR alleles from next-generation sequencing data still needs to be improved. Herein, a novel algorithm is described to retrieve TR regions from sequence alignment, and a software program TRcaller has been developed and integrated into a web portal to call TR alleles from both short- and long-read sequences, both whole genome and targeted sequences generated from multiple sequencing platforms. All TR alleles are genotyped as haplotypes and the robust alleles will be reported, even multiple alleles in a DNA mixture. TRcaller could provide substantially higher accuracy (>99% in 289 human individuals) in detecting TR alleles with magnitudes faster (e.g., ∼2 s for 300x human sequence data) than the mainstream software tools. The web portal preselected 119 TR loci from forensics, genealogy, and disease related TR loci. TRcaller is validated to be scalable in various applications, such as DNA forensics and disease diagnosis, which can be expanded into other fields like breeding programs. Availability: TRcaller is available at https://www.trcaller.com/SignIn.aspx.

A cost-benefit analysis for use of large SNP panels and high throughput typing for forensic investigative genetic genealogy.

Next-generation sequencing (NGS), also known as massively sequencing, enables large dense SNP panel analyses which generate the genetic component of forensic investigative genetic genealogy (FIGG). While the costs of implementing large SNP panel analyses into the laboratory system may seem high and daunting, the benefits of the technology may more than justify the investment. To determine if an infrastructural investment in public laboratories and using large SNP panel analyses would reap substantial benefits to society, a cost-benefit analysis (CBA) was performed. This CBA applied the logic that an increase of DNA profile uploads to a DNA database due to a sheer increase in number of markers and a greater sensitivity of detection afforded with NGS and a higher hit/association rate due to large SNP/kinship resolution and genealogy will increase investigative leads, will be more effective for identifying recidivists which in turn reduces future victims of crime, and will bring greater safety and security to communities. Analyses were performed for worst case/best case scenarios as well as by simulation sampling the range spaces with multiple input values simultaneously to generate best estimate summary statistics. This study shows that the benefits, both tangible and intangible, over the lifetime of an advanced database system would be huge and can be projected to be for less than $1 billion per year (over a 10-year period) investment can reap on average > $4.8 billion in tangible and intangible cost-benefits per year. More importantly, on average > 50,000 individuals need not become victims if FIGG were employed, assuming investigative associations generated were acted upon. The benefit to society is immense making the laboratory investment a nominal cost. The benefits likely are underestimated herein. There is latitude in the estimated costs, and even if they were doubled or tripled, there would still be substantial benefits gained with a FIGG-based approach. While the data used in this CBA are US centric (primarily because data were readily accessible), the model is generalizable and could be used by other jurisdictions to perform relevant and representative CBAs.

Multi intercalators FRET enhanced detection of minute amounts of DNA.

A novel approach is presented that increases sensitivity and specificity for detecting minimal traces of DNA in liquid and on solid samples. Förster Resonance Energy Transfer (FRET) from YOYO to Ethidium Bromide (EtBr) substantially increases the signal from DNA-bound EtBr highly enhancing sensitivity and specificity for DNA detection. The long fluorescence lifetime of the EtBr acceptor, when bound to DNA, allows for multi-pulse pumping with time gated (MPPTG) detection, which highly increases the detectable signal of DNA-bound EtBr. A straightforward spectra/image subtraction eliminates sample background and allows for a huge increase in the overall detection sensitivity. Using a combination of FRET and MPPTG detection an amount as small as 10 pg of DNA in a microliter sample can be detected without any additional sample purification/manipulation or use of amplification technologies. This amount of DNA is comparable to the DNA content of a one to two human cells. Such a detection method based on simple optics opens the potential for robust, highly sensitive DNA detection/imaging in the field, quick evaluation/sorting (i.e., triaging) of collected DNA samples, and can support various diagnostic assays.

Current Healthcare Systems in Light of Hyperendemic NCDs and the COVID-19 Pandemic: Time to Change.

Despite the significant achievements of current healthcare systems (CHCSs) in curing or treating several acute conditions, there has been far less success coping with noncommunicable diseases (NCDs), which have complex roots and nonconventional transmission vectors. Owing to the impact of the invisible hyperendemic NCDs and the COVID-19 pandemic, the limitations of CHCSs have been exposed. In contrast, the advent of omics-based technologies and big data science has raised global hope of curing or treating NCDs and improving overall healthcare outcomes. However, challenges related to their use and effectiveness must be addressed. Additionally, while such advancements intend to improve quality of life, they can also contribute the ever-increasing health disparity among vulnerable populations, such as low/middle-income populations, poorly educated people, gender-based violence victims, and minority and indigenous peoples, to name a few. Among five health determinants, the contribution of medical care to individual health does not exceed 11%. Therefore, it is time to implement a new well-being-oriented system complementary or parallel to CHCSs that incorporates all five health determinants to tackle NCDs and unforeseen diseases of the future, as well as to promote cost-effective, accessible, and sustainable healthy lifestyle choices that can reduce the current level of healthcare inequity.

MPKin-YSTR: Interpretation of Y chromosome STR haplotypes for missing persons cases.

Y chromosome Short Tandem Repeat (STR) haplotypes have been used in assisting forensic investigations primarily for identification and male lineage determination. The current SWGDAM interpretation guidelines for Y-STR typing provide helpful guidance on those purposes but do not address the issue of kinship analysis with Y-STR haplotypes. Because of the high mutation rate of Y-STRs, there are complex missing person cases in which inconsistent Y-STR haplotypes between true paternal lineage relatives will arise and cases with two or more male references in the same lineage and yet differ in their haplotypes. Therefore, more useful methods are needed for interpreting the Y-STR haplotype data. Computational methods and interpretation guidelines have been developed specifically addressing this issue, either using a mismatch-based counting method or a pedigree likelihood ratio method. In this study, a software program, MPKin-YSTR, was developed by implementing those more sophisticated methods. This software should be able to improve the interpretation of complex cases with Y-STR haplotype evidence. Thus, more biological evidence will be interpreted, which in turn will result in more investigation leads to help solve crimes.

Developmental validation of the ForenSeq MainstAY kit, MiSeq FGx sequencing system and ForenSeq Universal Analysis Software.

For human identification purposes, forensic genetics has primarily relied upon a core set of autosomal (and to a lesser extent Y chromosome) short tandem repeat (STR) markers that are enriched by amplification using the polymerase chain reaction (PCR) that are subsequently separated and detected using capillary electrophoresis (CE). While STR typing conducted in this manner is well-developed and robust, advances in molecular biology that have occurred over the last 15 years, in particular massively parallel sequencing (MPS) [1-7], offer certain advantages as compared to CE-based typing. First and foremost is the high throughput capacity of MPS. Current bench top high throughput sequencers enable larger batteries of markers to be multiplexed and multiple samples to be sequenced simultaneously (e.g., millions to billions of nucleotides can be sequenced in one run). Second, compared to the length-based CE approach, sequencing STRs increases discrimination power, enhances sensitivity of detection, reduces noise due to instrumentation, and improves mixture interpretation [4,8-23]. Third, since detection of STRs is based on sequence and not fluorescence, amplicons can be designed that are shorter in length and of similar lengths among loci, where possible, which can improve amplification efficiency and analysis of degraded samples. Lastly, MPS offers a single format approach that can be applied to analysis of a wide variety of genetic markers of forensic interest (e.g., STRs, mitochondrial DNA, single nucleotide polymorphisms, insertion/deletions). These features make MPS a desirable technology for casework [14,15,24,25-48]. The developmental validation of the ForenSeq MainstAY library preparation kit with the MiSeq FGx Sequencing System and ForenSeq Universal Software is reported here to assist with validation of this MPS system for casework [49]. The results show that the system is sensitive, accurate and precise, specific, and performs well with mixtures and mock case-type samples.

Revisiting informed consent in forensic genomics in light of current technologies and the times.

Informed consent is based on basic ethical principles that should be considered when conducting biomedical and behavioral research involving human subjects. These principles-respect, beneficence, and justice-form the foundations of informed consent which in itself is grounded on three fundamental elements: information, comprehension, and voluntary participation. While informed consent has focused on human subjects and research, the practice has been adopted willingly in the forensic science arena primarily to acquire reference samples from family members to assist in identifying missing persons. With advances in molecular biology technologies, data mining, and access to metadata, it is important to assess whether the past informed consent process and in particular associated risks are concomitant with these increased capabilities. Given the state-of-the-art, areas in which informed consent may need to be modified and augmented are as follows: reference samples from family members in missing persons or unidentified human remains cases; targeted analysis of an individual(s) during forensic genetic genealogy cases to reduce an investigative burden; donors who provide their samples for validation studies (to include population studies and entry into databases that would be applied to forensic statistical calculations) to support implementation of procedures and operations of the forensic laboratory; family members that may contribute samples or obtain genetic information from a molecular autopsy; and use of medical and other acquired samples that could be informative for identification purposes. The informed consent process should cover (1) purpose for collection of samples; (2) process to analyze the samples (to include type of data); (3) benefits (to donor, target, family, community, etc. as applicable); (4) risks (to donor, target, family, community, etc. as applicable); (5) access to data/reports by the donor; (6) sample disposition; (7) removal of data process (i.e., expungement); (8) process to ask questions/assessment of comprehension; (9) follow-up processes; and (10) voluntary, signed, and dated consent. Issues surrounding these topics are discussed with an emphasis on addressing risk factors. Addressing informed consent will allow human subjects to make decisions voluntarily and with autonomy as well as secure the use of samples for intended use.

USAT: a bioinformatic toolkit to facilitate interpretation and comparative visualization of tandem repeat sequences.

BACKGROUND: Tandem repeats (TR), highly variable genomic variants, are widely used in individual identification, disease diagnostics, and evolutionary studies. The recent advances in sequencing technologies and bioinformatic tools facilitate calling TR haplotypes genome widely. Both length-based and sequence-based TR alleles are used in different applications. However, sequence-based TR alleles could provide the highest precision in characterizing TR haplotypes. The need to identify the differences at the single nucleotide level between or among TR haplotypes with an easy-use bioinformatic tool is essential. RESULTS: In this study, we developed a Universal STR Allele Toolkit (USAT) for TR haplotype analysis, which takes TR haplotype output from existing tools to perform allele size conversion, sequence comparison of haplotypes, figure plotting, comparison for allele distribution, and interactive visualization. An exemplary application of USAT for analysis of the CODIS core STR loci for DNA forensics with benchmarking human individuals demonstrated the capabilities of USAT. USAT has user-friendly graphic interfaces and runs fast in major computing operating systems with parallel computing enabled. CONCLUSION: USAT is a user-friendly bioinformatics software for interpretation, visualization, and comparisons of TRs.

Medicine and health of 21st Century: Not just a high biotech-driven solution.

Many biotechnological innovations have shaped the contemporary healthcare system (CHS) with significant progress to treat or cure several acute conditions and diseases of known causes (particularly infectious, trauma). Some have been successful while others have created additional health care challenges. For example, a reliance on drugs has not been a panacea to meet the challenges related to multifactorial noncommunicable diseases (NCDs)-the main health burden of the 21st century. In contrast, the advent of omics-based and big data technologies has raised global hope to predict, treat, and/or cure NCDs, effectively fight even the current COVID-19 pandemic, and improve overall healthcare outcomes. Although this digital revolution has introduced extensive changes on all aspects of contemporary society, economy, firms, job market, and healthcare management, it is facing and will face several intrinsic and extrinsic challenges, impacting precision medicine implementation, costs, possible outcomes, and managing expectations. With all of biotechnology's exciting promises, biological systems' complexity, unfortunately, continues to be underestimated since it cannot readily be compartmentalized as an independent and segregated set of problems, and therefore is, in a number of situations, not readily mimicable by the current algorithm-building proficiency tools. Although the potential of biotechnology is motivating, we should not lose sight of approaches that may not seem as glamorous but can have large impacts on the healthcare of many and across disparate population groups. A balanced approach of "omics and big data" solution in CHS along with a large scale, simpler, and suitable strategies should be defined with expectations properly managed.

A machine learning approach for missing persons cases with high genotyping errors.

Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship.ip estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.

Optimized variant calling for estimating kinship.

One of the fundamental goals of forensic genetics is sample attribution, i.e., whether an item of evidence can be associated with some person or persons. The most common scenario involves a direct comparison, e.g., between DNA profiles from an evidentiary item and a sample collected from a person of interest. Less common is an indirect comparison in which kinship is used to potentially identify the source of the evidence. Because of the sheer amount of information lost in the hereditary process for comparison purposes, sampling a limited set of loci may not provide enough resolution to accurately resolve a relationship. Instead, whole genome techniques can sample the entirety of the genome or a sufficiently large portion of the genome and as such they may effect better relationship determinations. While relatively common in other areas of study, whole genome techniques have only begun to be explored in the forensic sciences. As such, bioinformatic pipelines are introduced for estimating kinship by massively parallel sequencing of whole genomes using approaches adapted from the medical and population genomic literature. The pipelines are designed to characterize a person's entire genome, not just some set of targeted markers. Two different variant callers are considered, contrasting a classical variant calling algorithm (BCFtools) to a more modern deep convolution neural network (DeepVariant). Two different bioinformatic pipelines specific to each variant caller are introduced and evaluated in a titration series. Filters and thresholds are then optimized specifically for the purposes of estimating kinship as determined by the KING-robust algorithm. With the appropriate filtering and thresholds in place both tools perform similarly, with DeepVariant tending to produce more accurate genotypes, though the resultant types of inaccuracies tended to produce slightly less accurate overall estimates of relatedness.

Maleficent Comrades: War in Ukraine and COVID-19.

Infectious diseases and war are maleficent comrades. This reality applies equally well to the war in Ukraine and the current coronavirus disease 2019 (COVID-19) pandemic. Europe is facing a huge refugee crisis and potentially the conflict could worsen the COVID-19 pandemic. Initially, 2 major countries of concern are Poland, which has taken the majority of refugees, and Moldova, which has taken a very large number of refugees on a per capita basis. However, the concern extends to the rest of Europe because of the mobility of refugees beyond the first country they enter. Vaccinating, infection control, and boosting refugees should be a priority. However, complete prevention of COVID-19 is very complex because of other issues related to the success of prevention.

A prospective cost-benefit analysis for nylon 4N6FLOQSwabs®: example of the process and potential benefits.

Laboratories and their criminal justice systems are confronted with challenges for implementing new technologies, practices, and policies even when there appears to be demonstrative benefits to operational performance. Impacting decisions are the often higher costs associated with, for example, new technologies, limited current budgets, and making hard decisions on what to sacrifice to take on the seemingly better approach. A prospective cost-benefit analysis (CBA) could help an agency better formulate its strategies and plans and more importantly delineate how a relatively small increase to take on, for example, a new technology can have large impact on the system (e.g., the agency, other agencies, victims and families, and taxpayers). To demonstrate the process and potential value a CBA was performed on the use of an alternate and more expensive swab with reported better DNA yield and being certified human DNA free (i.e., nylon 4N6FLOQSwabs®), versus the traditional less costly swab (i.e., cotton swab). Assumptions are described, potential underestimates and overestimates noted, different values applied (for low and modest to high), and potential benefits (monetary and qualitative) presented. The overall outcome is that the cost of using the more expensive technology pales compared with the potential tangible and intangible benefits. This approach could be a guide for laboratories (and associated criminal justice systems) worldwide to support increased funding, although the costs and benefits may vary locally and for different technologies, practices, and policies. With well-developed CBAs, goals of providing the best services to support the criminal justice system and society can be attained.

Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples.

Technological advances in sequencing and single nucleotide polymorphism (SNP) genotyping microarray technology have facilitated advances in forensic analysis beyond short tandem repeat (STR) profiling, enabling the identification of unknown DNA samples and distant relationships. Forensic genetic genealogy (FGG) has facilitated the identification of distant relatives of both unidentified remains and unknown donors of crime scene DNA, invigorating the use of biological samples to resolve open cases. Forensic samples are often degraded or contain only trace amounts of DNA. In this study, the accuracy of genome-wide relatedness methods and identity by descent (IBD) segment approaches was evaluated in the presence of challenges commonly encountered with forensic data: missing data and genotyping error. Pedigree whole-genome simulations were used to estimate the genotypes of thousands of individuals with known relationships using multiple populations with different biogeographic ancestral origins. Simulations were also performed with varying error rates and types. Using these data, the performance of different methods for quantifying relatedness was benchmarked across these scenarios. When the genotyping error was low (<1%), IBD segment methods outperformed genome-wide relatedness methods for close relationships and are more accurate at distant relationship inference. However, with an increasing genotyping error (1-5%), methods that do not rely on IBD segment detection are more robust and outperform IBD segment methods. The reduced call rate had little impact on either class of methods. These results have implications for the use of dense SNP data in forensic genomics for distant kinship analysis and FGG, especially when the sample quality is low.

Techniques for estimating genetically variable peptides and semi-continuous likelihoods from massively parallel sequencing data.

Forensic genetic investigations typically rely on analysis of DNA for attribution purposes. There are times, however, when the amount and/or the quality of the DNA is limited, and thus little or no information can be obtained regarding the source of the sample. An alternative biochemical target that also contains genetic signatures is protein. One class of genetic signatures is protein polymorphisms that are a direct consequence of simple/single/short nucleotide polymorphisms (SNPs) in DNA. However, to interpret protein polymorphisms in a forensic context, certain complexities must be understood and addressed. These complexities include: 1) SNPs can generate 0, 1, or arbitrarily many polymorphisms in a polypeptide; and 2) as an object of expression that is modulated by alleles, genes and interactions with the environment, proteins may be present or absent in a given sample. To address these issues, a novel approach was taken to generate the expected protein alleles in a reference sample based on whole genome (or exome) sequence data and assess the significance of the evidence using a haplotype-based semi-continuous likelihood algorithm that leverages whole proteome data. Converting the genomic information into the proteomic information allows for the zero-to-many relationship between SNPs and GVPs to be abstracted away. When viewed as a haplotype, many GVPs that correspond to the same SNP is equivalent to many SNPs in perfect linkage disequilibrium (LD). As long as the likelihood formulation correctly accounts for LD, the correspondence between the SNP and the proteome can be safely neglected. Tests were performed on simulated samples, including single-source and two-person mixtures, and the power of using a classical semi-continuous likelihood versus one that has been adapted to neglect drop-out was compared. Additionally, summary statistics and a rudimentary set of decision guidelines were introduced to help identify mixtures from protein data.