GenoStat Table of Contents

1. Introduction

2. Mixture resolution method

3. Cumulative statistics

4. Entering DNA profile data

5. Additional analysis parameters

Appendix


1. Introduction
GenoStat® is a powerful tool used to calculate DNA statistics and resolve DNA mixtures (separate mixtures into their contributor components). GenoStat has been written in Java to be able to be run on virtually any computer. To use GenoStat's statistics mode, simply check the allele boxes representing the DNA profile in your sample. To use GenoStat's mixture resolution mode,
enter the RFU values for the peaks found in a sample's electropherogram. The mathematically possible mixture separations (hypotheses) will be listed in the resolved mixtures area.


The default databases used by GenoStat are the FBI's "2015 Expanded FBI STR Population Data":

Hares, Douglas R. (2015), Selection and implementation of expanded CODIS core loci in the United States.Forensic Science International: Genetics, 17: 33-34. doi: 10.1016/j.fsigen.2015.03.006

Previous versions of the FBI databases as well as many additional population databases are bundled with GenoStat. Please see Appendix A.5 for further information.



2. Mixture resolution method
Samples containing DNA from two or more individuals can be difficult to interpret. Peak height information can be used as the basis of an automatable approach that objectively resolves the DNA profiles of contributors to mixed forensic samples. With this approach, all possible alternative combinations of genotypes that can account for the alleles at a given locus are evaluated for their ability to satisfy a set of two generally accepted constraints (peak height balance and peak height additivity). Hypothetical genotype combinations that are not eliminated from consideration can then be used to generate either a set of random match probabilities or a "constrained" combined probability of inclusion for the locus. This approach is unarguably objective as only information from the evidentiary sample is required for mixture resolution.

For each locus, our approach to mixture resolution postulates all possible genotype combinations and tests each for compliance with the predicted conditions that must be satisfied in order for that genotype combination to be acceptable. Consider the case of there being exactly two contributors to a mixed sample. The n peaks present at a given locus are ranked by height (or area) and labeled: P1, P2, … , Pn, where P1 is a peak of minimal height and Pn a peak of maximal height. All potential contributor genotype combinations are then listed. For example, at a locus with four peaks (labeled P1-P4) the possible set of genotypes for two individuals that could explain the observation of all four peaks are: [(P4, P3), (P2, P1)], [(P4, P2), (P3, P1)], and [(P4, P1), (P3, P2)]. The conditions that must be satisfied for each mixture combination pair are:

Contributor #1Contributor #2
Hypothesis #1P4 and P3P2 and P1
Hypothesis #2P4 and P2P3 and P1
Hypothesis #3P4 and P1P3 and P2

Each possible pairing of contributor genotypes represents a hypothesis that is tested for satisfiability against determined conditions of peak height balance and additivity. If either of the satisfiability conditions fail for a given hypothesis, that hypothesis is removed from further consideration. If all but one alternative hypothesis for a given locus has been eliminated from consideration, then the remaining hypothesis represents an unambiguously resolved genotype.



3. Cumulative statistics
The Cumulative statistics window forms the right side of the GenoStat screen. This area contains the results of the statistical calculations across all entered loci.

3.1 Locus selection
Statistics are only calculated for selected (checked) loci. The list of loci can be found on the right side of the GenoStat screen. Loci can be included or removed from generation of statistics by checking or unchecking the box next to the locus name. There are separate selection boxes for the random match probability (RMP) and combined probability of inclusion (CPI). Any profile can be included in the combined probability of inclusion (CPI) calculation, but only resolved loci (or loci with one selected mixture hypothesis) can be included in the random match probability (RMP) calculation.


3.2 Cumulative combined probability of inclusion (CPI)
The "unconstrained CPI" is the standard CPI formula, which includes all possible mixture contributor profiles for a given mixture profile. The "constrained" combined probability of inclusion (CPI) only considers the alternative hypotheses of genotype combinations that have not been eliminated from consideration. If a locus is fully resolved, then the "solved CPI" is reported. A full explanation of the statistical methods can be found in the
appendix.


3.3 Cumulative random match probability (RMP)
The cumulative random match probability is the random match probability (RMP) across all selected loci that have been fully resolved and/or loci with only a single mixture hypothesis selected.

The level of relatedness can be selected with the drop-down box located above the reported random match probabilities. The random match probability provides the chance that a randomly selected, unrelated individual would have a profile that matched that seen in a particular sample. GenoStat also provides estimates that a randomly selected related individual would have the same profile that was observed in a particular sample. Different degrees of relatedness result in different chances of finding a matching profile. GenoStat can generate statistical estimates for the following levels of relatedness: siblings; half-siblings; parents and children; aunts/uncles and nephews/nieces; first cousins; and second cousins. A full explanation of these formulas can be found in the
RMP appendix.


3.4 Cumulative mixture ratio
The cumulative mixture ratio is an approximation of the amount of DNA present from each contributor. The value is presented as [amount of contributor 1]:[amount of contributor 2]. The mixture ratio is determined by utilizing the peak height information from loci that are fully resolved or loci where only one mixture hypothesis has been selected.


3.5 Database selection
This version of GenoStat contains the three main databases published by the FBI: African American, Caucasian, and Southwest Hispanics. See Appendix for citations.

3.6 Minimum frequencies
For many tables included in Genostat, including the default tables, a minimum allele frequency ratio of 5/2N, where N is the number of individuals sampled, is enforced. This method was chosen in accordance with:

National Research Council. The Evaluation of Forensic DNA Evidence. Washington, DC: The National Academies Press, 1996. (freely available for download at
NAP.edu)



4. Entering DNA profile data
The left side of the GenoStat screen contains the areas where peak information is entered, loci are resolved, and locus statistics are shown.

4.1 Enter peak height information
Select one of the tested loci by selecting its tab along the top-left portion of the screen. Next, find the box corresponding to the first allele in the sample's electropherogram and enter its RFU value. Repeat the process for the remaining peaks in the locus.

Once all alleles for a given locus have been entered, click the button labeled
"Click here to resolve mixture."

NOTE: This version of GenoStat supports at most two contributors. Therefore, you cannot resolve a locus with more than four peaks.


4.1.1 Off-ladder alleles
GenoStat supports off-ladder alleles. Select on the button labeled "Off-ladder alleles" located under the allele entry boxes for a given locus. Here, you will be able to enter the allele's label and RFU value. To avoid any potential confusion, please ensure that the off-ladder allele's label is unique. Do not label an allele with the same label as an on-ladder allele and do not label two off-ladder alleles with the same name.


4.2. Mixture hypotheses
Once you have clicked the button labeled "Click here to resolve mixture", GenoStat will attempt to resolve the mixture. If a separation is mathematically possible, each possible set of contributor profiles (hypotheses) will be listed in the "resolved mixtures" box. If only one hypothesis is available, then the locus is fully resolved. If multiple hypotheses are available, then it is possible to remove a hypothesis from consideration by unchecking its "include" box (the box next to the hypothesis).

NOTE: A locus is only included in the random match probability (RMP) statistics if its RMP box is checked in the
main window and if the locus has only a single mixture hypothesis. If a locus is not fully resolved, you must deselect all but one mixture hypothesis for that locus to be included in the RMP statistics.


4.3 Locus statistics
The locus statistics window contains the
random match probabilities (RMPs) for the contributor profiles in each mixture hypothesis for a given locus. In addition, the combined probability of inclusion (CPI) is reported for the locus. The "unconstrained CPI" is the standard CPI formula, which includes all possible mixture contributor profiles for a given mixture profile. The "constrained CPI" . A "constrained" combined probability of inclusion (CPI) only considers the alternative hypotheses of genotype combinations that have not been eliminated from consideration. If a locus is fully resolved, then the "solved CPI" is reported. A full explanation of the statistical methods can be found in the appendix.



5. Additional analysis parameters

5.1 Minimum peak height threshold (MPHT)
When three or fewer alleles are observed at a particular locus, it is sometimes also possible that alleles possessed by one or both contributor are present at levels below the detection capability of the equipment used for genotyping (i.e., allelic dropout). The label MPHT is used to represent potential peaks below the minimum peak height threshold that may need to be considered in order to evaluate all possible contributor profiles.

The minimum peak height threshold (MPHT) is a user-defined parameter that represents the RFU threshold utilized during the course of the electronic analysis of the DNA data. GenoStat shares the Applied Biosystems' default minimum peak height threshold of 50 RFUs.


5.2 Peak height imbalance ratio (PHR)
Peak height balance demands that two peaks from the same contributor must have peak heights within a specific constant multiplier of each other. Thus, in order for a profile containing (P1, P2) to satisfy peak height balance, it must be true that:

P1/P2 ≥ PHR (where P1 ≤ P2)

for the specific value of PHR appropriate for the measurement technology used in analyzing the sample. General practice has found that, "[t]he peak height ratio, as measured by dividing the height of the lower quantity peak in relative fluorescence units by the height of the higher quantity allele peak, should be greater than approximately 70% in a single source sample" (Butler, 2001).


5.3 Magnitude-dependant peak height ratio (MD-PHR)
The extent to which two peaks are balanced varies with the magnitude of the peaks at a locus. As the magnitude of peaks increase, peak balance also tends to become greater (i.e., higher than 70%). Similarly, peak height balance ratios can fall below 70% for smaller peak pairs. Expected peak imbalance thresholds can be determined based on the average peak height of a contributor at a locus with the formula:

MD-PHR = 0.059 • ln(Ave peak height) + 0.36

This equation forms the 95% decision boundary for a validation study of 1763 heterozygous loci (manuscript forthcoming). The magnitude-dependant peak height ratio can be enabled with the checkbox on the main screen (MD-PHR).


Appendix

A1. Random Match Probability (RMP)
The random match probability (RMP) is a statistical estimate of the chance of finding a perfectly matching DNA profile in a randomly chosen, unrelated individual from a given population. The standard formula works by examining each locus individually as follows: Where p and q are the frequencies for the alleles observed in a given locus for a given population.

The total RMP for a sample is the multiplication of the above formula across all tested loci.


Related individuals
To calculate the random match probability among related individuals, the following formulas are used. Where F is the level of relatedness. F = 1/4 for parent and offspring, 1/8 for half-siblings, 1/8 for uncle and nephew, and 1/16 for first cousins.

The sibling match probability is calculated with the following formulas:


A2. Combined Probability of Inclusion (CPI)
The combined probability of inclusion (CPI) is the percentage of a given population that cannot be excluded from contributing to a given DNA profile. The combined probability of exclusion (CPE) is the percentage of a given population that cannot be included in a given DNA mixture. The CPE is simply (1 - CPI).

The combined probability of inclusion works by determining all of the potential contributors that could be present in a mixed sample. Consider the base case of a locus with two alleles (A, B). The following individuals could contribute to this mixture:

    A,A
    A,B
    B,A
    B,B

The chance of any of them contributing to the mixed sample is the summation of the probability of observing each contributor profile:


This is able to be reduced to: (A + B)2

The formula is easily expandable: Where A, B, C, A1, A2, ..., An are the frequencies for observing the given alleles in a given population.

The total CPI is the product of the CPI across all tested loci.


Constrained CPI
The standard CPI formula takes into account all possible contributors to a mixture. If the mixture resolution is even partially successful, some potential contributor profiles can be eliminated from consideration. The constrained CPI only takes into consideration the contributor profiles that are mathematically feasible.

Consider the following mixture: A, B, C with a resolution of: The standard CPI formula would be (A + B + C)2, which is the summation of all possible mixture profiles. For the constrained CPI, we can remove some of the potential profiles from consideration (such as B,B and A,C).

Therefore, the constrained CPI is (AA + 2BC + 2AB + CC)

As with the standard CPI, the total constrained CPI is the product of the unconstrained CPI across all loci.


Solved CPI
When a mixture has been fully resolved, the constrained CPI is said to be the solved CPI. The solved CPI only takes into consideration the resolved mixture contributor profiles.

Consider the following mixture: A, B, C with a resolution of: The solved CPI is (AA + 2BC). This is the same as adding the random match probability (RMP) values from the two contributor profiles.


A3. Statistical considerations for allelic dropout
Calculating a CPI with allelic dropout is problematic unless there is information regarding likely contributors. Therefore, the constrained CPI is able to evaluate specific hypotheses involving dropout to provide a statistic. Consider the case where one of a contributor's alleles has potentially dropped out. For example, consider the mixture hypothesis that contains the contributor profiles (A, A) and (B, MPHT). The statistical component of contributor two must include a correction for allelic dropout. As hypothesized, the missing allele is known to not be an A or a B. Therefore, all alleles other than A and B must be taken into consideration:


Consider a resolution that produces the set of potential contributor pairs including [(A, A), (B, B)], [(A, A), (A, B)], and [(A, A), (B, MPHT)]. The constrained CPI considers the genotypes (A, A), (B, B), (A, B), and the dropout formula developed above or:


When locus dropout is present, any statistical correction will likely result in a CPI of one. Therefore, a hypothesis of (MPHT, MPHT) will result in a CPI of one for that locus.



A4. Correction for population substructure (theta correction)
Populations can have different levels of substructure (inbreeding) that can cause a larger-than-expected number of homozygotes. Therefore, homozygotes are not as rare in highly structured populations and a correction can be performed. Theta values must be ≤ 1 and are typically chosen to be 0.01 or 0.03.

Theta correction for the Random Match Probability (RMP)
Theta correction for the Combined Probability of Inclusion (CPI)


A5. Database references
2015 errata and updates to the databases published by the FBI can be found in two articles. The article with reference "2015-1" is used as default in Genostat:

2015-1 - Hares, Douglas R. (2015), Selection and implementation of expanded CODIS core loci in the United States.Forensic Science International: Genetics, 17: 33-34. doi: 10.1016/j.fsigen.2015.03.006

2015-2 - Moretti, T. R., Budowle, B. and Buckleton, J. S. (2015), Erratum. Journal of Forensic Sciences, 60: 1114-1116. doi: 10.1111/1556-4029.12806

GenoStat® includes several additional databases that can be utilized. They are listed in the form population (reference). For example, the FBI Navajo database is listed as Navajo (2). The databases come from the OmniPop Excel spreadsheet found at
STRbase. Previous releases of Genostat used frequencies from (1) and (2) as default databases.

The additional database references are as follows:

1 - Population Data on the Thirteen CODIS Core Short Tandem Repeat Loci in African Americans, U.S. Caucasians, Hispanics, Bahamians, Jamaicans, and Trinidadians, JFS, 1999, 44, 1277-1286.

2 - CODIS STR Loci Data from 41 Sample Populations, JFS, 2001, 46(3), 453-489.

3 - Swiss Caucasian Population Data for 13 STR Loci Using AmpFlSTR Profiler Plus and Cofiler PCR Amplification Kits, Gehrig et.al, JFS, 1999, 44(5), 1035-1038.

4 - Allele Frequencies for Fourteen STR Loci of the PowerPlex 1.1 and 2.1 Multiplex Systems and Penta D Locus In Caucasians, African-Americans, Hispanics, and Other Populations of the United States of America and Brazil, Levedakou et.al, JFS, 2001, 46(3) 736-761.

5 - Allele Frequencies for the CODIS Core STR Loci in Connecticut Populations, Scherczinger et.al, J Forensic Sci, 2000, July (4), 938-940.

6 - Allele Frequencies of 13 Short Tandem Repeats in Population Samples From the Iberian Peninsula and Northern Africa, Perez-Lezaun et al., IJLM, 2000, 113, p208-214

7 - Turkish Population Data With the CODIS Multiplex Short Tandem Repeat Loci, Akbasak et al., FSI, 2001, 123, p227-229

8 - STR Data for the AmpFlSTR Profiler Plus and COfiler Loci From the Maghreb (North Africa), FSI, 2001, 122, 199-200

9 - Population Data of 13 STRs in Southern Spain (Andalusia), FSI, 2001, 119, 113-115

10 - Brazilian Population Database for the 13 STR Loci of the AmpFlSTR Profiler Plus and Cofiler Multiplex Kits, FSI, 2001, 118, 91-94

11 - 13 STR Loci Frequency Data from a Scottish Population, FSI, 2001, 116, 187-188

12 - Allele Frequencies for the PowerPlex 16 STR Loci in an Albanian Population Sample from Northern Italy, JFS, 2001, 46, 998-999

13 - Allele Frequencies for the 13 STR Loci and the D1S80 Locus in a Tamil Population from Madras, India, JFS, 2001, 46, 1515-1517

14 - ABI Profiler Plus / Cofiler Users Manuals

15 - Allele Frequencies for Nine STR Loci in African-Americans, Chines, Vietnamese, and Bangladesh Populations, JFS, 1999, p1316-1318

16 - Nine STR Markers Plus Amelogenin (AmpflSTR Profiler Plus): A Forensic Study In An Austrian Population, IJLM, 1999, 113, p60-62

17 - Spanish Population Data on Nine STR Loci, JFS, 2001, p1003-1004

18 - STR Data for the AmpFlSTR Profiler Plus Loci Among Golla Population of Southern Andhra Pradesh, India, JFS, 2001, p734-735

19 - Population Data for Nine Fluorescent Based STR Loci Among Four Important Tribal Populations of India, JFS, 2001, p184-188

20 - STR Data for the AMPFlSTR Profiler Plus Loci among Four Predominant Populations of Eastern India, JFS, 2000, p1353-1357

21 - Allele Frequencies for Nine STR Loci in African American and Caucasian Populations from Marion Count, Indiana, USA, JFS, 2000, p744-746

22 - Populations Genetics of Nine STR Loci in Two Populations from Brazil, JFS, 2000, p432-435

23 - Identifiler User Guide

24 - Allele Frequency Distributions for Nine STR Loci in the Japanese Population, JFS, 1999, p1319

25 - Maine Caucasian Population DNA Database Using Twelve Short Tandem Repeat Loci, JFS, 1999, p392-395

26 - Population Genetic Studies On The Tetrameric Short Tandem Repeat Loci D3S1358, VWA, FGA, D8S1179, D21S11, D18S51, D13S317, And D7S820 In Egypt, FSI, 1999, p23-31

27 - Portugese Population And Paternity Investigation Studies With A Multiplex PCR - The AmpFlSTR Profiler Plus, FSI, 2000, p31-37

28 - Allelic Distribution Of Nine Short Tandem Repeat (STR), HLA-DQA1, And Polymarker Loci In An Omani Sample Population, FSI, 2000, p81-85

29 - A Study On Ten Short Tandem Repeat Systems: African Immigration And Spanish Population Data, FSI, 2000, p167-177

30 - STR Data (AmpFlSTR Profiler Plus) From North Portugal, FSI, 2001, p119-121

31 - STR Data For 21 Loci In Northwest Africa, FSI, 2001, p41-51

32 - STR Data (AmpFlSTR Profiler Plus and GenePrint CTTv) From Mozambique, FSI, 2001, p131-133

33 - Allele Frequencies For Nine STR Loci In Beijing Chinese, FSI, 2001, p207-209

34 - STR Data For The AmpFlSTR Profiler Plus Loci From Majorcan, Minorcan And Valencian Populations (Eastern Spain), FSI, 2001, p201-204

35 - Population Data On The Nine STRs From Cantabria, A Mountainous Region In Northern Spain, FSI, 2001, p175-177

36 - STR Data For The AmpFlSTR Profiler Plus Loci From Macau (China), FSI, 2001, p74-75

37 - Data On Nine STR Loci Used For Forensic And Paternity Testing In The Greek Cypriot Population Of Cyprus, FSI, 2001, p225-226

38 - Population Data For 12 STR Loci In Hong Kong Chinese, IJLM, 2001, p281-284

39 - Evaluation And Application Of The AmpFlSTR Profiler Plus PCR Amplification Kit In A Bavarian Population Sample, IJLM, 2001, p278-280

40 - Significant Differences Between Yemenite and Egyptian STR Profiles and the Influence on Frequency Estimates in Arabs, IJLM, 2001, p211-214

41 - Genetic Diversity of Nine STRs in Two Northwest Iberian Populations: Galicia and Northern Portugal, IJLM, 2000, p109-113

42 - Forensic Validation of a Multiplex Containing Nine STRs - Population Genetics in Northern Poland, IJLM, 2000, p45-49

43 - A Korean Population Study of the Nine STR Loci FGA, VWA, D3S1358, D18S51, D21S11, D8S1179, D7S820, D13S317 and D5S818, IJLM, 2000, p41-44

44 - Genetic Variability at Nine STR Loci in the Chueta (Majorcan Jews) and the Balearic Populations Investigated by a Single Multiplex Reaction, IJLM, 2000, p263-267

45 - Database of Nine Tetrameric STR Loci - D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317 and D7S820 in Thai Population, FSI, 2001, p123-125

46 - Population Database For 9 STR's In 3 Populations, CAC Fall 1998

47 - STR Data for the PowerPlex 16 Loci in Buenos Aires Population (Agentina), JFS, 2002, p418-420

48 - Italian Population Data On Thirteen Short Tandem Repeat Loci: HUMTHO1, D21S11,D18S51, HUMVWFA31, HUMFIBRA, D8S1179, HUMTPOX, HUMCSF1PO, D16S539, D7S820, D13S317, D5S818, D3S1358, FSI, 1998, p53-60

49 - Genetic Variation at Nine Short Tandem Repeat Loci in Chamorros and Filipinos from Guam, Legal Medicine, 2000, p26-30

50 - Population Genetics of 15 STR Loci in the Population of Podlasie (NE Poland), FSI, 2001, p226-227

51 - Analysis of 13 Tetrameric Short Tandem Repeat Loci in a Population of Tuscany (Central Italy) Performed by Means of an Automated Infrared Sequencer, FSI, 2002, p83-85

52 - Jewish Population Genetic Data in 20 Polymorphic Loci, FSI, 2002, p52-58

53 - Genetic profile of the Madeira Archipelago population using the new Powerplex 16 System kit, FSI, 2002, p281-283

54 - Allele Frequencies for the 13 CODIS STR Loci in a Sample of Southern Croatians, JFS, 2002, p669-670

55 - Genetic variablility at 14 STR loci in the Puna population of north western Argentina, IJLM, 2002, p126-132

56 - RCMP/CFS (Canadian) STR frequency web site www.csfs.ca/databases

57 - STR data for the AmpFlSTR Profiler Plus loci from Greece, FSI, 2002, p265-266

58 - Polymorphism at fifteen hypervariable microsatellite loci in four populations of Maharashtra, India, FSI, 2002, p267-271

59 - Tunisian population data on 15 PCR-based loci, FSI, 2002, p272-274

60 - Population studies on three Native Alaska population groups using STR loci, FSI, 2002, p51-57

61 - Allele Frequency Data for Powerplex 16 Loci in Four Major Populations of Orissa, India, JFS, 2002, p912-915

62 - TheForensic Validation Studies of Profiler Plus and Allele Frequencies of Profiler Loci in a Polish Population, Progress in Forensic Genetics 8, 2000, p136-138

63 - Allele frequencies of the Profiler Plus STR loci in Canary Islands (Spain)/ Allele frequencies of the Profiler Plus STR loci in Canary Islands (Spain), Progress in Forensic Genetics 9, 2003, p95-103

64 - Allele Frequencies for 15 Autosomal STR Loci in U.S. Caucasian, African American, and Hispanic Populations, JFS, 2003, p908-911

65 - North Portugal Population Genetic Data For Nine STRs Loci, Progress in Forensic Genetics 8, 2000, p205-207

66 - Allele frequencies of STR multiplex systems in two portugese population samples, Progress in Forensic Genetics 8, 2000, p208-221

67 - Comparative analysis of STR data for Portugese spoken countries, Progress in Forensic Genetics 8, 2000, p212-214

68 - Allele Frequencies of 13 Loci in the Santa Catarina Population of Southern Brazil, JFS, 2003, p901-902

69 - African population data with AmpFlSTR Profiler Plus, Progress in Forensic Genetics 8, 2000, p230-232

70 - Genetic analysis of AmpFlSTR Profiler Plus Loci in Japanese, Progress in Forensic Genetics 8, 2000, p236-238

71 - Polymorphisms of 13 STR Markers in Chinese Population, Progress in Forensic Genetics 8, 2000, p242-244

72 - Genetic Study of 15 STR Loci Among Four Major Ethnic Groups of Bihar, India, JFS, 2002, p1139j-1142

73 - Allele Frequencies of CODIs STR Loci in Chinese Population, JFS, 2002, p1143-1144

80 - Genetic profile of a multi-ethnic population from Guine-Bissau (west Africa coast) using the new PowerPlex 16 System kit, FSI, 2002, p78-80

81 - Allele distribution on nine short tandem repeat loci for Turkish population: D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317, D7S820, FSI, 2002, p75-77

82 - Genetic profile of the Azores Archipelago population using the new PowerPlex 16 System kit, FSI, 2002, p68-71

83 - STR data for the PowerPlex 16 loci for the Chinese population in Hong Kong, FSI, 2002, p64-67

87 - Genetic Variation of the nine Profiler Plus loci in Russians, IJLM, 2002, p309-311

95 - Paraguayan Population Data on the Fifteen STR Loci Included in the POWERPLEX 16 Kit, JFS, 2003, 253-255

99 - Allele frequency data for 15 STR loci (AmpFlSTR SGM Plus and AmpFlSTR Profiler) in the Belgian population, Progress in Forensic Genetics 9, 2003, p219-222

118 - Allele frequencies for the 13 CODIS STR loci in Peru, FSI, 2003, p164-165

124 - Genetic profiling of a central Venezuelan population using 15 STR markers that may be of forensic importance, FSI, 2003, p99-101

126 - STR-CODIS typing in Greece, FSI, 2003, p104-106

155 - Population genetics of the 15 AmpFlSTR Identifiler loci in Kosovo Albanians, IJLM, 2004, p115-118

156 - Bosnian population data for the 15 STR loci in the Power Plex 16 kit, IJLM, 2004, p119-121

157 - Allele frequencies of the 15 AmpFlSTR Identifiler loci in the population of Vojvodina Province, Serbia and Montenegro, IJLM, 2004, 184-186

163 - Allele distribution of 15 STR loci in a population sample of Byelorussan minority residing in the northeastern Poland, FSI, 2004, 265-267

224 - Norwegian population data for 15 autosomal STR loci: PowerPlex 16, International Society of Forensic Genetics - 21st Congress, 9/13/05-917/05 (personal communication with Margurethe Stenersen)

225 - Kurdish (Iraq) and Somalian population data for 15 autosomal and 9 Y-chromosomal STR loci, Progress in Forensic Genetics 10, 2004, 185-187