PyPop: a mature open-source software pipeline for population genomics.

Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data. In particular, PyPop tests data conformity to Hardy-Weinberg equilibrium expectations, performs Ewens-Watterson tests for selection, estimates haplotype frequencies, measures linkage disequilibrium, and tests significance. Standardized means of performing these tests is key for contemporary studies of evolutionary biology and population genetics, and these tests are central to genetic studies of disease association as well. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index. New features include implementation of the asymmetric linkage disequilibrium measures and, of particular interest to the immunogenetics research communities, support for modern nomenclature, including colon-delimited allele names, and improvements to meta-analysis features for aggregating outputs for multiple populations. Code available at: https://zenodo.org/records/10080668 and https://github.com/alexlancaster/pypop.

Comparison between qPCR and RNA-seq reveals challenges of quantifying HLA expression.

Human leukocyte antigen (HLA) class I and II loci are essential elements of innate and acquired immunity. Their functions include antigen presentation to T cells leading to cellular and humoral immune responses, and modulation of NK cells. Their exceptional influence on disease outcome has now been made clear by genome-wide association studies. The exons encoding the peptide-binding groove have been the main focus for determining HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease outcome, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. To estimate HLA expression, immunogenetic studies traditionally rely on quantitative PCR (qPCR). Adoption of alternative high-throughput technologies such as RNA-seq has been hampered by technical issues due to the extreme polymorphism at HLA genes. Recently, however, multiple bioinformatic methods have been developed to accurately estimate HLA expression from RNA-seq data. This opens an exciting opportunity to quantify HLA expression in large datasets but also brings questions on whether RNA-seq results are comparable to those by qPCR. In this study, we analyze three classes of expression data for HLA class I genes for a matched set of individuals: (a) RNA-seq, (b) qPCR, and (c) cell surface HLA-C expression. We observed a moderate correlation between expression estimates from qPCR and RNA-seq for HLA-A, -B, and -C (0.2 ≤ rho ≤ 0.53). We discuss technical and biological factors which need to be accounted for when comparing quantifications for different molecular phenotypes or using different techniques.

How natural selection shapes genetic differentiation in the MHC region: A case study with Native Americans.

The Human Leukocyte Antigen (HLA) loci are extremely well documented targets of balancing selection, yet few studies have explored how selection affects population differentiation at these loci. In the present study we investigate genetic differentiation at HLA genes by comparing differentiation at microsatellites distributed genomewide to those in the MHC region. Our study uses a sample of 494 individuals from 30 human populations, 28 of which are Native Americans, all of whom were typed for genomewide and MHC region microsatellites. We find greater differentiation in the MHC than in the remainder of the genome (FST-MHC = 0.130 and FST-Genomic = 0.087), and use a permutation approach to show that this difference is statistically significant, and not accounted for by confounding factors. This finding lies in the opposite direction to the expectation that balancing selection reduces population differentiation. We interpret our findings as evidence that selection favors different sets of alleles in distinct localities, leading to increased differentiation. Thus, balancing selection at HLA genes simultaneously increases intra-population polymorphism and inter-population differentiation in Native Americans.

Demographic history and selection at HLA loci in Native Americans.

The American continent was the last to be occupied by modern humans, and native populations bear the marks of recent expansions, bottlenecks, natural selection, and population substructure. Here we investigate how this demographic history has shaped genetic variation at the strongly selected HLA loci. In order to disentangle the relative contributions of selection and demography process, we assembled a dataset with genome-wide microsatellites and HLA-A, -B, -C, and -DRB1 typing data for a set of 424 Native American individuals. We find that demographic history explains a sizeable fraction of HLA variation, both within and among populations. A striking feature of HLA variation in the Americas is the existence of alleles which are present in the continent but either absent or very rare elsewhere in the world. We show that this feature is consistent with demographic history (i.e., the combination of changes in population size associated with bottlenecks and subsequent population expansions). However, signatures of selection at HLA loci are still visible, with significant evidence selection at deeper timescales for most loci and populations, as well as population differentiation at HLA loci exceeding that seen at neutral markers.

Asymmetric linkage disequilibrium: Tools for assessing multiallelic LD.

Standard measures of linkage disequilibrium (LD) provide an incomplete description of the correlation between two loci. Recently, Thomson and Single (2014) described a new asymmetric pair of LD measures (ALD) that give a more complete description of LD. The ALD measures are symmetric and equivalent to the correlation coefficient r when both loci are bi-allelic. When the numbers of alleles at the two loci differ, the ALD measures capture this asymmetry and provide additional detail about the LD structure. In disease association studies the ALD measures are useful for identifying additional disease genes in a genetic region, by conditioning on known effects. In evolutionary genetic studies ALD measures provide insight into selection acting on individual amino acids of specific genes, or other loci in high LD (see Thomson and Single (2014) for these examples). Here we describe new software for computing and visualizing ALD. We demonstrate the utility of this software using haplotype frequency data from the National Marrow Donor Program (NMDP). This enhances our understanding of LD patterns in the NMDP data by quantifying the degree to which LD is asymmetric and also quantifies this effect for individual alleles.

Conditional asymmetric linkage disequilibrium (ALD): extending the biallelic r2 measure.

For multiallelic loci, standard measures of linkage disequilibrium provide an incomplete description of the correlation of variation at two loci, especially when there are different numbers of alleles at the two loci. We have developed a complementary pair of conditional asymmetric linkage disequilibrium (ALD) measures. Since these measures do not assume symmetry, they more accurately describe the correlation between two loci and can identify heterogeneity in genetic variation not captured by other symmetric measures. For biallelic loci the ALD are symmetric and equivalent to the correlation coefficient r. The ALD measures are particularly relevant for disease-association studies to identify cases in which an analysis can be stratified by one of more loci. A stratified analysis can aid in detecting primary disease-predisposing genes and additional disease genes in a genetic region. The ALD measures are also informative for detecting selection acting independently on loci in high linkage disequilibrium or on specific amino acids within genes. For SNP data, the ALD statistics provide a measure of linkage disequilibrium on the same scale for comparisons among SNPs, among SNPs and more polymorphic loci, among haplotype blocks of SNPs, and for fine mapping of disease genes. The ALD measures, combined with haplotype-specific homozygosity, will be increasingly useful as next-generation sequencing methods identify additional allelic variation throughout the genome.

Utilization of neoadjuvant chemotherapy varies in the treatment of women with invasive breast cancer.

BACKGROUND: Treatment with neoadjuvant chemotherapy (NAC) has made it possible for some women to be successfully treated with breast conservation therapy (BCT ) who were initially considered ineligible. Factors related to current practice patterns of NAC use are important to understand particularly as the surgical treatment of invasive breast cancer has changed. The goal of this study was to determine variations in neoadjuvant chemotherapy use in a large multi-center national database of patients with breast cancer. METHODS: We evaluated NAC use in patients with initially operable invasive breast cancer and potential impact on breast conservation rates. Records of 2871 women ages 18-years and older diagnosed with 2907 invasive breast cancers from January 2003 to December 2008 at four institutions across the United States were examined using the Breast Cancer Surgical Outcomes (BRCASO) database. Main outcome measures included NAC use and association with pre-operatively identified clinical factors, surgical approach (partial mastectomy [PM] or total mastectomy [TM]), and BCT failure (initial PM followed by subsequent TM). RESULTS: Overall, NAC utilization was 3.8%l. Factors associated with NAC use included younger age, pre-operatively known positive nodal status, and increasing clinical tumor size. NAC use and BCT failure rates increased with clinical tumor size, and there was significant variation in NAC use across institutions. Initial TM frequency approached initial PM frequency for tumors >30-40 mm; BCT failure rate was 22.7% for tumors >40 mm. Only 2.7% of patients undergoing initial PM and 7.2% undergoing initial TM received NAC. CONCLUSIONS: NAC use in this study was infrequent and varied among institutions. Infrequent NAC use in patients suggests that NAC may be underutilized in eligible patients desiring breast conservation.

Factors associated with the frequency of initial total mastectomy: results of a multi-institutional study.

BACKGROUND: Several previous studies have reported conflicting data on recent trends in use of initial total mastectomy (TM); the factors that contribute to TM variation are not entirely clear. Using a multi-institution database, we analyzed how practice, patient, and tumor characteristics contributed to variation in TM for invasive breast cancer. STUDY DESIGN: We collected detailed clinical and pathologic data about breast cancer diagnosis, initial, and subsequent breast cancer operations performed on all female patients from 4 participating institutions from 2003 to 2008. We limited this analysis to 2,384 incident cases of invasive breast cancer, stages I to III, and excluded patients with clinical indications for mastectomy. Predictors of initial TM were identified with univariate analyses and random effects multivariable logistic regression models. RESULTS: Initial TM was performed on 397 (16.7%) eligible patients. Use of preoperative MRI more than doubled the rate of TM (odds ratio [OR] = 2.44; 95% CI, 1.58-3.77; p < 0.0001). Increasing tumor size, high nuclear grade, and age were also associated with increased rates of initial TM. Differences by age and ethnicity were observed, and significant variation in the frequency of TM was seen at the individual surgeon level (p < 0.001). Our results were similar when restricted to tumors <20 mm. CONCLUSIONS: We identified factors associated with initial TM, including preoperative MRI and individual surgeon, that contribute to the current debate about variation in use of TM for the management of breast cancer. Additional evaluation of patient understanding of surgical options and outcomes in breast cancer and the impact of the surgeon provider is warranted.

Killer cell immunoglobulin-like receptor (KIR) gene content variation in the HGDP-CEPH populations.

In the present study, we investigate patterns of variation in the KIR cluster in a large and well-characterized sample of worldwide human populations in the Human Genome Diversity Project-Centre d'Etude du Polymorphisme Humain (HGDP-CEPH) panel in order to better understand the patterns of diversity in the region. Comparison of KIR data with that from other genomic regions allows control for strictly demographic factors; over 500,000 additional genomic markers have been typed in this panel by other investigators and the data made publicly available. Presence/absence frequencies and haplotypic associations for the KIR region are analyzed in the 52 populations comprising the panel and in accordance with major world regions (Africa, Middle East, Central Asia, East Asia, Europe, Americas, and Oceania). These data represent the first overview of KIR population genetics in the well-documented HGDP-CEPH panel and suggest different evolutionary histories and recent selection in the KIR gene cluster.

Standard methods for the management of immunogenetic data.

In this chapter, we outline some basic principles for the consistent management of immunogenetic data. These include the preparation of a single master data file that can serve as the basis for all subsequent analyses, a focus on the quality and homogeneity of the data to be analyzed, the documentation of the coding systems used to represent the data, and the application of nomenclature standards specific for each immunogenetic system being evaluated. The data management principles discussed here are intended to provide a foundation for the data analysis methods detailed in Chaps. 13 and 14 . The relationship between the data management and analysis methods covered in these three chapters is illustrated in Fig. 3.The application of these data management principles is a first step toward consistent and reproducible data analyses. While it may take extra time and effort to apply them, we feel that it is better to take this approach than to assume that low data quality can be compensated for by large sample sizes.In addition to their relevance for analytical reproducibility, it is important to consider these data management principles from an ethical perspective. The reliability of the data collected and generated as part of a research study should be as important a component of the ethical review of a research application as the security of those data. Finally, in addition to ensuring the integrity of the data from collection to publication, the application of these data management principles will provide a means to foster research integrity and to improve the potential for collaborative data sharing.

Analytical methods for immunogenetic population data.

In this chapter, we describe analyses commonly applied to immunogenetic population data, along with software tools that are currently available to perform those analyses. Where possible, we focus on tools that have been developed specifically for the analysis of highly polymorphic immunogenetic data. These analytical methods serve both as a means to examine the appropriateness of a dataset for testing a specific hypothesis, as well as a means of testing hypotheses. Rather than treat this chapter as a protocol for analyzing any population dataset, each researcher and analyst should first consider their data, the possible analyses, and any available tools in light of the hypothesis being tested. The extent to which the data and analyses are appropriate to each other should be determined before any analyses are performed.

Improving quality of breast cancer surgery through development of a national breast cancer surgical outcomes (BRCASO) research database.

BACKGROUND: Common measures of surgical quality are 30-day morbidity and mortality, which poorly describe breast cancer surgical quality with extremely low morbidity and mortality rates. Several national quality programs have collected additional surgical quality measures; however, program participation is voluntary and results may not be generalizable to all surgeons. We developed the Breast Cancer Surgical Outcomes (BRCASO) database to capture meaningful breast cancer surgical quality measures among a non-voluntary sample, and study variation in these measures across providers, facilities, and health plans. This paper describes our study protocol, data collection methods, and summarizes the strengths and limitations of these data. METHODS: We included 4524 women ≥18 years diagnosed with breast cancer between 2003-2008. All women with initial breast cancer surgery performed by a surgeon employed at the University of Vermont or three Cancer Research Network (CRN) health plans were eligible for inclusion. From the CRN institutions, we collected electronic administrative data including tumor registry information, Current Procedure Terminology codes for breast cancer surgeries, surgeons, surgical facilities, and patient demographics. We supplemented electronic data with medical record abstraction to collect additional pathology and surgery detail. All data were manually abstracted at the University of Vermont. RESULTS: The CRN institutions pre-filled 30% (22 out of 72) of elements using electronic data. The remaining elements, including detailed pathology margin status and breast and lymph node surgeries, required chart abstraction. The mean age was 61 years (range 20-98 years); 70% of women were diagnosed with invasive ductal carcinoma, 20% with ductal carcinoma in situ, and 10% with invasive lobular carcinoma. CONCLUSIONS: The BRCASO database is one of the largest, multi-site research resources of meaningful breast cancer surgical quality data in the United States. Assembling data from electronic administrative databases and manual chart review balanced efficiency with high-quality, unbiased data collection. Using the BRCASO database, we will evaluate surgical quality measures including mastectomy rates, positive margin rates, and partial mastectomy re-excision rates among a diverse, non-voluntary population of patients, providers, and facilities.

Variability in reexcision following breast conservation surgery.

CONTEXT: Health care reform calls for increasing physician accountability and transparency of outcomes. Partial mastectomy is the most commonly performed procedure for invasive breast cancer and often requires reexcision. Variability in reexcision might be reflective of the quality of care. OBJECTIVE: To assess hospital and surgeon-specific variation in reexcision rates following partial mastectomy. DESIGN, SETTING, AND PATIENTS: An observational study of breast surgery performed between 2003 and 2008 intended to evaluate variability in breast cancer surgical care outcomes and evaluate potential quality measures of breast cancer surgery. Women with invasive breast cancer undergoing partial mastectomy from 4 institutions were studied (1 university hospital [University of Vermont] and 3 large health plans [Kaiser Permanente Colorado, Group Health, and Marshfield Clinic]). Data were obtained from electronic medical records and chart abstraction of surgical, pathology, radiology, and outpatient records, including detailed surgical margin status. Logistic regression including surgeon-level random effects was used to identify predictors of reexcision. MAIN OUTCOME MEASURE: Incidence of reexcision. RESULTS: A total of 2206 women with 2220 invasive breast cancers underwent partial mastectomy and 509 patients (22.9%; 95% CI, 21.2%-24.7%) underwent reexcision (454 patients [89.2%; 95% CI, 86.5%-91.9%] had 1 reexcision, 48 [9.4%; 95% CI, 6.9%-12.0%] had 2 reexcisions, and 7 [1.4%; 95% CI, 0.4%-2.4%] had 3 reexcisions). Among all patients undergoing initial partial mastectomy, total mastectomy was performed in 190 patients (8.5%; 95% CI, 7.2%-9.5%). Reexcision rates for margin status following initial surgery were 85.9% (95% CI, 82.0%-89.8%) for initial positive margins, 47.9% (95% CI, 42.0%-53.9%) for less than 1.0 mm margins, 20.2% (95% CI, 15.3%-25.0%) for 1.0 to 1.9 mm margins, and 6.3% (95% CI, 3.2%-9.3%) for 2.0 to 2.9 mm margins. For patients with negative margins, reexcision rates varied widely among surgeons (range, 0%-70%; P = .003) and institutions (range, 1.7%-20.9%; P < .001). Reexcision rates were not associated with surgeon procedure volume after adjusting for case mix (P = .92). CONCLUSION: Substantial surgeon and institutional variation were observed in reexcision following partial mastectomy in women with invasive breast cancer.

Tracking human migrations by the analysis of the distribution of HLA alleles, lineages and haplotypes in closed and open populations.

The human leucocyte antigen (HLA) system shows extensive variation in the number and function of loci and the number of alleles present at any one locus. Allele distribution has been analysed in many populations through the course of several decades, and the implementation of molecular typing has significantly increased the level of diversity revealing that many serotypes have multiple functional variants. While the degree of diversity in many populations is equivalent and may result from functional polymorphism(s) in peptide presentation, homogeneous and heterogeneous populations present contrasting numbers of alleles and lineages at the loci with high-density expression products. In spite of these differences, the homozygosity levels are comparable in almost all of them. The balanced distribution of HLA alleles is consistent with overdominant selection. The genetic distances between outbred populations correlate with their geographical locations; the formal genetic distance measurements are larger than expected between inbred populations in the same region. The latter present many unique alleles grouped in a few lineages consistent with limited founder polymorphism in which any novel allele may have been positively selected to enlarge the communal peptide-binding repertoire of a given population. On the other hand, it has been observed that some alleles are found in multiple populations with distinctive haplotypic associations suggesting that convergent evolution events may have taken place as well. It appears that the HLA system has been under strong selection, probably owing to its fundamental role in varying immune responses. Therefore, allelic diversity in HLA should be analysed in conjunction with other genetic markers to accurately track the migrations of modern humans.

Local recurrence after partial mastectomy: relation to initial surgical margins.

BACKGROUND: Local recurrence (LR) after partial mastectomy (PM) has been associated with inadequate surgical margins. We assessed LR association with initial margins after PM in patients receiving postoperative radiation therapy (RT). METHODS: Initial margins, re-excision status, and ipsilateral LR were identified for all patients having initial PM from 2003 to 2008. RESULTS: Seven hundred twelve patients underwent PM as their final procedure, and 598 (84.0%) had adjuvant RT. Initial margins were positive or <1-mm margins in 166 patients (27.8%). Re-excision was performed for all positive and 20.2% of patients with margins <1 mm. We observed 10 LRs (1.7%) at the 3.4-year mean follow-up. For patients with initial margins <1 mm, the LR rate was 4.2% (7/167) and just .7% for margins ≥1 mm (P = .006). CONCLUSIONS: We report lower LR rates than traditionally reported. The surgical practice of re-excision to achieve margins of 1 to 5 mm needs closer scrutiny because it may have no impact on LR.

Sequence feature variant type (SFVT) analysis of the HLA genetic association in juvenile idiopathic arthritis.

The immune response HLA class II DRB1 gene provides the major genetic contribution to Juvenile Idiopathic Arthritis (JIA), with a hierarchy of predisposing through intermediate to protective effects. With JIA, and the many other HLA associated diseases, it is difficult to identify the combinations of biologically relevant amino acid (AA) residues directly involved in disease due to the high level of HLA polymorphism, the pattern of AA variability, including varying degrees of linkage disequilibrium (LD), and the fact that most HLA variation occurs at functionally important sites. In a subset of JIA patients with the clinical phenotype oligoarticular-persistent (OP), we have applied a recently developed novel approach to genetic association analyses with genes/proteins sub-divided into biologically relevant smaller sequence features (SFs), and their "alleles" which are called variant types (VTs). With SFVT analysis, association tests are performed on variation at biologically relevant SFs based on structural (e.g., beta-strand 1) and functional (e.g., peptide binding site) features of the protein. We have extended the SFVT analysis pipeline to additionally include pairwise comparisons of DRB1 alleles within serogroup classes, our extension of the Salamon Unique Combinations algorithm, and LD patterns of AA variability to evaluate the SFVT results; all of which contributed additional complementary information. With JIA-OP, we identified a set of single AA SFs, and SFs in which they occur, particularly pockets of the peptide binding site, that account for the major disease risk attributable to HLA DRB1. These are (in numeric order): AAs 13 (pockets 4 and 6), 37 and 57 (both pocket 9), 67 (pocket 7), 74 (pocket 4), and 86 (pocket 1), and to a lesser extent 30 (pockets 6 and 7) and 71 (pockets 4, 5, and 7).

Distribution of killer cell immunoglobulin-like receptors (KIR) and their HLA-C ligands in two Iranian populations.

Killer cell immunoglobulin-like receptors (KIR) gene frequencies vary between populations and contribute to functional variation in immune responses to viruses,autoimmunity and reproductive success. This study describes the frequency distribution of 12 variable KIR genes and their HLA-C ligands in two Iranian populations who have lived for many generations in different environments:t he Azerbaijanis at high altitude and the Jonobi people at sea level. The results are compared with those published for other human populations and a large group of English Caucasians. Differences were seen in KIR and HLA-C group frequencies, in linkage disequilibrium and inhibitory/activating KIR ratios between the groups. Similarities with geographically close populations in the frequencies of the KIR A and B haplotypes and KIR AA genotype reflected their common ancestry. The extreme variability of the KIR gene family and their HLA-C ligands is highlighted and their importance in defining differences between geographically and culturally isolated communities subject to different environmental pressures who come from the same ethnic grouping.

Quality assessment of neoadjuvant therapy use in breast conservation: barriers to implementation.

Neoadjuvant systemic therapy (NST) for operable breast cancer can increase the options for conservative surgery in patients with breast cancer. We performed an analysis of a breast cancer outcomes database as a quality assessment of neoadjuvant therapy use in relation to breast conservative rate (BCR). Data were reviewed from a breast cancer database established to monitor outcomes of breast cancer surgery at a tertiary care breast cancer clinic. The frequency of NST-use was correlated to tumor size and BCR. Cause-specific factors for omitting NST in patients undergoing mastectomy for tumors 3 cm or greater were determined. NST was employed in 29 of 241 (12%) cases of invasive breast carcinoma treated surgically from 2003 to 2005. Although a significant decrease in BCR occurred in tumors >3 cm, NST was not frequently employed until tumors reached >5 cm. Defined contraindications to breast conservation (65%) and patient choice for mastectomy (30%) were the two most common reasons for omitting NST in tumors > or = 3 cm. Despite the initial appearance of NST under-utilization in tumors measuring between 3-5 cm, appropriate exclusion of patients not suitable for breast conservation and patient choice for mastectomy both emerged as leading factors for the omission of NST in this group. Use of NST is an important quality metric in optimizing breast conservation. Patient education and greater understanding of patient-related barriers to NST may help improve BCR.

Methods for assessing gene content diversity of KIR with examples from a global set of populations.

A number of statistical methods are widely used to describe allelic variation at specific genetic loci and its implication on the evolutionary history of these loci. Although the methods were developed primarily to study allelic variation at loci that are virtually always present in the genome, they are often applied to data of gene content variation (i.e., presence/absence of multiple homologous genes) at the killer cell immunoglobulin-like receptor (KIR) gene cluster. In this paper, we discuss methodological issues involved in the analysis of gene content variation data in the KIR region and also its covariation with polymorphism at the human leukocyte antigen class I loci, which encode ligands for KIR. A comparison of several statistical methods and measures (gene frequency, haplotype frequency, and linkage disequilibrium estimation) using the Centre d'Etude du Polymorphisme Humain data will be provided using KIR haplotypes that have been determined by segregation analysis, noting the strengths and weaknesses of the methods when only the presence/absence data is considered. Finally, application of these methods to a set of globally distributed populations is described (see Single et al., Nat Genet 39:1114-1119, 2007) in order to illustrate the challenges faced when inferring the joint effects of natural selection and demographic history on these immune-related genes.

Balancing selection and heterogeneity across the classical human leukocyte antigen loci: a meta-analytic review of 497 population studies.

This paper presents a meta-analysis of high-resolution human leukocyte antigen (HLA) allele frequency data describing 497 population samples. Most of the datasets were compiled from studies published in eight journals from 1990 to 2007; additional datasets came from the International Histocompatibility Workshops and from the AlleleFrequencies.net database. In all, these data represent approximately 66,800 individuals from throughout the world, providing an opportunity to observe trends that may not have been evident at the time the data were originally analyzed, especially with regard to the relative importance of balancing selection among the HLA loci. Population genetic measures of allele frequency distributions were summarized across populations by locus and geographic region. A role for balancing selection maintaining much of HLA variation was confirmed. Further, the breadth of this meta-analysis allowed the ranking of the HLA loci, with DQA1 and HLA-C showing the strongest balancing selection and DPB1 being compatible with neutrality. Comparisons of the allelic spectra reported by studies since 1990 indicate that most of the HLA alleles identified since 2000 are very-low-frequency alleles. The literature-based allele-count data, as well as maps summarizing the geographic distributions for each allele, are available online.