Baseline characteristics of SARS-CoV-2 vaccine non-responders in a large population-based sample.

INTRODUCTION: Studies indicate that individuals with chronic conditions and specific baseline characteristics may not mount a robust humoral antibody response to SARS-CoV-2 vaccines. In this paper, we used data from the Texas Coronavirus Antibody REsponse Survey (Texas CARES), a longitudinal state-wide seroprevalence program that has enrolled more than 90,000 participants, to evaluate the role of chronic diseases as the potential risk factors of non-response to SARS-CoV-2 vaccines in a large epidemiologic cohort. METHODS: A participant needed to complete an online survey and a blood draw to test for SARS-CoV-2 circulating plasma antibodies at four-time points spaced at least three months apart. Chronic disease predictors of vaccine non-response are evaluated using logistic regression with non-response as the outcome and each chronic disease + age as the predictors. RESULTS: As of April 24, 2023, 18,240 participants met the inclusion criteria; 0.58% (N = 105) of these are non-responders. Adjusting for age, our results show that participants with self-reported immunocompromised status, kidney disease, cancer, and "other" non-specified comorbidity were 15.43, 5.11, 2.59, and 3.13 times more likely to fail to mount a complete response to a vaccine, respectively. Furthermore, having two or more chronic diseases doubled the prevalence of non-response. CONCLUSION: Consistent with smaller targeted studies, a large epidemiologic cohort bears the same conclusion and demonstrates immunocompromised, cancer, kidney disease, and the number of diseases are associated with vaccine non-response. This study suggests that those individuals, with chronic diseases with the potential to affect their immune system response, may need increased doses or repeated doses of COVID-19 vaccines to develop a protective antibody level.

Characterizing Health Literacy and Its Correlates Among Individuals With Traumatic Brain Injury (TBI): A TBI Model Systems Study.

OBJECTIVE: To characterize health literacy among individuals with traumatic brain injury (TBI) at least a year postinjury and to explore its relationship to sociodemographic variables, injury severity, and cognition. SETTING: Community following discharge from inpatient rehabilitation. PARTICIPANTS: In total, 205 individuals with complicated mild to severe TBI who completed follow-up as part of a national longitudinal study of TBI and completed a web-based health literacy measure. DESIGN: Multicenter, cross-sectional, observational study. MAIN MEASURES: Health Literacy Assessment Using Talking Touchscreen Technology. RESULTS: Thirty-one percent of the sample demonstrated marginal/inadequate health literacy; 69% demonstrated adequate health literacy. A higher proportion of non-Hispanic White adults had adequate health literacy than non-Hispanic Black and Hispanic adults. Individuals with greater than a high school education were more likely to have adequate health literacy than those with a high school education or less. Better executive functioning performance was related to adequate health literacy. Better episodic memory performance was related to adequate health literacy, but only for those with complicated mild to moderate injury. CONCLUSIONS: A substantial proportion of individuals with TBI have marginal/inadequate health literacy, which may impact their understanding, appreciation, and use of health-related information and recommendations. While low health literacy may be preexisting, directly related to TBI, or a combination of both, it should be screened and considered by professionals when communicating with persons with TBI. Healthcare providers should tailor their communication approaches and presentation of health information, particularly for those with low health literacy.

Feasibility and user-experience of a virtual environment for social connection and education after stroke: A pilot study.

OBJECTIVES: To evaluate the feasibility and usability of stroke survivor participation in an 8-week virtual environment intervention that provides opportunities for social support exchanges, social network interactions, and recovery education. MATERIALS AND METHODS: A single-group, pre- and post-test measure design was used. Descriptive statistics were used to examine enrollment and retention rates, proportion of questionnaires completed, and virtual environment process data (e.g., number of log-ins) and usability scores. Changes in pre- and post-intervention questionnaire (e.g., usability, social support, depression, anxiety, loneliness, and self-efficacy) scores were explored using Wilcoxon signed-rank tests and paired t-test. RESULTS: Fifteen (65 %) of the eligible stroke survivors enrolled (60 % white, 27 % black), 12 (80 %) had an ischemic stroke, ages ranged from 33 to 74 years (mean 44 years), and mean months since stroke was 33 ± 23. Retention and questionnaire completion rates were both 93 % (n = 14). Survivors logged into the virtual environment a total of 122 times, logged an average of 49 min/log-in, and 12 (80 %) attended support groups and social activities. Median usability score indicated lower than average usability. Improvement trends in social support, loneliness, and depressive symptoms were found, but significant changes in mean questionnaire scores were not found. CONCLUSIONS: Overall, the results suggest that using a virtual environment to foster social support exchanges, social network interactions, and recovery education after stroke is feasible. Similar to other chronic disease populations, stroke survivor adoption of a virtual environment likely requires ongoing technical assistance, repetition of instructions, and opportunities for practice to reinforce engagement. TRIAL REGISTRATION: NCT05487144.

The Relationship of Health Literacy to Health Outcomes Among Individuals With Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

OBJECTIVE: To examine the associations between health literacy and health outcomes among individuals with traumatic brain injury (TBI) at least a year post-injury. SETTING: Community following discharge from inpatient rehabilitation. PARTICIPANTS: A total of 205 individuals with complicated mild to severe TBI who completed a TBI Model Systems National Database follow-up interview and a web-based health literacy measure. DESIGN: A multicenter, cross-sectional, observational study. MAIN MEASURES: The Health Literacy Assessment Using Talking Touchscreen Technology (Health LiTT), number of comorbid conditions (Medical and Mental Health Comorbidities Interview [MMHCI]), perceived physical and mental health (PROMIS Global Physical and Mental Health subscales), Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder-7 (GAD-7). RESULTS: After controlling for sociodemographic, injury, cognition, and time post-injury, adequate health literacy was associated with higher odds of greater perceived physical health compared with participants with marginal/inadequate health literacy (odds ratio = 4.10; CI = 1.52-11.70]. Participants with inadequate/marginal health literacy had 3.50 times greater odds of depression (PHQ-9 ≥ 10) compared with those with adequate health literacy. Participants 45 years and older reported a greater number of MMHCI physical health conditions, but fewer MMHCI mental health conditions and GAD-7 anxiety symptoms compared with those who were younger. Non-Hispanic White participants and those with mild/moderate TBI were more likely to report a greater number of MMHCI mental health conditions compared with non-Hispanic Black participants or those with severe TBI. Greater time post-injury was associated with greater number of chronic physical and mental health conditions, and less odds of good-to-excellent perceived global mental health. CONCLUSIONS: Inadequate health literacy is associated with worse perceived physical health and greater depressive symptoms among adults with TBI. Greater efforts are needed to explore the mechanisms by which health literacy influences chronic disease management and mental health after TBI to improve postinjury health status and outcomes, particularly among those with limited health literacy skills.

Estimation of non-monotonic transition rates in a semi-Markov process with covariates adjustments and application to caregivers' stress data.

With the large ongoing number of aged people and Alzheimer's disease (AD) patients worldwide, unpaid caregivers have become the primary sources of their daily caregiving. Alzheimer's family caregivers often suffer from physical and mental morbidities owing to various reasons. The aims of this paper were to develop alternate methods to understand the transition properties, the dynamic change, and the long-run behavior of AD caregivers' stress levels, by assuming their transition to the next level only depends on the duration of the current stress level. In this paper, we modeled the transition rates in the semi-Markov Process with log-logistic hazard functions. We assumed the transition rates were non-monotonic over time and the scale of transition rates depended on covariates. We also extended the uniform accelerated expansion to calculate the long-run probability distribution of stress levels while adjusting for multiple covariates. The proposed methods were evaluated through an empirical study. The application results showed that all the transition rates of caregivers' stress levels were right skewed. Care recipients' baseline age was significantly associated with the transitions. The long-run probability of severe state was slightly higher, implying a prolonged recovery time for severe stress patients.

Coping With Chronic Pain After Traumatic Brain Injury: Role of Race/Ethnicity and Effect on Participation Outcomes in a TBI Model Systems Sample.

OBJECTIVE: To investigate catastrophizing and self-efficacy for managing pain among Non-Hispanic Whites, Non-Hispanic Blacks, and Hispanics with chronic pain after traumatic brain injury (TBI), and whether coping interacts with race/ethnicity to predict participation outcomes. SETTING: Community after discharge from inpatient rehabilitation. PARTICIPANTS: 621 individuals with moderate to severe TBI and chronic pain, who completed follow-up as part of a national longitudinal study of TBI and also participated in a collaborative study on chronic pain. DESIGN: Multicenter, cross-sectional, survey study. MAIN MEASURES: Catastrophizing subscale from the Coping With Pain Scale; Pain Self-Efficacy Questionnaire; Participation Assessment With Recombined Tools-Objective. RESULTS: After controlling for relevant sociodemographic variables, a significant interaction was observed between race/ethnicity and insurance status, such that Blacks who had public health insurance reported greater catastrophizing in response to pain compared with Whites. Race/ethnicity and self-efficacy for managing pain were unrelated. Greater catastrophizing was associated with lower participation but did not interact with race/ethnicity. Blacks reported lower participation relative to Whites, independent of catastrophizing. CONCLUSIONS: Black individuals who have TBI and chronic pain, and who have public insurance, may be vulnerable to difficulties managing pain. They are more likely to cope by catastrophizing, and catastrophizing is related to worse participation outcomes. The results suggest that access to care may affect response to chronic pain after TBI.

Disparities in Chronic Pain Experience and Treatment History Among Persons With Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

OBJECTIVE: To determine disparities in pain severity, pain interference, and history of pain treatment for non-Hispanic Whites, non-Hispanic Blacks, and Hispanics with traumatic brain injury (TBI) and chronic pain. SETTING: Community following discharge from inpatient rehabilitation. PARTICIPANTS: A total of 621 individuals with medically documented moderate to severe TBI who had received acute trauma care and inpatient rehabilitation (440 non-Hispanic Whites, 111 non-Hispanic Blacks, and 70 Hispanics). DESIGN: A multicenter, cross-sectional, survey study. MAIN MEASURES: Brief Pain Inventory; receipt of opioid prescription; receipt of nonpharmacologic pain treatments; and receipt of comprehensive interdisciplinary pain rehabilitation. RESULTS: After controlling for relevant sociodemographic variables, non-Hispanic Blacks reported greater pain severity and greater pain interference relative to non-Hispanic Whites. Race/ethnicity interacted with age, such that the differences between Whites and Blacks were greater for older participants (for severity and interference) and for those with less than a high school education (for interference). There were no differences found between the racial/ethnic groups in the odds of having ever received pain treatment. CONCLUSIONS: Among individuals with TBI who report chronic pain, non-Hispanic Blacks may be more vulnerable to difficulties managing pain severity and to interference of pain in activities and mood. Systemic biases experienced by many Black individuals with regard to social determinants of health must be considered in a holistic approach to assessing and treating chronic pain in individuals with TBI.

Incidence and Predictors of Breakthrough and Severe Breakthrough Infections of SARS-CoV-2 After Primary Series Vaccination in Adults: A Population-Based Survey of 22 575 Participants.

BACKGROUND: Breakthrough infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are well documented. The current study estimates breakthrough incidence across pandemic waves, and evaluates predictors of breakthrough and severe breakthrough infections (defined as those requiring hospitalization). METHODS: In total, 89 762 participants underwent longitudinal antibody surveillance. Incidence rates were calculated using total person-days contributed. Bias-corrected and age-adjusted logistic regression determined multivariable predictors of breakthrough and severe breakthrough infection, respectively. RESULTS: The incidence was 0.45 (95% confidence interval [CI], .38-.50) during pre-Delta, 2.80 (95% CI, 2.25-3.14) during Delta, and 11.2 (95% CI, 8.80-12.95) during Omicron, per 10 000 person-days. Factors associated with elevated odds of breakthrough included Hispanic ethnicity (vs non-Hispanic white, OR = 1.243; 95% CI, 1.073-1.441), larger household size (OR = 1.251 [95% CI, 1.048-1.494] for 3-5 vs 1 and OR = 1.726 [95% CI, 1.317-2.262] for more than 5 vs 1 person), rural versus urban living (OR = 1.383; 95% CI, 1.122-1.704), receiving Pfizer or Johnson & Johnson versus Moderna, and multiple comorbidities. Of the 1700 breakthrough infections, 1665 reported on severity; 112 (6.73%) were severe. Higher body mass index, Hispanic ethnicity, vaccine type, asthma, and hypertension predicted severe breakthroughs. CONCLUSIONS: Breakthrough infection was 4-25 times more common during the Omicron-dominant wave versus earlier waves. Higher burden of severe breakthrough infections was identified in subgroups.

Evaluating the impact of using a wound-specific oral nutritional supplement to support wound healing in a rehabilitation setting.

Chronic wounds adversely affect patient quality of life, increase the risk of mortality, and impose high costs on healthcare systems. Since protein-energy malnutrition or specific nutrient deficiencies can delay wound healing, nutritionally focused care is a key strategy to help prevent or treat the occurrence of non-healing wounds. The objective of our study of inpatients in a rehabilitation hospital was to quantify the effect of daily wound-specific oral nutritional supplementation (WS-ONS) on healing chronic wounds. Using electronic medical records, we conducted a retrospective analysis of patients with chronic wounds. We identified records for (a) a treatment group who received standard wound care + usual hospital diet + daily WS-ONS for ≥14 days, and (b) a control group who received standard wound care + a usual hospital diet. We collected data for demographics, nutritional status, and wound-relevant health characteristics. We examined weekly measurements of wound number and sizes (surface area for superficial wounds or volume for non-superficial wounds). There were 341 patients identified, 114 with 322 wounds in the treatment group and 227 patients with 420 wounds in the control group. We found that rehabilitation inpatients who were given nutritional support had larger wounds and lower functional independence on admission. At discharge, wound area reduction (percent) was nearly two-fold better in patients who were given daily WS-ONS + usual hospital diet compared to those who consumed usual diet only (61.1% vs 34.5%). Overall, weekly wound improvement (lowered wound area or wound volume) was more likely in the WS-ONS group than in the Control group, particularly from the start of care to week 2. Inpatients with largest wounds and lowest functional independence on admission were most likely to be given WS-ONS, an indication that caregivers recognised the need for supplementation. Week-to-week improvement in wound size was more likely in patients who received WS-ONS than in those who did not. Specifically, wound areas and wound volumes were significantly lower at discharge among patients who were given specialised nutritional support. More research in this field is needed to improve care and reduce healthcare costs.

Antibody Duration After Infection From SARS-CoV-2 in the Texas Coronavirus Antibody Response Survey.

Understanding the duration of antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 is important to controlling the current pandemic. Participants from the Texas Coronavirus Antibody Response Survey (Texas CARES) with at least 1 nucleocapsid protein antibody test were selected for a longitudinal analysis of antibody duration. A linear mixed model was fit to data from participants (n = 4553) with 1 to 3 antibody tests over 11 months (1 October 2020 to 16 September 2021), and models fit showed that expected antibody response after COVID-19 infection robustly increases for 100 days postinfection, and predicts individuals may remain antibody positive from natural infection beyond 500 days depending on age, body mass index, smoking or vaping use, and disease severity (hospitalized or not; symptomatic or not).

Methodology to estimate natural- and vaccine-induced antibodies to SARS-CoV-2 in a large geographic region.

Accurate estimates of natural and/or vaccine-induced antibodies to SARS-CoV-2 are difficult to obtain. Although model-based estimates of seroprevalence have been proposed, they require inputting unknown parameters including viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach, the current study presents a data-driven detailed statistical procedure for estimating total seroprevalence (defined as antibodies from natural infection or from full vaccination) in a region using prospectively collected serological data and state-level vaccination data. Specifically, we conducted a longitudinal statewide serological survey with 88,605 participants 5 years or older with 3 prospective blood draws beginning September 30, 2020. Along with state vaccination data, as of October 31, 2021, the estimated percentage of those 5 years or older with naturally occurring antibodies to SARS-CoV-2 in Texas is 35.0% (95% CI = (33.1%, 36.9%)). This is 3× higher than, state-confirmed COVID-19 cases (11.83%) for all ages. The percentage with naturally occurring or vaccine-induced antibodies (total seroprevalence) is 77.42%. This methodology is integral to pandemic preparedness as accurate estimates of seroprevalence can inform policy-making decisions relevant to SARS-CoV-2.

Relationships of self-awareness and facial affect recognition to social communication ability in persons with traumatic brain injury.

Traumatic brain injury (TBI) can cause changes to the injured person's physical ability, cognitive functioning, and social interactions. Since these attributes largely determine a person's concept of who they are, TBI poses a threat to sense of self. Due to the importance of social communication skills for community integration, impairment of these skills is a particular threat to sense of self. The present investigation sought to explore characteristics that influence social communication abilities. We hypothesized that both ability to interpret facial affect and self-awareness would be associated with communication ability. We also expected that facial affect recognition would influence self-awareness and that the effect of facial affect recognition on social communication would be partially mediated by self-awareness. For this prospective cohort study, participants were 77 individuals with documented TBI. Of these, 65% were male and 83% sustained severe injuries. The hypothesized association of facial affect recognition with social communication was demonstrated with path analysis as was the effect of facial affect recognition on self-awareness. However, the effect of facial affect recognition on social communication was not mediated by self-awareness. In addition, social communication was associated with employment, social integration, and loneliness. Findings highlighted the importance of social communication after TBI.

Trends and Correlates of Breakthrough Infections With SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant has been hypothesized to decrease the efficacy of COVID-19 vaccines. Factors associated with infections with SARS-CoV-2 after vaccination are unknown. In this observational cohort study, we examined two groups in Harris County, Texas: (1) individuals with positive Nucleic Acid Amplification test between 12/14/2020 and 9/30/2021 and (2) the subset of individuals fully vaccinated in the same time period. Infected individuals were classified as a breakthrough if their infection occurred 14 days after their vaccination had been completed. Among fully vaccinated individuals, demographic and vaccine factors associated with breakthrough infections were assessed. Of 146,731 positive SARS-CoV-2 tests, 7.5% were breakthrough infections. Correlates of breakthrough infection included young adult age, female, White race, and receiving the Janssen vaccine, after adjustments including the amount of community spread at the time of infection. Vaccines remained effective in decreasing the probability of testing positive for SARS-CoV-2. The data indicate that increased vaccine booster uptake would help decrease new infections.

The Impact of Health Literacy on Kidney Transplant Listing.

Introduction: Limited health literacy has been associated with poor health outcomes in the general population, but there have been few studies investigating the association between functional health literacy and kidney transplant listing. The primary objective of this study was to determine if functional health literacy was associated with kidney transplant listing after controlling for demographic, psychosocial, and medical variables, which were secondarily examined for correlation with transplant listing. Design: We retrospectively reviewed 423 kidney transplant candidates who were prospectively administered the Test of Functional Health Literacy in Adults during their transplant evaluation. Results: The functional health literacy scores were found to correlate with transplant listing (P = 0.013). Unexpectedly, a subset of patients (n = 14 out of 36) who had scores < 59 was still able to obtain approval for listing. The probability of approval decreased when functional health literacy scores ranged from 0 to 59 and increased when functional health literacy scores varied between 60 to 100. Multivariable analysis found transplant listing to also be associated with substance use (OR = 0.15, P < 0.001), ESKD etiology other than diabetes or hypertension (OR = 2.62, P < 0.001), time on dialysis (P = 0.012), and pace of transplant evaluation (P < 0.001). Conclusion: Functional health literacy was associated with kidney transplant listing. Programmatic interventions that can help overcome the impact of functional health literacy and improve access to transplantation should be explored.

External validation of a model determining risk of neoplastic progression of Barrett's esophagus in a cohort of U.S. veterans.

BACKGROUND AND AIMS: Risk of esophageal adenocarcinoma (EAC) in those with Barrett's esophagus (BE) is 11-fold greater than the general population. It remains unclear which BE patients are at highest risk of progression to EAC. We aimed to validate a predictive model risk-stratifying BE patients. METHODS: We conducted a retrospective cohort study at the Houston Veteran Affairs Medical Center of consecutive patients with a new diagnosis of BE from November 1990 to January 2019. Study follow-up was through February 2020. Patients were excluded if they had no follow-up EGD with esophageal biopsy sampling after the initial BE-diagnosing EGD or evidence of high-grade dysplasia (HGD) or EAC on initial EGD. We performed an external validation study of a risk model containing sex, smoking, BE length, and low-grade dysplasia (LGD) status and assessed discriminatory ability using the area under the receiver operating characteristic curve (AUROC). RESULTS: Among 608 BE patients, 24 progressed to HGD/EAC. The points-based model discriminated well with an AUROC of .72 (95% confidence interval [CI], .63-.82). When categorized into low-, intermediate-, and high-risk groups according to published cutoffs, the AUROC was poor at .57. Restructured into low-risk versus high-risk groups, the AUROC was .72 (95% CI, .64-.80). Excluding baseline LGD did not reduce discriminatory ability (AUROC, .73; 95% CI, .64-.82). CONCLUSIONS: This external validation provides further evidence that the model including sex, LGD status, smoking status, and BE length may help to risk stratify BE patients. A simplified version excluding LGD status and/or reducing the number of risk groups has increased utility in clinical practice without loss of discriminatory ability.

Power calculator for detecting allelic imbalance using hierarchical Bayesian model.

OBJECTIVE: Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI exist, but methods are needed to estimate type I error and power for detecting AI and difference of AI between conditions. As the costs of the technology plummet, what is more important: reads or replicates? RESULTS: We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10, 20, and 30%, respectively, deviation from allelic balance in a condition with power > 80%. A minimum of 960 and 240 allele specific reads divided equally among 8 replicates is needed to detect a 20 or 30% difference in AI between conditions with comparable power. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions.

Understanding loss to follow-up in a longitudinal study of people with traumatic brain injury.

OBJECTIVE: To examine factors related to attrition in a traumatic brain injury (TBI) study sample assessed up to 15 years after injury. PARTICIPANTS: One thousand twenty-eight participants with TBI who completed the year 1 follow-up assessment at a TBI Model Systems Center between 1992 and 2018. METHOD: Secondary analysis of data from a prospective longitudinal cohort study considering follow-up data collection completion status at years 1, 2, 5, 10, and 15. RESULTS: In univariable analyses, multiple factors were associated with loss to follow-up (LOFU) including being a member of a socially disadvantaged group, substance use history, residence, payor, cause of injury, and results of earlier follow-up attempts. In a multiple logistic regression analysis examining the prediction of follow-up condition at 10 or 15 years post-injury, only payor and race/ethnicity were significant predictors. Hispanic ethnicity was associated with higher odds of LOFU, and these participants often spoke Spanish and were born outside of the United States. CONCLUSIONS: The findings suggest a need to understand sociodemographic variables and their influence on participant attrition in longitudinal TBI research. With a better understanding of these predictors, procedures can be developed to address retention of participants who are identified as being at increased risk for study drop out.

Testcrosses are an efficient strategy for identifying cis-regulatory variation: Bayesian analysis of allele-specific expression (BayesASE).

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? The approach described applies to any technology generating allele-specific sequence counts, for example for chromatin accessibility and can be applied generally including to comparisons between tissues or environments for the same genotype. Tests of allelic effect are generally performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between nontester alleles, allowing n alleles to be compared with n crosses. Using a mouse data set where both testcrosses and direct comparisons have been performed, we show that the predicted differences between nontester alleles are validated at levels of over 90% when a parent-of-origin effect is present and of 60%-80% overall. Power considerations for a testcross, are similar to those in a reciprocal cross. In all applications, the testing for AI involves several complex bioinformatics steps. BayesASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BayesASE has been packaged in Galaxy, made available in Nextflow and as a collection of scripts for the SLURM workload manager on github (https://github.com/McIntyre-Lab/BayesASE).