Changes in chromatin accessibility and transcriptional landscape induced by HDAC inhibitors in TP53 mutated patient-derived colon cancer organoids.

Here we present the generation and characterization of patient-derived organoids (PDOs) from colorectal cancer patients. PDOs derived from two patients with TP53 mutations were tested with two different HDAC inhibitors (SAHA and NKL54). Cell death induction, transcriptome, and chromatin accessibility changes were analyzed. HDACIs promote the upregulation of low expressed genes and the downregulation of highly expressed genes. A similar differential effect is observed at the level of chromatin accessibility. Only SAHA is a potent inducer of cell death, which is characterized by the upregulation of BH3-only genes BIK and BMF. Up-regulation of BIK is associated with increased accessibility in an intronic region that has enhancer properties. SAHA, but not NKL54, also causes downregulation of BCL2L1 and decreases chromatin accessibility in three distinct regions of the BCL2L1 locus. Both inhibitors upregulate the expression of innate immunity genes and members of the MHC family. In summary, our exploratory study indicates a mechanism of action for SAHA and demonstrate the low efficacy of NKL54 as a single agent for apoptosis induction, using two PDOs. These observations need to be validated in a larger cohort of PDOs.

Equated hospitalization rate of patients with inflammatory rheumatic diseases as compared to normal population in 2°wave SARSCoV2 infection.

OBJECTIVE: To investigate the clinical manifestations and outcome of COVID-19 in patients with inflammatory rheumatic and musculoskeletal disease (iRMD) as compared with the general population. METHODS: This is a case-control study of patients selected from the South-Tyrol public health service-Italy with and without iRMD affected by COVID-19. We included patients ≥18 years and with a positive SARS-CoV-2 PCR test between 1.10.2020 and 01.03.2021. Cases were identified by linking the diagnosis of a rheumatic disease with PCR test positivity; these were matched in a 1:1.8 (planned 1:2) ratio for age, sex, and date of COVID-19 diagnosis with people from the general population. The outcomes of primary interest were hospitalization and severe course (intensive care unit, mechanical ventilation/extracorporeal membrane oxygenation, death). RESULTS: The study population consisted of 561 COVID-19 patients, of which 201 (mean age 60.4 years; 65.2% female) were patients with iRMD and 360 were controls from the general population (59.8 years; 64.7% female). The majority of iRMD patients (88.6%) received an immunosuppressive drug at time of COVID-19 diagnosis, 36.3% were under glucocorticoids. COVID-19 related hospitalization (12.4% vs 10.6%, p= 0.49), severe course (5.0% vs 5.3%, p= 1.00), and mortality (3.5% vs 4.4%, p= 0.66) were similar between groups. Among hospitalized patients, mechanic ventilation was more common in iRMD patients than in controls [n = 5 (20.0%) vs n = 1 (2.6%), p= 0.035]. CONCLUSIONS: Our study indicates similar rates for admission, severe course and mortality between patients with iRMD and controls affected by COVID-19. Among hospitalized patients, mechanical ventilation was more frequently required in the iRMD group.

Trends and symptoms of SARS-CoV-2 infection: a longitudinal study on an Alpine population representative sample.

OBJECTIVES: The continuous monitoring of SARS-CoV-2 infection waves and the emergence of novel pathogens pose a challenge for effective public health surveillance strategies based on diagnostics. Longitudinal population representative studies on incident events and symptoms of SARS-CoV-2 infection are scarce. We aimed at describing the evolution of the COVID-19 pandemic during 2020 and 2021 through regular monitoring of self-reported symptoms in an Alpine community sample. DESIGN: To this purpose, we designed a longitudinal population representative study, the Cooperative Health Research in South Tyrol COVID-19 study. PARTICIPANTS AND OUTCOME MEASURES: A sample of 845 participants was retrospectively investigated for active and past infections with swab and blood tests, by August 2020, allowing adjusted cumulative incidence estimation. Of them, 700 participants without previous infection or vaccination were followed up monthly until July 2021 for first-time infection and symptom self-reporting: COVID-19 anamnesis, social contacts, lifestyle and sociodemographic data were assessed remotely through digital questionnaires. Temporal symptom trajectories and infection rates were modelled through longitudinal clustering and dynamic correlation analysis. Negative binomial regression and random forest analysis assessed the relative importance of symptoms. RESULTS: At baseline, the cumulative incidence of SARS-CoV-2 infection was 1.10% (95% CI 0.51%, 2.10%). Symptom trajectories mimicked both self-reported and confirmed cases of incident infections. Cluster analysis identified two groups of high-frequency and low-frequency symptoms. Symptoms like fever and loss of smell fell in the low-frequency cluster. Symptoms most discriminative of test positivity (loss of smell, fatigue and joint-muscle aches) confirmed prior evidence. CONCLUSIONS: Regular symptom tracking from population representative samples is an effective screening tool auxiliary to laboratory diagnostics for novel pathogens at critical times, as manifested in this study of COVID-19 patterns. Integrated surveillance systems might benefit from more direct involvement of citizens' active symptom tracking.

Determinants of SARS-CoV-2 nasopharyngeal testing in a rural community sample susceptible of first infection: the CHRIS COVID-19 study.

To characterize COVID-19 epidemiology, numerous population-based studies have been undertaken to model the risk of SARS-CoV-2 infection. Less is known about what may drive the probability to undergo testing. Understanding how much testing is driven by contextual or individual conditions is important to delineate the role of individual behavior and to shape public health interventions and resource allocation. In the Val Venosta/Vinschgau district (South Tyrol, Italy), we conducted a population-representative longitudinal study on 697 individuals susceptible to first infection who completed 4,512 repeated online questionnaires at four-week intervals between September 2020 and May 2021. Mixed-effects logistic regression models were fitted to investigate associations of self-reported SARS-CoV-2 testing with individual characteristics (social, demographic, and biological) and contextual determinants. Testing was associated with month of reporting, reflecting the timing of both the pandemic intensity and public health interventions, COVID-19-related symptoms (odds ratio, OR:8.26; 95% confidence interval, CI:6.04-11.31), contacts with infected individuals within home (OR:7.47, 95%CI:3.81-14.62) or outside home (OR:9.87, 95%CI:5.78-16.85), and being retired (OR:0.50, 95%CI:0.34-0.73). Symptoms and next within- and outside-home contacts were the leading determinants of swab testing predisposition in the most acute phase of the pandemics. Testing was not associated with age, sex, education, comorbidities, or lifestyle factors. In the study area, contextual determinants reflecting the course of the pandemic were predominant compared to individual sociodemographic characteristics in explaining the SARS-CoV-2 probability of testing. Decision makers should evaluate whether the intended target groups were correctly prioritized by the testing campaign.

The Class IIA Histone Deacetylase (HDAC) Inhibitor TMP269 Downregulates Ribosomal Proteins and Has Anti-Proliferative and Pro-Apoptotic Effects on AML Cells.

Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by altered myeloid progenitor cell proliferation and differentiation. As in many other cancers, epigenetic transcriptional repressors such as histone deacetylases (HDACs) are dysregulated in AML. Here, we investigated (1) HDAC gene expression in AML patients and in different AML cell lines and (2) the effect of treating AML cells with the specific class IIA HDAC inhibitor TMP269, by applying proteomic and comparative bioinformatic analyses. We also analyzed cell proliferation, apoptosis, and the cell-killing capacities of TMP269 in combination with venetoclax compared to azacitidine plus venetoclax, by flow cytometry. Our results demonstrate significantly overexpressed class I and class II HDAC genes in AML patients, a phenotype which is conserved in AML cell lines. In AML MOLM-13 cells, TMP269 treatment downregulated a set of ribosomal proteins which are overexpressed in AML patients at the transcriptional level. TMP269 showed anti-proliferative effects and induced additive apoptotic effects in combination with venetoclax. We conclude that TMP269 exerts anti-leukemic activity when combined with venetoclax and has potential as a therapeutic drug in AML.

Transcriptomic and genomic studies classify NKL54 as a histone deacetylase inhibitor with indirect influence on MEF2-dependent transcription.

In leiomyosarcoma class IIa HDACs (histone deacetylases) bind MEF2 and convert these transcription factors into repressors to sustain proliferation. Disruption of this complex with small molecules should antagonize cancer growth. NKL54, a PAOA (pimeloylanilide o-aminoanilide) derivative, binds a hydrophobic groove of MEF2, which is used as a docking site by class IIa HDACs. However, NKL54 could also act as HDAC inhibitor (HDACI). Therefore, it is unclear which activity is predominant. Here, we show that NKL54 and similar derivatives are unable to release MEF2 from binding to class IIa HDACs. Comparative transcriptomic analysis classifies these molecules as HDACIs strongly related to SAHA/vorinostat. Low expressed genes are upregulated by HDACIs, while abundant genes are repressed. This transcriptional resetting correlates with a reorganization of H3K27 acetylation around the transcription start site (TSS). Among the upregulated genes there are several BH3-only family members, thus explaining the induction of apoptosis. Moreover, NKL54 triggers the upregulation of MEF2 and the downregulation of class IIa HDACs. NKL54 also increases the binding of MEF2D to promoters of genes that are upregulated after treatment. In summary, although NKL54 cannot outcompete MEF2 from binding to class IIa HDACs, it supports MEF2-dependent transcription through several actions, including potentiation of chromatin binding.

Influence of Glucose on Candida albicans and the Relevance of the Complement FH-Binding Molecule Hgt1 in a Murine Model of Candidiasis.

Candidiasis is common in diabetic patients. Complement evasion is facilitated by binding complement factor H (FH). Since the expression of high-affinity glucose transporter 1 (Hgt1), a FH-binding molecule, is glucose-dependent, we aimed to study its relevance to the pathogenesis of Candida albicans. Euglycemic and diabetic mice were intravenously challenged with either Candida albicans lacking Hgt1 (hgt1-/-) or its parental strain (SN152). Survival and clinical status were monitored over 14 days. In vitro, Candida albicans strains were grown at different glucose concentrations, opsonized with human serum, and checked for C3b/iC3b and FH deposition. Phagocytosis was studied by fluorescein isothiocyanate-labeled opsonized yeast cells incubated with granulocytes. The murine model demonstrated a significantly higher virulence of SN152 in diabetic mice and an overall increased lethality of mice challenged with hgt1-/-. In vitro lower phagocytosis and C3b/iC3b deposition and higher FH deposition were demonstrated for SN152 incubated at higher glucose concentrations, while there was no difference on hgt1-/- at physiological glucose concentrations. Despite C3b/iC3b and FH deposition being glucose-dependent, this effect has a minor influence on phagocytosis. The absence of Hgt1 is diminishing this dependency on complement deposition, but it cannot be attributed to being beneficial in a murine model.

Prospective epidemiological, molecular, and genetic characterization of a novel coronavirus disease in the Val Venosta/Vinschgau: the CHRIS COVID-19 study protocol.

The COVID-19 pandemic has been threatening the healthcare and socioeconomic systems of entire nations. While population-based surveys to assess the distribution of SARS-CoV-2 infection have become a priority, pre-existing longitudinal studies are ideally suited to assess the determinants of COVID-19 onset and severity.The Cooperative Health Research In South Tyrol (CHRIS) study completed the baseline recruitment of 13,393 adults from the Venosta/Vinschgau rural district in 2018, collecting extensive phenotypic and biomarker data, metabolomic data, densely imputed genotype and whole-exome sequencing data.Based on CHRIS, we designed a prospective study, called CHRIS COVID-19, aimed at: 1) estimating the incidence of SARS-CoV-2 infections; 2) screening for and investigating the determinants of incident infection among CHRIS participants and their household members; 3) monitoring the immune response of infected participants prospectively.An online screening questionnaire was sent to all CHRIS participants and their household members. A random sample of 1450 participants representative of the district population was invited to assess active (nasopharyngeal swab) or past (serum antibody test) infections. We prospectively invited for complete SARS-CoV-2 testing all questionnaire completers gauged as possible cases of past infection and their household members. In positive tested individuals, antibody response is monitored quarterly for one year. Untested and negative participants receive the screening questionnaire every four weeks until gauged as possible incident cases or till the study end.Originated from a collaboration between researchers and community stakeholders, the CHRIS COVID-19 study aims at generating knowledge about the epidemiological, molecular, and genetic characterization of COVID-19 and its long-term sequelae.

Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample: The CHRIS Study.

Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 × 10-8) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.

Prevalence and determinants of serum antibodies to SARS-CoV-2 in the general population of the Gardena valley.

Estimating the spread of SARS-CoV-2 infection in communities is critical. We surveyed 2244 stratified random sample community members of the Gardena valley, a winter touristic area, amidst the first expansion phase of the COVID-19 pandemic in Europe. We measured agreement between Diasorin and Abbott serum bioassay outputs and the Abbott optimal discriminant threshold of serum neutralisation titres with recursive receiver operating characteristic curve. We analytically adjusted serum antibody tests for unbiased seroprevalence estimate and analysed the determinants of infection with non-response weighted multiple logistic regression. SARS-CoV-2 seroprevalence was 26.9% (95% CI 25.2-28.6) by June 2020. The bioassays had a modest agreement with each other. At a lower threshold than the manufacturer's recommended level, the Abbott assay reflected greater discrimination of serum neutralisation capacity. Seropositivity was associated with place and economic activity, not with sex or age. Symptoms like fever and weakness were age-dependent. SARS-CoV-2 mitigation strategies should account for context in high prevalence areas.

Generation of hiPSC-Derived Functional Dopaminergic Neurons in Alginate-Based 3D Culture.

Human induced pluripotent stem cells (hiPSCs) represent an unlimited cell source for the generation of patient-specific dopaminergic (DA) neurons, overcoming the hurdle of restricted accessibility to disease-affected tissue for mechanistic studies on Parkinson's disease (PD). However, the complexity of the human brain is not fully recapitulated by existing monolayer culture methods. Neurons differentiated in a three dimensional (3D) in vitro culture system might better mimic the in vivo cellular environment for basic mechanistic studies and represent better predictors of drug responses in vivo. In this work we established a new in vitro cell culture system based on the microencapsulation of hiPSCs in small alginate/fibronectin beads and their differentiation to DA neurons. Optimization of hydrogel matrix concentrations and composition allowed a high viability of embedded hiPSCs. Neural differentiation competence and efficiency of DA neuronal generation were increased in the 3D cultures compared to a conventional 2D culture methodology. Additionally, electrophysiological parameters and metabolic switching profile confirmed increased functionality and an anticipated metabolic resetting of neurons grown in alginate scaffolds with respect to their 2D counterpart neurons. We also report long-term maintenance of neuronal cultures and preservation of the mature functional properties. Furthermore, our findings indicate that our 3D model system can recapitulate mitochondrial superoxide production as an important mitochondrial phenotype observed in neurons derived from PD patients, and that this phenotype might be detectable earlier during neuronal differentiation. Taken together, these results indicate that our alginate-based 3D culture system offers an advantageous strategy for the reliable and rapid derivation of mature and functional DA neurons from hiPSCs.

Familial Aggregation of Endemic Congenital Hypothyroidism Syndrome in Congo (DR): Historical Data.

Familial aggregation of endemic congenital hypothyroidism (CH) in an iodine-deficient population from northern Congo (Democratic Republic (DR)) was analysed on data collected four decades ago (1979-1980). During a systematic survey of 62 families, 46 endemic CH subjects (44 myxedematous and 2 neurological) were identified based on clinical evidence within a village cohort of 468 subjects. A distribution analysis showed that two families presented significant excess of cases versus a random background distribution. Both families were characterised by two healthy parents having all of their five offspring affected by some form of endemic CH. Goitre prevalence in endemic CH was lower than that in the general population, while goitre prevalence in the unaffected part of the cohort (parents and siblings) was similar to that of the general population. Some unidentified genetic/epigenetic factor(s) could contribute to the evolution of some iodine-deficient hypothyroid neonates through irreversible and progressive loss of thyroid functional capacity during early childhood (<5 years old). Besides severe iodine deficiency, environmental exposure to thiocyanate overload and selenium deficiency, factors not randomly distributed within families and population, intervened in the full expression of endemic CH. Further exploration in the field will remain open, as iodine deficiency in Congo (DR) was eliminated in the 1990s.

ensembldb: an R package to create and use Ensembl-based annotation resources.

SUMMARY: Bioinformatics research frequently involves handling gene-centric data such as exons, transcripts, proteins and their positions relative to a reference coordinate system. The ensembldb Bioconductor package retrieves and stores Ensembl-based genetic annotations and positional information, and furthermore offers identifier conversion and coordinates mappings for gene-associated data. In support of reproducible research, data are tied to Ensembl releases and are kept separately from the software. Premade data packages are available for a variety of genomes and Ensembl releases. Three examples demonstrate typical use cases of this software. AVAILABILITY AND IMPLEMENTATION: ensembldb is part of Bioconductor (https://bioconductor.org/packages/ensembldb). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

Motivation: Familial aggregation analysis is an important early step for characterizing the genetic determinants of phenotypes in epidemiological studies. To facilitate this analysis, a collection of methods to detect familial aggregation in large pedigrees has been made available recently. However, efficacy of these methods in real world scenarios remains largely unknown. Here, we assess the performance of five aggregation methods to identify individuals or groups of related individuals affected by a Mendelian trait within a large set of decoys. We investigate method performance under a representative set of combinations of causal variant penetrance, trait prevalence and number of affected generations in the pedigree. These methods are then applied to assess familial aggregation of familial hypercholesterolemia and stroke, in the context of the Cooperative Health Research in South Tyrol (CHRIS) study. Results: We find that in some situations statistical hypothesis testing with a binomial null distribution achieves performance similar to methods that are based on kinship information, while kinship based methods perform better when information is available on fewer generations. Potential case families from the CHRIS study are reported and the results are discussed taking into account insights from the performance assessment. Availability and implementation: The familial aggregation analysis package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg. Supplementary information: Supplementary data are available at Bioinformatics online.

HDAC Inhibition Improves the Sarcoendoplasmic Reticulum Ca2+-ATPase Activity in Cardiac Myocytes.

SERCA2a is the Ca2+ ATPase playing the major contribution in cardiomyocyte (CM) calcium removal. Its activity can be regulated by both modulatory proteins and several post-translational modifications. The aim of the present work was to investigate whether the function of SERCA2 can be modulated by treating CMs with the histone deacetylase (HDAC) inhibitor suberanilohydroxamic acid (SAHA). The incubation with SAHA (2.5 µM, 90 min) of CMs isolated from rat adult hearts resulted in an increase of SERCA2 acetylation level and improved ATPase activity. This was associated with a significant improvement of calcium transient recovery time and cell contractility. Previous reports have identified K464 as an acetylation site in human SERCA2. Mutants were generated where K464 was substituted with glutamine (Q) or arginine (R), mimicking constitutive acetylation or deacetylation, respectively. The K464Q mutation ameliorated ATPase activity and calcium transient recovery time, thus indicating that constitutive K464 acetylation has a positive impact on human SERCA2a (hSERCA2a) function. In conclusion, SAHA induced deacetylation inhibition had a positive impact on CM calcium handling, that, at least in part, was due to improved SERCA2 activity. This observation can provide the basis for the development of novel pharmacological approaches to ameliorate SERCA2 efficiency.

Detect, correct, retract: How to manage incorrect structural models.

The massive technical and computational progress of biomolecular crystallography has generated some adverse side effects. Most crystal structure models, produced by crystallographers or well-trained structural biologists, constitute useful sources of information, but occasional extreme outliers remind us that the process of structure determination is not fail-safe. The occurrence of severe errors or gross misinterpretations raises fundamental questions: Why do such aberrations emerge in the first place? How did they evade the sophisticated validation procedures which often produce clear and dire warnings, and why were severe errors not noticed by the depositors themselves, their supervisors, referees and editors? Once detected, what can be done to either correct, improve or eliminate such models? How do incorrect models affect the underlying claims or biomedical hypotheses they were intended, but failed, to support? What is the long-range effect of the propagation of such errors? And finally, what mechanisms can be envisioned to restore the validity of the scientific record and, if necessary, retract publications that are clearly invalidated by the lack of experimental evidence? We suggest that cognitive bias and flawed epistemology are likely at the root of the problem. By using examples from the published literature and from public repositories such as the Protein Data Bank, we provide case summaries to guide correction or improvement of structural models. When strong claims are unsustainable because of a deficient crystallographic model, removal of such a model and even retraction of the affected publication are necessary to restore the integrity of the scientific record.

Inclusion of biological knowledge in a Bayesian shrinkage model for joint estimation of SNP effects.

With the aim of improving detection of novel single-nucleotide polymorphisms (SNPs) in genetic association studies, we propose a method of including prior biological information in a Bayesian shrinkage model that jointly estimates SNP effects. We assume that the SNP effects follow a normal distribution centered at zero with variance controlled by a shrinkage hyperparameter. We use biological information to define the amount of shrinkage applied on the SNP effects distribution, so that the effects of SNPs with more biological support are less shrunk toward zero, thus being more likely detected. The performance of the method was tested in a simulation study (1,000 datasets, 500 subjects with ∼200 SNPs in 10 linkage disequilibrium (LD) blocks) using a continuous and a binary outcome. It was further tested in an empirical example on body mass index (continuous) and overweight (binary) in a dataset of 1,829 subjects and 2,614 SNPs from 30 blocks. Biological knowledge was retrieved using the bioinformatics tool Dintor, which queried various databases. The joint Bayesian model with inclusion of prior information outperformed the standard analysis: in the simulation study, the mean ranking of the true LD block was 2.8 for the Bayesian model versus 3.6 for the standard analysis of individual SNPs; in the empirical example, the mean ranking of the six true blocks was 8.5 versus 9.3 in the standard analysis. These results suggest that our method is more powerful than the standard analysis. We expect its performance to improve further as more biological information about SNPs becomes available.

Twilight reloaded: the peptide experience.

The de facto commoditization of biomolecular crystallography as a result of almost disruptive instrumentation automation and continuing improvement of software allows any sensibly trained structural biologist to conduct crystallographic studies of biomolecules with reasonably valid outcomes: that is, models based on properly interpreted electron density. Robust validation has led to major mistakes in the protein part of structure models becoming rare, but some depositions of protein-peptide complex structure models, which generally carry significant interest to the scientific community, still contain erroneous models of the bound peptide ligand. Here, the protein small-molecule ligand validation tool Twilight is updated to include peptide ligands. (i) The primary technical reasons and potential human factors leading to problems in ligand structure models are presented; (ii) a new method used to score peptide-ligand models is presented; (iii) a few instructive and specific examples, including an electron-density-based analysis of peptide-ligand structures that do not contain any ligands, are discussed in detail; (iv) means to avoid such mistakes and the implications for database integrity are discussed and (v) some suggestions as to how journal editors could help to expunge errors from the Protein Data Bank are provided.

Exploring Approaches for Detecting Protein Functional Similarity within an Orthology-based Framework.

Protein functional similarity based on gene ontology (GO) annotations serves as a powerful tool when comparing proteins on a functional level in applications such as protein-protein interaction prediction, gene prioritization, and disease gene discovery. Functional similarity (FS) is usually quantified by combining the GO hierarchy with an annotation corpus that links genes and gene products to GO terms. One large group of algorithms involves calculation of GO term semantic similarity (SS) between all the terms annotating the two proteins, followed by a second step, described as "mixing strategy", which involves combining the SS values to yield the final FS value. Due to the variability of protein annotation caused e.g. by annotation bias, this value cannot be reliably compared on an absolute scale. We therefore introduce a similarity z-score that takes into account the FS background distribution of each protein. For a selection of popular SS measures and mixing strategies we demonstrate moderate accuracy improvement when using z-scores in a benchmark that aims to separate orthologous cases from random gene pairs and discuss in this context the impact of annotation corpus choice. The approach has been implemented in Frela, a fast high-throughput public web server for protein FS calculation and interpretation.

FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees.

UNLABELLED: Familial aggregation analysis is the first fundamental step to perform when assessing the extent of genetic background of a disease. However, there is a lack of software to analyze the familial clustering of complex phenotypes in very large pedigrees. Such pedigrees can be utilized to calculate measures that express trait aggregation on both the family and individual level, providing valuable directions in choosing families for detailed follow-up studies. We developed FamAgg, an open source R package that contains both established and novel methods to investigate familial aggregation of traits in large pedigrees. We demonstrate its use and interpretation by analyzing a publicly available cancer dataset with more than 20 000 participants distributed across approximately 400 families. AVAILABILITY AND IMPLEMENTATION: The FamAgg package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg CONTACT: Christian.Weichenberger@eurac.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.