PyQMC: An all-Python real-space quantum Monte Carlo module in PySCF.

We describe a new open-source Python-based package for high accuracy correlated electron calculations using quantum Monte Carlo (QMC) in real space: PyQMC. PyQMC implements modern versions of QMC algorithms in an accessible format, enabling algorithmic development and easy implementation of complex workflows. Tight integration with the PySCF environment allows for a simple comparison between QMC calculations and other many-body wave function techniques, as well as access to high accuracy trial wave functions.

Genome-wide association study identifies the GLDC/IL33 locus associated with survival of osteosarcoma patients.

Survival rates for osteosarcoma, the most common primary bone cancer, have changed little over the past three decades and are particularly low for patients with metastatic disease. We conducted a multi-institutional genome-wide association study (GWAS) to identify germline genetic variants associated with overall survival in 632 patients with osteosarcoma, including 523 patients of European ancestry and 109 from Brazil. We conducted a time-to-event analysis and estimated hazard ratios (HR) and 95% confidence intervals (CI) using Cox proportional hazards models, with and without adjustment for metastatic disease.

Genome-Wide Association Study to Identify Susceptibility Loci That Modify Radiation-Related Risk for Breast Cancer After Childhood Cancer.

Background: Childhood cancer survivors treated with chest-directed radiotherapy have substantially elevated risk for developing breast cancer. Although genetic susceptibility to breast cancer in the general population is well studied, large-scale evaluation of breast cancer susceptibility after chest-directed radiotherapy for childhood cancer is lacking.

Methods: We conducted a genome-wide association study of breast cancer in female survivors of childhood cancer, pooling two cohorts with detailed treatment data and systematic, long-term follow-up: the Childhood Cancer Survivor Study and St.

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry.

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.

Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types.

Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.

Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients.

Joint analysis of three genome-wide association studies of esophageal squamous cell carcinoma in Chinese populations.

We conducted a joint (pooled) analysis of three genome-wide association studies (GWAS) of esophageal squamous cell carcinoma (ESCC) in individuals of Chinese ancestry (5,337 ESCC cases and 5,787 controls) with 9,654 ESCC cases and 10,058 controls for follow-up. In a logistic regression model adjusted for age, sex, study and two eigenvectors, two new loci achieved genome-wide significance, marked by rs7447927 at 5q31.2 (per-allele odds ratio (OR) = 0.

A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits.

Pooling genome-wide association studies (GWASs) increases power but also poses methodological challenges because studies are often heterogeneous. For example, combining GWASs of related but distinct traits can provide promising directions for the discovery of loci with small but common pleiotropic effects. Classical approaches for meta-analysis or pooled analysis, however, might not be suitable for such analysis because individual variants are likely to be associated with only a subset of the traits or might demonstrate effects in different directions.

Geographic heterogeneity of prevalence of the human herpesvirus 8 in sub-Saharan Africa: clues about etiology.

Purpose: Human herpesvirus 8 (HHV-8, or Kaposi sarcoma [KS]-associated herpesvirus, KSHV) is a necessary but insufficient cause of KS, as KS develops in few HHV-8-infected persons. In sub-Saharan Africa, marked differences in the geographic distribution of HHV-8 and KS suggest that environmental cofactors influence HHV-8 transmission, control, and progression to KS. However, a direct comparison of HHV-8 prevalence estimates is complicated because studies used different serologic assays and analytic methods.