HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data.

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data.

Multi-region DNA sequencing of primary tumors and metastases from individual patients helps identify somatic aberrations driving cancer development. However, most methods to infer copy-number aberrations (CNAs) analyze individual samples. We introduce HATCHet2 to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 introduces a novel statistic, the mirrored haplotype B-allele frequency (mhBAF), to identify mirrored-subclonal CNAs having different numbers of copies of parental haplotypes in different tumor clones. HATCHet2 also has high accuracy in identifying focal CNAs and extends the earlier HATCHet method in several directions. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 50 prostate cancer samples from 10 patients reveals previously-unreported mirrored-subclonal CNAs affecting cancer genes.

Psychological status and uric acid levels in oral lichen planus patients - A case- control study.

BACKGROUND AND AIMS: Oral lichen planus (OLP) has varied etiology and clinical expression may be influenced simultaneously by different mechanisms. Psychological disturbances and oxidative stress are some such factors proposed in the etiopathogenesis of OLP. The aim was to assess the possible association of psychological traits like stress, anxiety, depression, serum and salivary uric acid levels with disease expression in OLP patients. METHODS: A case-control study was conducted in OLP subjects (n = 43) with a clinical and histopathological diagnosis, age and gender matched healthy controls (n = 42) to evaluate psychometric properties through DASS - 42 scale and uric acid (serum and salivary levels) evaluation through "Modified Trinder Method, End point" method. RESULTS: The mean depression, anxiety, stress scores in OLP group were 16.51 ± 7.21, 15.58 ± 6.78 and 15.05 ± 6.11 and the scores in control group were 6.31 ± 3.48, 5.02 ± 2.70 and 5.69 ± 3.39 respectively. The mean value of serum UA level and salivary UA level in OLP group were 4.70 ± 1.33 mg/dl and 5.25 ± 1.61 mg/dl respectively, while the corresponding scores in control group were 5.86 ± 1.12 mg/dl and 6.18 ± 1.28 mg/dl. CONCLUSION: OLP group had significantly higher depression, anxiety, stress and total scores. Mean serum and salivary uric acid levels were significantly lower in OLP subjects when compared with controls. CLINICAL RELEVANCE: Correction of psychological traits in oral lichen planus patients may significantly improve the clinical picture, while uric acid levels can be employed for biochemical evaluation in lichen planus patients to analyse oxidative stress.

Improving Metadata Infrastructure for Complex Surveys: Insights from the Fragile Families Challenge.

Researchers rely on metadata systems to prepare data for analysis. As the complexity of data sets increases and the breadth of data analysis practices grow, existing metadata systems can limit the efficiency and quality of data preparation. This article describes the redesign of a metadata system supporting the Fragile Families and Child Wellbeing Study on the basis of the experiences of participants in the Fragile Families Challenge. The authors demonstrate how treating metadata as data (i.e., releasing comprehensive information about variables in a format amenable to both automated and manual processing) can make the task of data preparation less arduous and less error prone for all types of data analysis. The authors hope that their work will facilitate new applications of machine-learning methods to longitudinal surveys and inspire research on data preparation in the social sciences. The authors have open-sourced the tools they created so that others can use and improve them.