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Nandita Mukhopadhyay
University of Pittsburgh
18Publications
7H-index
277Citations
Publications 19
Newest
Orofacial clefts (OFCs) are among the most prevalent craniofacial birth defects worldwide and create a significant public health burden. The majority of OFCs are non-syndromic, and the genetic etiology of non-syndromic OFCs is only partially determined. Here, we analyze whole genome sequence (WGS) data for association with risk of OFCs in European and Colombian families selected from a multicenter family-based OFC study. This is the first large-scale WGS study of OFC in parent–offspring trios, a...
Source
#1Manika Govil (University of Pittsburgh)H-Index: 7
#2Nandita Mukhopadhyay (University of Pittsburgh)H-Index: 7
Last.Debra L. Schutte (WSU: Wayne State University)H-Index: 5
view all 6 authors...
Source
#1Nandita Mukhopadhyay (University of Pittsburgh)H-Index: 7
#2Madison Bishop (Emory University)
Last.Mary L. Marazita (University of Pittsburgh)H-Index: 55
view all 19 authors...
Orofacial clefts (OFCs) are one of the most common birth defects worldwide and create a significant health burden. The majority of OFCs are non-syndromic, and the genetic component has been only partially determined. Here, we analyze whole genome sequence (WGS) data for association with risk of OFCs in European and Colombian families selected from a multicenter family-based OFC study. Part of the Gabriella Miller Kids First Pediatric Research Program, this is the first large-scale WGS study of O...
Source
#1Manika Govil (University of Pittsburgh)H-Index: 7
#2Nandita Mukhopadhyay (University of Pittsburgh)H-Index: 7
Last.Mary L. Marazita (University of Pittsburgh)H-Index: 55
view all 12 authors...
Background Dental caries is a common chronic disease among children and adults alike, posing a substantial health burden. Caries is affected by multiple genetic and environmental factors, and prior studies have found that a substantial proportion of caries susceptibility is genetically inherited.
1 CitationsSource
#1Nandita Mukhopadhyay (University of Pittsburgh)H-Index: 7
#2Janelle A. Noble (Children's Hospital Oakland Research Institute)H-Index: 32
Last.David A. Greenberg (OSU: Ohio State University)H-Index: 85
view all 5 authors...
There is a growing body of evidence suggesting that type 1 diabetes (T1D) is a genetically heterogeneous disease. However, the extent of this heterogeneity, and what observations may distinguish different forms, is unclear. One indicator may be T1D-related microvascular complications (MVCs), which are familial, but occur in some families, and not others. We tested the hypothesis that T1D plus MVC is genetically distinct from T1D without MCV. We studied 415 families (2,462 individuals, 896 with T...
2 CitationsSource
#1Zhen Zeng (University of Pittsburgh)H-Index: 16
#2Daniel E. Weeks (University of Pittsburgh)H-Index: 61
Last.Eleanor Feingold (University of Pittsburgh)H-Index: 41
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When genome-wide association studies (GWAS) or sequencing studies are performed on family-based datasets, the genotype data can be used to check the structure of putative pedigrees. Even in datasets of putatively unrelated people, close relationships can often be detected using dense single-nucleotide polymorphism/variant (SNP/SNV) data. A number of methods for finding relationships using dense genetic data exist, but they all have certain limitations, including that they typically use average g...
2 CitationsSource
#1Robert V. Baron (University of Pittsburgh)H-Index: 3
#2Charles Kollar (University of Pittsburgh)H-Index: 1
Last.Daniel E. Weeks (University of Pittsburgh)H-Index: 61
view all 4 authors...
In a typical study of the genetics of a complex human disease, many different analysis programs are used, to test for linkage and association. This requires extensive and careful data reformatting, as many of these analysis programs use differing input formats. Writing scripts to facilitate this can be tedious, time-consuming, and error-prone. To address these issues, the open source Mega2 data reformatting program provides validated and tested data conversions from several commonly-used input f...
4 CitationsSource
#1Candace D. Middlebrooks (Emory University)H-Index: 5
#2Nandita Mukhopadhyay (University of Pittsburgh)H-Index: 7
Last.Stephanie L. Sherman (Emory University)H-Index: 60
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In oocytes with nondisjoined chromosomes 21 due to a meiosis I (MI) error, recombination is significantly reduced along chromosome 21; several lines of evidence indicate that this contributes to the nondisjunction event. A pilot study found evidence that these oocytes also have reduced recombination genome-wide when compared with controls. This suggests that factors that act globally may be contributing to the reduced recombination on chromosome 21, and hence, the nondisjunction event. To identi...
8 CitationsSource
#1Samsiddhi Bhattacharjee (University of Pittsburgh)H-Index: 9
#2Chia-Ling Kuo (University of Pittsburgh)H-Index: 4
Last.Eleanor Feingold (University of Pittsburgh)H-Index: 41
view all 6 authors...
The traditional variance components approach for quantitative trait locus (QTL) linkage analysis is sensitive to violations of normality and fails for selected sampling schemes. Recently, a number of new methods have been developed for QTL mapping in humans. Most of the new methods are based on score statistics or regression-based statistics and are expected to be relatively robust to non-normality of the trait distribution and also to selected sampling, at least in terms of type I error. Wherea...
11 CitationsSource
#1Nandita Mukhopadhyay (University of Pittsburgh)H-Index: 7
#2Indrani Halder (University of Pittsburgh)H-Index: 21
Last.Daniel E. Weeks (University of Pittsburgh)H-Index: 61
view all 4 authors...
Rheumatoid arthritis (RA) is a multifactorial disease with complex genetic etiology, about which little is known. Here, we apply a two-stage procedure in which a quick first-stage analysis was used to narrow down targets for a more thorough and detailed testing for gene × gene interaction. Potentially interesting regions were first identified by testing for major gene effects using non-parametric linkage methods. To select regions of interest, we first tested for linkage to three different RA-re...
2 CitationsSource
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