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2. Multi-platform discovery of haplotype-resolved structural variation in human genomes.

Author

Chaisson, Mark JP, Sanders, Ashley D, Zhao, Xuefang, Malhotra, Ankit, Porubsky, David, Rausch, Tobias, Gardner, Eugene J, Rodriguez, Oscar L, Guo, Li, Collins, Ryan L, Fan, Xian, Wen, Jia, Handsaker, Robert E, Fairley, Susan, Kronenberg, Zev N, Kong, Xiangmeng, Hormozdiari, Fereydoun, Lee, Dillon, Wenger, Aaron M, Hastie, Alex R, Antaki, Danny, Anantharaman, Thomas, Audano, Peter A, Brand, Harrison, Cantsilieris, Stuart, Cao, Han, Cerveira, Eliza, Chen, Chong, Chen, Xintong, Chin, Chen-Shan, Chong, Zechen, Chuang, Nelson T, Lambert, Christine C, Church, Deanna M, Clarke, Laura, Farrell, Andrew, Flores, Joey, Galeev, Timur, Gorkin, David U, Gujral, Madhusudan, Guryev, Victor, Heaton, William Haynes, Korlach, Jonas, Kumar, Sushant, Kwon, Jee Young, Lam, Ernest T, Lee, Jong Eun, Lee, Joyce, Lee, Wan-Ping, Lee, Sau Peng, Li, Shantao, Marks, Patrick, Viaud-Martinez, Karine, Meiers, Sascha, Munson, Katherine M, Navarro, Fabio CP, Nelson, Bradley J, Nodzak, Conor, Noor, Amina, Kyriazopoulou-Panagiotopoulou, Sofia, Pang, Andy WC, Qiu, Yunjiang, Rosanio, Gabriel, Ryan, Mallory, Stütz, Adrian, Spierings, Diana CJ, Ward, Alistair, Welch, AnneMarie E, Xiao, Ming, Xu, Wei, Zhang, Chengsheng, Zhu, Qihui, Zheng-Bradley, Xiangqun, Lowy, Ernesto, Yakneen, Sergei, McCarroll, Steven, Jun, Goo, Ding, Li, Koh, Chong Lek, Ren, Bing, Flicek, Paul, Chen, Ken, Gerstein, Mark B, Kwok, Pui-Yan, Lansdorp, Peter M, Marth, Gabor T, Sebat, Jonathan, Shi, Xinghua, Bashir, Ali, Ye, Kai, Devine, Scott E, Talkowski, Michael E, Mills, Ryan E, Marschall, Tobias, Korbel, Jan O, Eichler, Evan E, and Lee, Charles

Subjects
Humans, Chromosome Mapping, Genomics, Haplotypes, Genome, Human, Algorithms, Databases, Genetic, INDEL Mutation, Genomic Structural Variation, High-Throughput Nucleotide Sequencing, Whole Genome Sequencing, Genome, Human, Databases, Genetic
Abstract

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (

Published
2019

3. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder

Author

An, Joon-Yong, Lin, Kevin, Zhu, Lingxue, Werling, Donna M, Dong, Shan, Brand, Harrison, Wang, Harold Z, Zhao, Xuefang, Schwartz, Grace B, Collins, Ryan L, Currall, Benjamin B, Dastmalchi, Claudia, Dea, Jeanselle, Duhn, Clif, Gilson, Michael C, Klei, Lambertus, Liang, Lindsay, Markenscoff-Papadimitriou, Eirene, Pochareddy, Sirisha, Ahituv, Nadav, Buxbaum, Joseph D, Coon, Hilary, Daly, Mark J, Kim, Young Shin, Marth, Gabor T, Neale, Benjamin M, Quinlan, Aaron R, Rubenstein, John L, Sestan, Nenad, State, Matthew W, Willsey, A Jeremy, Talkowski, Michael E, Devlin, Bernie, Roeder, Kathryn, and Sanders, Stephan J

Subjects
Human Genome, Genetics, Biotechnology, Intellectual and Developmental Disabilities (IDD), Mental Health, Brain Disorders, Autism, Pediatric, 2.1 Biological and endogenous factors, Aetiology, Mental health, Autism Spectrum Disorder, Binding Sites, Conserved Sequence, DNA Mutational Analysis, Genetic Loci, Genetic Variation, Humans, Mutation, Pedigree, Promoter Regions, Genetic, Risk, Transcription Factors, General Science & Technology
Abstract

Whole-genome sequencing (WGS) has facilitated the first genome-wide evaluations of the contribution of de novo noncoding mutations to complex disorders. Using WGS, we identified 255,106 de novo mutations among sample genomes from members of 1902 quartet families in which one child, but not a sibling or their parents, was affected by autism spectrum disorder (ASD). In contrast to coding mutations, no noncoding functional annotation category, analyzed in isolation, was significantly associated with ASD. Casting noncoding variation in the context of a de novo risk score across multiple annotation categories, however, did demonstrate association with mutations localized to promoter regions. We found that the strongest driver of this promoter signal emanates from evolutionarily conserved transcription factor binding sites distal to the transcription start site. These data suggest that de novo mutations in promoter regions, characterized by evolutionary and functional signatures, contribute to ASD.

Published
2018

4. An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder

Author

Werling, Donna M, Brand, Harrison, An, Joon-Yong, Stone, Matthew R, Zhu, Lingxue, Glessner, Joseph T, Collins, Ryan L, Dong, Shan, Layer, Ryan M, Markenscoff-Papadimitriou, Eirene, Farrell, Andrew, Schwartz, Grace B, Wang, Harold Z, Currall, Benjamin B, Zhao, Xuefang, Dea, Jeanselle, Duhn, Clif, Erdman, Carolyn A, Gilson, Michael C, Yadav, Rachita, Handsaker, Robert E, Kashin, Seva, Klei, Lambertus, Mandell, Jeffrey D, Nowakowski, Tomasz J, Liu, Yuwen, Pochareddy, Sirisha, Smith, Louw, Walker, Michael F, Waterman, Matthew J, He, Xin, Kriegstein, Arnold R, Rubenstein, John L, Sestan, Nenad, McCarroll, Steven A, Neale, Benjamin M, Coon, Hilary, Willsey, A Jeremy, Buxbaum, Joseph D, Daly, Mark J, State, Matthew W, Quinlan, Aaron R, Marth, Gabor T, Roeder, Kathryn, Devlin, Bernie, Talkowski, Michael E, and Sanders, Stephan J

Subjects
Biological Sciences, Genetics, Human Genome, Biotechnology, Brain Disorders, Intellectual and Developmental Disabilities (IDD), Mental Health, Autism, 2.1 Biological and endogenous factors, Autism Spectrum Disorder, Female, Genetic Predisposition to Disease, Genome, Genome-Wide Association Study, Humans, INDEL Mutation, Male, Polymorphism, Single Nucleotide, Protein Isoforms, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.

Published
2018

5. A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology

Author

Guillen, Katrin P., Fujita, Maihi, Butterfield, Andrew J., Scherer, Sandra D., Bailey, Matthew H., Chu, Zhengtao, DeRose, Yoko S., Zhao, Ling, Cortes-Sanchez, Emilio, Yang, Chieh-Hsiang, Toner, Jennifer, Wang, Guoying, Qiao, Yi, Huang, Xiaomeng, Greenland, Jeffery A., Vahrenkamp, Jeffery M., Lum, David H., Factor, Rachel E., Nelson, Edward W., Matsen, Cindy B., Poretta, Jane M., Rosenthal, Regina, Beck, Anna C., Buys, Saundra S., Vaklavas, Christos, Ward, John H., Jensen, Randy L., Jones, Kevin B., Li, Zheqi, Oesterreich, Steffi, Dobrolecki, Lacey E., Pathi, Satya S., Woo, Xing Yi, Berrett, Kristofer C., Wadsworth, Mark E., Chuang, Jeffrey H., Lewis, Michael T., Marth, Gabor T., Gertz, Jason, Varley, Katherine E., Welm, Bryan E., and Welm, Alana L.

Published
2022
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7. A global reference for human genetic variation

Author

Auton, Adam, Abecasis, Gonçalo R, Altshuler, David M, Durbin, Richard M, Bentley, David R, Chakravarti, Aravinda, Clark, Andrew G, Donnelly, Peter, Eichler, Evan E, Flicek, Paul, Gabriel, Stacey B, Gibbs, Richard A, Green, Eric D, Hurles, Matthew E, Knoppers, Bartha M, Korbel, Jan O, Lander, Eric S, Lee, Charles, Lehrach, Hans, Mardis, Elaine R, Marth, Gabor T, McVean, Gil A, Nickerson, Deborah A, Schmidt, Jeanette P, Sherry, Stephen T, Wang, Jun, Wilson, Richard K, Barnes, Kathleen C, Beiswanger, Christine, Burchard, Esteban G, Bustamante, Carlos D, Cai, Hongyu, Cao, Hongzhi, Gerry, Norman P, Gharani, Neda, Gignoux, Christopher R, Gravel, Simon, Henn, Brenna, Jones, Danielle, Jorde, Lynn, Kaye, Jane S, Keinan, Alon, Kent, Alastair, Kerasidou, Angeliki, Li, Yingrui, Mathias, Rasika, Moreno-Estrada, Andres, Ossorio, Pilar N, Parker, Michael, Resch, Alissa M, Rotimi, Charles N, Royal, Charmaine D, Sandoval, Karla, Su, Yeyang, Sudbrak, Ralf, Tian, Zhongming, Tishkoff, Sarah, Toji, Lorraine H, Tyler-Smith, Chris, Via, Marc, Wang, Yuhong, Yang, Huanming, Yang, Ling, Zhu, Jiayong, Brooks, Lisa D, Felsenfeld, Adam L, McEwen, Jean E, Vaydylevich, Yekaterina, Duncanson, Audrey, Dunn, Michael, Schloss, Jeffery A, Garrison, Erik P, Min Kang, Hyun, Marchini, Jonathan L, and McCarthy, Shane

Subjects
Human Genome, Genetics, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Datasets as Topic, Demography, Disease Susceptibility, Exome, Genetic Variation, Genetics, Medical, Genetics, Population, Genome, Human, Genome-Wide Association Study, Genomics, Genotype, Haplotypes, High-Throughput Nucleotide Sequencing, Humans, INDEL Mutation, Internationality, Physical Chromosome Mapping, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Rare Diseases, Reference Standards, Sequence Analysis, DNA, Genomes Project Consortium, General Science & Technology
Abstract

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

Published
2015

8. MOSAIK: A hash-based algorithm for accurate next-generation sequencing read mapping

Author

Lee, Wan-Ping, Stromberg, Michael, Ward, Alistair, Stewart, Chip, Garrison, Erik, and Marth, Gabor T.

Subjects
Quantitative Biology - Genomics, Quantitative Biology - Quantitative Methods
Abstract

This paper presents an accurate short-read mapper for next-generation sequencing data which is widely used in the 1000 Genomes Project, and human clinical and other species genome studies.

Published
2013
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11. SSW Library: An SIMD Smith-Waterman C/C++ Library for Use in Genomic Applications

Author

Zhao, Mengyao, Lee, Wan-Ping, Garrison, Erik, and Marth, Gabor T.

Subjects
Quantitative Biology - Genomics
Abstract

Summary: The Smith Waterman (SW) algorithm, which produces the optimal pairwise alignment between two sequences, is frequently used as a key component of fast heuristic read mapping and variation detection tools, but current implementations are either designed as monolithic protein database searching tools or are embedded into other tools. To facilitate easy integration of the fast Single Instruction Multiple Data (SIMD) SW algorithm into third party software, we wrote a C/C++ library, which extends Farrars Striped SW (SSW) to return alignment information in addition to the optimal SW score. Availability: SSW is available both as a C/C++ software library, as well as a stand alone alignment tool wrapping the librarys functionality at https://github.com/mengyao/Complete- Striped-Smith-Waterman-Library Contact: marth@bc.edu, Comment: 3 pages, 2 figures

Published
2012
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13. Genetic basis for phenotypic differences between different Toxoplasma gondii type I strains

Author

Yang, Ninghan, Farrell, Andrew, Niedelman, Wendy, Melo, Mariane, Lu, Diana, Julien, Lindsay, Marth, Gabor T, Gubbels, Marc-Jan, and Saeij, Jeroen PJ

Subjects
Microbiology, Biological Sciences, Genetics, Infectious Diseases, Biodefense, Biotechnology, Emerging Infectious Diseases, 2.1 Biological and endogenous factors, Infection, Good Health and Well Being, Animals, Fibroblasts, Gene Expression Regulation, Genes, Protozoan, HEK293 Cells, Humans, Interleukin-12 Subunit p40, Intracellular Membranes, Macrophages, Mice, NF-kappa B, Phenotype, Polymorphism, Single Nucleotide, Protein Transport, Protozoan Proteins, Species Specificity, Toxoplasma, Vacuoles, Type I strains, Comparative genomics, Transcriptomics, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundToxoplasma gondii has a largely clonal population in North America and Europe, with types I, II and III clonal lineages accounting for the majority of strains isolated from patients. RH, a particular type I strain, is most frequently used to characterize Toxoplasma biology. However, compared to other type I strains, RH has unique characteristics such as faster growth, increased extracellular survival rate and inability to form orally infectious cysts. Thus, to identify candidate genes that could account for these parasite phenotypic differences, we determined genetic differences and differential parasite gene expression between RH and another type I strain, GT1. Moreover, as differences in host cell modulation could affect Toxoplasma replication in the host, we determined differentially modulated host processes among the type I strains through host transcriptional profiling.ResultsThrough whole genome sequencing, we identified 1,394 single nucleotide polymorphisms (SNPs) and insertions/deletions (indels) between RH and GT1. These SNPs/indels together with parasite gene expression differences between RH and GT1 were used to identify candidate genes that could account for type I phenotypic differences. A polymorphism in dense granule protein, GRA2, determined RH and GT1 differences in the evasion of the interferon gamma response. In addition, host transcriptional profiling identified that genes regulated by NF-ĸB, such as interleukin (IL)-12p40, were differentially modulated by the different type I strains. We subsequently showed that this difference in NF-ĸB activation was due to polymorphisms in GRA15. Furthermore, we observed that RH, but not other type I strains, recruited phosphorylated IĸBα (a component of the NF-ĸB complex) to the parasitophorous vacuole membrane and this recruitment of p- IĸBα was partially dependent on GRA2.ConclusionsWe identified candidate parasite genes that could be responsible for phenotypic variation among the type I strains through comparative genomics and transcriptomics. We also identified differentially modulated host pathways among the type I strains, and these can serve as a guideline for future studies in examining the phenotypic differences among type I strains.

Published
2013

14. An integrated map of genetic variation from 1,092 human genomes.

Author

1000 Genomes Project Consortium, Abecasis, Goncalo R, Auton, Adam, Brooks, Lisa D, DePristo, Mark A, Durbin, Richard M, Handsaker, Robert E, Kang, Hyun Min, Marth, Gabor T, and McVean, Gil A

Subjects
Genomes Project Consortium, Humans, Transcription Factors, Genetics, Medical, Genetics, Population, Genomics, Evolution, Molecular, Sequence Deletion, Binding Sites, Conserved Sequence, Haplotypes, Polymorphism, Single Nucleotide, Alleles, Genome, Human, Continental Population Groups, Genetic Variation, Genome-Wide Association Study, Nucleotide Motifs, General Science & Technology
Abstract

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.

Published
2012

15. An integrated map of genetic variation from 1,092 human genomes

Author

McVean, Gil A, Altshuler (Co-Chair), David M, Durbin (Co-Chair), Richard M, Abecasis, Gonçalo R, Bentley, David R, Chakravarti, Aravinda, Clark, Andrew G, Donnelly, Peter, Eichler, Evan E, Flicek, Paul, Gabriel, Stacey B, Gibbs, Richard A, Green, Eric D, Hurles, Matthew E, Knoppers, Bartha M, Korbel, Jan O, Lander, Eric S, Lee, Charles, Lehrach, Hans, Mardis, Elaine R, Marth, Gabor T, Nickerson, Deborah A, Schmidt, Jeanette P, Sherry, Stephen T, Wang, Jun, and Wilson, Richard K

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Alleles, Binding Sites, Conserved Sequence, Evolution, Molecular, Genetic Variation, Genetics, Medical, Genetics, Population, Genome, Human, Genome-Wide Association Study, Genomics, Haplotypes, Humans, Nucleotide Motifs, Polymorphism, Single Nucleotide, Racial Groups, Sequence Deletion, Transcription Factors, Genomes Project Consortium, General Science & Technology
Abstract

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.

Published
2012

16. Mapping copy number variation by population-scale genome sequencing

Author

Mills, Ryan E, Walter, Klaudia, Stewart, Chip, Handsaker, Robert E, Chen, Ken, Alkan, Can, Abyzov, Alexej, Yoon, Seungtai Chris, Ye, Kai, Cheetham, R Keira, Chinwalla, Asif, Conrad, Donald F, Fu, Yutao, Grubert, Fabian, Hajirasouliha, Iman, Hormozdiari, Fereydoun, Iakoucheva, Lilia M, Iqbal, Zamin, Kang, Shuli, Kidd, Jeffrey M, Konkel, Miriam K, Korn, Joshua, Khurana, Ekta, Kural, Deniz, Lam, Hugo YK, Leng, Jing, Li, Ruiqiang, Li, Yingrui, Lin, Chang-Yun, Luo, Ruibang, Mu, Xinmeng Jasmine, Nemesh, James, Peckham, Heather E, Rausch, Tobias, Scally, Aylwyn, Shi, Xinghua, Stromberg, Michael P, Stütz, Adrian M, Urban, Alexander Eckehart, Walker, Jerilyn A, Wu, Jiantao, Zhang, Yujun, Zhang, Zhengdong D, Batzer, Mark A, Ding, Li, Marth, Gabor T, McVean, Gil, Sebat, Jonathan, Snyder, Michael, Wang, Jun, Ye, Kenny, Eichler, Evan E, Gerstein, Mark B, Hurles, Matthew E, Lee, Charles, McCarroll, Steven A, and Korbel, Jan O

Subjects
Biotechnology, Human Genome, Genetics, Generic health relevance, DNA Copy Number Variations, Gene Duplication, Genetic Predisposition to Disease, Genetics, Population, Genome, Human, Genomics, Genotype, Humans, Mutagenesis, Insertional, Reproducibility of Results, Sequence Analysis, DNA, Sequence Deletion, Genomes Project, General Science & Technology
Abstract

Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.

Published
2011

20. Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments

Author

Chamberlin, John T., Lee, Younghee, Marth, Gabor T., and Quinlan, Aaron R.

Abstract

A mechanistic understanding of the biological and technical factors that impact transcript measurements is essential to designing and analyzing single-cell and single-nucleus RNA sequencing experiments. Nuclei contain the same pre-mRNA population as cells, but they contain a small subset of the mRNAs. Nonetheless, early studies argued that single-nucleus analysis yielded results comparable to cellular samples if pre-mRNA measurements were included. However, typical workflows do not distinguish between pre-mRNA and mRNA when estimating gene expression, and variation in their relative abundances across cell types has received limited attention. These gaps are especially important given that incorporating pre-mRNA has become commonplace for both assays, despite known gene length bias in pre-mRNA capture. Here, we reanalyze public data sets from mouse and human to describe the mechanisms and contrasting effects of mRNA and pre-mRNA sampling on gene expression and marker gene selection in single-cell and single-nucleus RNA-seq. We show that pre-mRNA levels vary considerably among cell types, which mediates the degree of gene length bias and limits the generalizability of a recently published normalization method intended to correct for this bias. As an alternative, we repurpose an existing post hoc gene length–based correction method from conventional RNA-seq gene set enrichment analysis. Finally, we show that inclusion of pre-mRNA in bioinformatic processing can impart a larger effect than assay choice itself, which is pivotal to the effective reuse of existing data. These analyses advance our understanding of the sources of variation in single-cell and single-nucleus RNA-seq experiments and provide useful guidance for future studies.

Published
2024
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27. A global reference for human genetic variation

Author

Altshuler, David M., (Co-Chair), Durbin, Richard M., (Co-Chair, Principal Investigator), Donnelly, Peter, Green, Eric D., Nickerson, Deborah A., Boerwinkle, Eric, Doddapaneni, Harsha, Han, Yi, Korchina, Viktoriya, Kovar, Christie, Lee, Sandra, Muzny, Donna, Reid, Jeffrey G., Zhu, Yiming, Wang, Jun, (Principal Investigator), Chang, Yuqi, Feng, Qiang, Fang, Xiaodong, Guo, Xiaosen, Jian, Min, Jiang, Hui, Jin, Xin, Lan, Tianming, Li, Guoqing, Li, Jingxiang, Li, Yingrui, Liu, Shengmao, Liu, Xiao, Lu, Yao, Ma, Xuedi, Tang, Meifang, Wang, Bo, Wang, Guangbiao, Wu, Honglong, Wu, Renhua, Xu, Xun, Yin, Ye, Zhang, Dandan, Zhang, Wenwei, Zhao, Jiao, Zhao, Meiru, Zheng, Xiaole, Lander, Eric S., (Principal Investigator), Gabriel, Stacey B., (Co-Chair), Gupta, Namrata, Gharani, Neda, Toji, Lorraine H., Gerry, Norman P., Resch, Alissa M., Barker, Jonathan, Gil, Laurent, Hunt, Sarah E., Kelman, Gavin, Kulesha, Eugene, Leinonen, Rasko, McLaren, William M., Radhakrishnan, Rajesh, Roa, Asier, Smirnov, Dmitriy, Smith, Richard E., Streeter, Ian, Thormann, Anja, Toneva, Iliana, Vaughan, Brendan, Zheng-Bradley, Xiangqun, Bentley, David R., (Principal Investigator), Grocock, Russell, Humphray, Sean, James, Terena, Kingsbury, Zoya, Lehrach, Hans, (Principal Investigator), Sudbrak, Ralf, (Project Leader), Albrecht, Marcus W., Amstislavskiy, Vyacheslav S., Borodina, Tatiana A., Lienhard, Matthias, Mertes, Florian, Sultan, Marc, Timmermann, Bernd, Yaspo, Marie-Laure, Mardis, Elaine R., (Co-Principal Investigator) (Co-Chair), Wilson, Richard K., (Co-Principal Investigator), Fulton, Lucinda, Fulton, Robert, Ananiev, Victor, Belaia, Zinaida, Beloslyudtsev, Dimitriy, Bouk, Nathan, Chen, Chao, Church, Deanna, Cohen, Robert, Cook, Charles, Garner, John, Hefferon, Timothy, Kimelman, Mikhail, Liu, Chunlei, Lopez, John, Meric, Peter, O’Sullivan, Chris, Ostapchuk, Yuri, Phan, Lon, Ponomarov, Sergiy, Schneider, Valerie, Shekhtman, Eugene, Sirotkin, Karl, Slotta, Douglas, Zhang, Hua, Balasubramaniam, Senduran, Burton, John, Danecek, Petr, Keane, Thomas M., Kolb-Kokocinski, Anja, McCarthy, Shane, Stalker, James, Quail, Michael, Schmidt, Jeanette P., (Principal Investigator), Davies, Christopher J., Gollub, Jeremy, Webster, Teresa, Wong, Brant, Zhan, Yiping, Auton, Adam, (Principal Investigator), Campbell, Christopher L., Kong, Yu, Marcketta, Anthony, Yu, Fuli, (Project Leader), Antunes, Lilian, Bainbridge, Matthew, Sabo, Aniko, Huang, Zhuoyi, Coin, Lachlan J. M., Fang, Lin, Li, Qibin, Li, Zhenyu, Lin, Haoxiang, Liu, Binghang, Luo, Ruibang, Shao, Haojing, Xie, Yinlong, Ye, Chen, Yu, Chang, Zhang, Fan, Zheng, Hancheng, Zhu, Hongmei, Alkan, Can, Dal, Elif, Kahveci, Fatma, Garrison, Erik P., (Project Lead), Kural, Deniz, Lee, Wan-Ping, Leong, Wen Fung, Stromberg, Michael, Ward, Alistair N., Wu, Jiantao, Zhang, Mengyao, Daly, Mark J., (Principal Investigator), DePristo, Mark A., (Project Leader), Handsaker, Robert E., (Project Leader), Banks, Eric, Bhatia, Gaurav, del Angel, Guillermo, Genovese, Giulio, Li, Heng, Kashin, Seva, Nemesh, James C., Poplin, Ryan E., Yoon, Seungtai C., (Principal Investigator), Lihm, Jayon, Makarov, Vladimir, Clark, Andrew G., (Principal Investigator), Gottipati, Srikanth, Keinan, Alon, Rodriguez-Flores, Juan L., Rausch, Tobias, (Project Leader), Fritz, Markus H., Stütz, Adrian M., Beal, Kathryn, Datta, Avik, Herrero, Javier, Ritchie, Graham R. S., Zerbino, Daniel, Sabeti, Pardis C., (Principal Investigator), Shlyakhter, Ilya, Schaffner, Stephen F., Vitti, Joseph, Cooper, David N., (Principal Investigator), Ball, Edward V., Stenson, Peter D., Barnes, Bret, Bauer, Markus, Cheetham, Keira R., Cox, Anthony, Eberle, Michael, Kahn, Scott, Murray, Lisa, Peden, John, Shaw, Richard, Kenny, Eimear E., (Principal Investigator), Batzer, Mark A., (Principal Investigator), Konkel, Miriam K., Walker, Jerilyn A., MacArthur, Daniel G., (Principal Investigator), Lek, Monkol, Herwig, Ralf, Koboldt, Daniel C., Larson, David, Ye, Kai, Gravel, Simon, Swaroop, Anand, Chew, Emily, Lappalainen, Tuuli, (Principal Investigator), Erlich, Yaniv, (Principal Investigator), Gymrek, Melissa, Willems, Thomas Frederick, Simpson, Jared T., Shriver, Mark D., (Principal Investigator), Rosenfeld, Jeffrey A., (Principal Investigator), Montgomery, Stephen B., (Principal Investigator), De La Vega, Francisco M., (Principal Investigator), Byrnes, Jake K., Carroll, Andrew W., DeGorter, Marianne K., Lacroute, Phil, Maples, Brian K., Martin, Alicia R., Moreno-Estrada, Andres, Shringarpure, Suyash S., Zakharia, Fouad, Halperin, Eran, (Principal Investigator), Baran, Yael, Cerveira, Eliza, Hwang, Jaeho, Malhotra, Ankit, (Co-Project Lead), Plewczynski, Dariusz, Radew, Kamen, Romanovitch, Mallory, Zhang, Chengsheng, (Co-Project Lead), Hyland, Fiona C. L., Craig, David W., (Principal Investigator), Christoforides, Alexis, Homer, Nils, Izatt, Tyler, Kurdoglu, Ahmet A., Sinari, Shripad A., Squire, Kevin, Xiao, Chunlin, Sebat, Jonathan, (Principal Investigator), Antaki, Danny, Gujral, Madhusudan, Noor, Amina, Ye, Kenny, Burchard, Esteban G., (Principal Investigator), Hernandez, Ryan D., (Principal Investigator), Gignoux, Christopher R., Haussler, David, (Principal Investigator), Katzman, Sol J., Kent, James W., Howie, Bryan, Ruiz-Linares, Andres, (Principal Investigator), Dermitzakis, Emmanouil T., (Principal Investigator), Devine, Scott E., (Principal Investigator), Abecasis, Gonçalo R., (Principal Investigator) (Co-Chair), Kang, Hyun Min, (Project Leader), Kidd, Jeffrey M., (Principal Investigator), Blackwell, Tom, Caron, Sean, Chen, Wei, Emery, Sarah, Fritsche, Lars, Fuchsberger, Christian, Jun, Goo, Li, Bingshan, Lyons, Robert, Scheller, Chris, Sidore, Carlo, Song, Shiya, Sliwerska, Elzbieta, Taliun, Daniel, Tan, Adrian, Welch, Ryan, Wing, Mary Kate, Zhan, Xiaowei, Awadalla, Philip, (Principal Investigator), Hodgkinson, Alan, Li, Yun, Shi, Xinghua, (Principal Investigator), Quitadamo, Andrew, Lunter, Gerton, (Principal Investigator), McVean, Gil A., (Principal Investigator) (Co-Chair), Marchini, Jonathan L., (Principal Investigator), Myers, Simon, (Principal Investigator), Churchhouse, Claire, Delaneau, Olivier, Gupta-Hinch, Anjali, Kretzschmar, Warren, Iqbal, Zamin, Mathieson, Iain, Menelaou, Androniki, Rimmer, Andy, Xifara, Dionysia K., Oleksyk, Taras K., (Principal Investigator), Fu, Yunxin, (Principal Investigator), Liu, Xiaoming, Xiong, Momiao, Jorde, Lynn, (Principal Investigator), Witherspoon, David, Xing, Jinchuan, Browning, Brian L., (Principal Investigator), Browning, Sharon R., (Principal Investigator), Hormozdiari, Fereydoun, Sudmant, Peter H., Khurana, Ekta, (Principal Investigator), Hurles, Matthew E., (Principal Investigator), Albers, Cornelis A., Ayub, Qasim, Chen, Yuan, Colonna, Vincenza, Jostins, Luke, Walter, Klaudia, Xue, Yali, Abyzov, Alexej, Balasubramanian, Suganthi, Chen, Jieming, Clarke, Declan, Fu, Yao, Harmanci, Arif O., Jin, Mike, Lee, Donghoon, Liu, Jeremy, Mu, Xinmeng Jasmine, Zhang, Jing, Zhang, Yan, McCarroll, Steven A., (Principal Investigator), Hartl, Chris, Shakir, Khalid, Degenhardt, Jeremiah, Korbel, Jan O., (Principal Investigator) (Co-Chair), Meiers, Sascha, Raeder, Benjamin, Casale, Francesco Paolo, Stegle, Oliver, Lameijer, Eric-Wubbo, Ding, Li, (Principal Investigator), Hall, Ira, Lee, Charles, (Principal Investigator) (Co-Chair), Bafna, Vineet, Michaelson, Jacob, Gardner, Eugene J., (Project Leader), Mills, Ryan E., (Principal Investigator), Dayama, Gargi, Chen, Ken, (Principle Investigator), Fan, Xian, Chong, Zechen, Chen, Tenghui, Eichler, Evan E., (Principal Investigator) (Co-Chair), Chaisson, Mark J., Huddleston, John, Malig, Maika, Nelson, Bradley J., Parrish, Nicholas F., Blackburne, Ben, Lindsay, Sarah J., Ning, Zemin, Zhang, Yujun, Lam, Hugo, Sisu, Cristina, Gibbs, Richard A., (Principal Investigator) (Co-Chair), Challis, Danny, Evani, Uday S., Lu, James, Nagaswamy, Uma, Yu, Jin, Li, Wangshen, Marth, Gabor T., (Principal Investigator) (Co-Chair), Habegger, Lukas, Yu, Haiyuan, (Principal Investigator), Cunningham, Fiona, Dunham, Ian, Lage, Kasper, (Principal Investigator), Jespersen, Jakob Berg, Horn, Heiko, Tyler-Smith, Chris, (Principal Investigator) (Co-Chair), Gerstein, Mark B., (Principal Investigator) (Co-Chair), Kim, Donghoon, Desalle, Rob, Narechania, Apurva, Wilson Sayres, Melissa A., Bustamante, Carlos D., (Principal Investigator) (Co-Chair), Mendez, Fernando L., Poznik, David G., Underhill, Peter A., Coin, Lachlan, (Principal Investigator), Mittelman, David, Banerjee, Ruby, Cerezo, Maria, Fitzgerald, Thomas W., Louzada, Sandra, Massaia, Andrea, Ritchie, Graham R., Yang, Fengtang, Kalra, Divya, Hale, Walker, Dan, Xu, Flicek, Paul, (Principal Investigator) (Co-Chair), Clarke, Laura, (Project Lead), Sherry, Stephen T., (Principal Investigator) (Co-Chair), Chakravarti, Aravinda, (Co-Chair), Knoppers, Bartha M., (Co-Chair), Barnes, Kathleen C., Beiswanger, Christine, Cai, Hongyu, Cao, Hongzhi, Henn, Brenna, Jones, Danielle, Kaye, Jane S., Kent, Alastair, Kerasidou, Angeliki, Mathias, Rasika, Ossorio, Pilar N., Parker, Michael, Rotimi, Charles N., Royal, Charmaine D., Sandoval, Karla, Su, Yeyang, Tian, Zhongming, Tishkoff, Sarah, Via, Marc, Wang, Yuhong, Yang, Ling, Zhu, Jiayong, Bodmer, Walter, Bedoya, Gabriel, Cai, Zhiming, Gao, Yang, Chu, Jiayou, Peltonen, Leena, Garcia-Montero, Andres, Orfao, Alberto, Dutil, Julie, Martinez-Cruzado, Juan C., Mathias, Rasika A., Hennis, Anselm, Watson, Harold, McKenzie, Colin, Qadri, Firdausi, LaRocque, Regina, Deng, Xiaoyan, Asogun, Danny, Folarin, Onikepe, Happi, Christian, Omoniwa, Omonwunmi, Stremlau, Matt, Tariyal, Ridhi, Jallow, Muminatou, Joof, Fatoumatta Sisay, Corrah, Tumani, Rockett, Kirk, Kwiatkowski, Dominic, Kooner, Jaspal, Hiê`n, Trâ`n Tinh, Dunstan, Sarah J., Hang, Nguyen Thuy, Fonnie, Richard, Garry, Robert, Kanneh, Lansana, Moses, Lina, Schieffelin, John, Grant, Donald S., Gallo, Carla, Poletti, Giovanni, Saleheen, Danish, Rasheed, Asif, Brooks, Lisa D., Felsenfeld, Adam L., McEwen, Jean E., Vaydylevich, Yekaterina, Duncanson, Audrey, Dunn, Michael, Schloss, Jeffery A., and Yang, Huanming

Published
2015
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30. A map of human genome variation from population-scale sequencing

Author

Durbin, Richard M., Altshuler, David L., Durbin, Richard M., Abecasis, Gonçalo R., Bentley, David R., Chakravarti, Aravinda, Clark, Andrew G., Collins, Francis S., De La Vega, Francisco M., Donnelly, Peter, Egholm, Michael, Flicek, Paul, Gabriel, Stacey B., Gibbs, Richard A., Knoppers, Bartha M., Lander, Eric S., Lehrach, Hans, Mardis, Elaine R., McVean, Gil A., Nickerson, Debbie A., Peltonen, Leena, Schafer, Alan J., Sherry, Stephen T., Wang, Jun, Wilson, Richard K., Gibbs, Richard A., Deiros, David, Metzker, Mike, Muzny, Donna, Reid, Jeff, Wheeler, David, Wang, Jun, Li, Jingxiang, Jian, Min, Li, Guoqing, Li, Ruiqiang, Liang, Huiqing, Tian, Geng, Wang, Bo, Wang, Jian, Wang, Wei, Yang, Huanming, Zhang, Xiuqing, Zheng, Huisong, Lander, Eric S., Altshuler, David L., Ambrogio, Lauren, Bloom, Toby, Cibulskis, Kristian, Fennell, Tim J., Gabriel, Stacey B., Jaffe, David B., Shefler, Erica, Sougnez, Carrie L., Bentley, David R., Gormley, Niall, Humphray, Sean, Kingsbury, Zoya, Koko-Gonzales, Paula, Stone, Jennifer, McKernan, Kevin J., Costa, Gina L., Ichikawa, Jeffry K., Lee, Clarence C., Sudbrak, Ralf, Lehrach, Hans, Borodina, Tatiana A., Dahl, Andreas, Davydov, Alexey N., Marquardt, Peter, Mertes, Florian, Nietfeld, Wilfiried, Rosenstiel, Philip, Schreiber, Stefan, Soldatov, Aleksey V., Timmermann, Bernd, Tolzmann, Marius, Egholm, Michael, Affourtit, Jason, Ashworth, Dana, Attiya, Said, Bachorski, Melissa, Buglione, Eli, Burke, Adam, Caprio, Amanda, Celone, Christopher, Clark, Shauna, Conners, David, Desany, Brian, Gu, Lisa, Guccione, Lorri, Kao, Kalvin, Kebbel, Andrew, Knowlton, Jennifer, Labrecque, Matthew, McDade, Louise, Mealmaker, Craig, Minderman, Melissa, Nawrocki, Anne, Niazi, Faheem, Pareja, Kristen, Ramenani, Ravi, Riches, David, Song, Wanmin, Turcotte, Cynthia, Wang, Shally, Mardis, Elaine R., Wilson, Richard K., Dooling, David, Fulton, Lucinda, Fulton, Robert, Weinstock, George, Durbin, Richard M., Burton, John, Carter, David M., Churcher, Carol, Coffey, Alison, Cox, Anthony, Palotie, Aarno, Quail, Michael, Skelly, Tom, Stalker, James, Swerdlow, Harold P., Turner, Daniel, De Witte, Anniek, Giles, Shane, Bainbridge, Matthew, Challis, Danny, Sabo, Aniko, Yu, Fuli, Yu, Jin, Fang, Xiaodong, Guo, Xiaosen, Li, Yingrui, Luo, Ruibang, Tai, Shuaishuai, Wu, Honglong, Zheng, Hancheng, Zheng, Xiaole, Zhou, Yan, Marth, Gabor T., Garrison, Erik P., Huang, Weichun, Indap, Amit, Kural, Deniz, Lee, Wan-Ping, Fung Leong, Wen, Quinlan, Aaron R., Stewart, Chip, Stromberg, Michael P., Ward, Alistair N., Wu, Jiantao, Lee, Charles, Mills, Ryan E., Shi, Xinghua, Daly, Mark J., DePristo, Mark A., Ball, Aaron D., Banks, Eric, Browning, Brian L., Garimella, Kiran V., Grossman, Sharon R., Handsaker, Robert E., Hanna, Matt, Hartl, Chris, Kernytsky, Andrew M., Korn, Joshua M., Li, Heng, Maguire, Jared R., McCarroll, Steven A., McKenna, Aaron, Nemesh, James C., Philippakis, Anthony A., Poplin, Ryan E., Price, Alkes, Rivas, Manuel A., Sabeti, Pardis C., Schaffner, Stephen F., Shlyakhter, Ilya A., Cooper, David N., Ball, Edward V., Mort, Matthew, Phillips, Andrew D., Stenson, Peter D., Sebat, Jonathan, Makarov, Vladimir, Ye, Kenny, Yoon, Seungtai C., Bustamante, Carlos D., Clark, Andrew G., Boyko, Adam, Degenhardt, Jeremiah, Gravel, Simon, Gutenkunst, Ryan N., Kaganovich, Mark, Keinan, Alon, Lacroute, Phil, Ma, Xin, Reynolds, Andy, Clarke, Laura, Flicek, Paul, Cunningham, Fiona, Herrero, Javier, Keenen, Stephen, Kulesha, Eugene, Leinonen, Rasko, McLaren, William M., Radhakrishnan, Rajesh, Smith, Richard E., Zalunin, Vadim, Zheng-Bradley, Xiangqun, Korbel, Jan O., Stütz, Adrian M., Humphray, Sean, Bauer, Markus, Cheetham, Keira R., Cox, Tony, Eberle, Michael, James, Terena, Kahn, Scott, Murray, Lisa, Ye, Kai, De La Vega, Francisco M., Fu, Yutao, Hyland, Fiona C. L., Manning, Jonathan M., McLaughlin, Stephen F., Peckham, Heather E., Sakarya, Onur, Sun, Yongming A., Tsung, Eric F., Batzer, Mark A., Konkel, Miriam K., Walker, Jerilyn A., Albrecht, Marcus W., Amstislavskiy, Vyacheslav S., Herwig, Ralf, Parkhomchuk, Dimitri V., Sherry, Stephen T., Agarwala, Richa, Khouri, Hoda M., Morgulis, Aleksandr O., Paschall, Justin E., Phan, Lon D., Rotmistrovsky, Kirill E., Sanders, Robert D., Shumway, Martin F., Xiao, Chunlin, McVean, Gil A., Auton, Adam, Iqbal, Zamin, Lunter, Gerton, Marchini, Jonathan L., Moutsianas, Loukas, Myers, Simon, Tumian, Afidalina, Desany, Brian, Knight, James, Winer, Roger, Craig, David W., Beckstrom-Sternberg, Steve M., Christoforides, Alexis, Kurdoglu, Ahmet A., Pearson, John V., Sinari, Shripad A., Tembe, Waibhav D., Haussler, David, Hinrichs, Angie S., Katzman, Sol J., Kern, Andrew, Kuhn, Robert M., Przeworski, Molly, Hernandez, Ryan D., Howie, Bryan, Kelley, Joanna L., Cord Melton, S., Abecasis, Gonçalo R., Li, Yun, Anderson, Paul, Blackwell, Tom, Chen, Wei, Cookson, William O., Ding, Jun, Min Kang, Hyun, Lathrop, Mark, Liang, Liming, Moffatt, Miriam F., Scheet, Paul, Sidore, Carlo, Snyder, Matthew, Zhan, Xiaowei, Zöllner, Sebastian, Awadalla, Philip, Casals, Ferran, Idaghdour, Youssef, Keebler, John, Stone, Eric A., Zilversmit, Martine, Jorde, Lynn, Xing, Jinchuan, Eichler, Evan E., Aksay, Gozde, Alkan, Can, Hajirasouliha, Iman, Hormozdiari, Fereydoun, Sahinalp, Cenk S., Sudmant, Peter H., Mardis, Elaine R., Chen, Ken, Chinwalla, Asif, Ding, Li, Koboldt, Daniel C., McLellan, Mike D., Wallis, John W., Wendl, Michael C., Zhang, Qunyuan, Albers, Cornelis A., Ayub, Qasim, Balasubramaniam, Senduran, Barrett, Jeffrey C., Chen, Yuan, Conrad, Donald F., Danecek, Petr, Dermitzakis, Emmanouil T., Hu, Min, Huang, Ni, Hurles, Matt E., Jin, Hanjun, Jostins, Luke, Keane, Thomas M., Quang Le, Si, Lindsay, Sarah, Long, Quan, MacArthur, Daniel G., Montgomery, Stephen B., Parts, Leopold, Tyler-Smith, Chris, Walter, Klaudia, Zhang, Yujun, Gerstein, Mark B., Snyder, Michael, Abyzov, Alexej, Balasubramanian, Suganthi, Bjornson, Robert, Du, Jiang, Grubert, Fabian, Habegger, Lukas, Haraksingh, Rajini, Jee, Justin, Khurana, Ekta, Lam, Hugo Y. K., Leng, Jing, Jasmine Mu, Xinmeng, Urban, Alexander E., Zhang, Zhengdong, Lee, Charles, McCarroll, Steven A., DePristo, Mark A., Korbel, Jan O., De La Vega, Francisco M., Blackwell, Tom, Eichler, Evan E., Kidd, Jeffrey M., Hurles, Matt E., Gibbs, Richard A., Coafra, Cristian, Dinh, Huyen, Kovar, Christie, Lee, Sandy, Nazareth, Lynne, Marth, Gabor T., Wilkinson, Jane, Flicek, Paul, Sherry, Stephen T., Abecasis, Gonçalo R., Mardis, Elaine R., Coffey, Allison, Scott, Carol, Gerstein, Mark B., Chakravarti, Aravinda, Knoppers, Bartha M., Bustamante, Carlos D., Gharani, Neda, Jorde, Lynn, Kaye, Jane S., Kent, Alastair, Li, Taosha, McGuire, Amy L., Ossorio, Pilar N., Rotimi, Charles N., Su, Yeyang, Toji, Lorraine H., Brooks, Lisa D., Felsenfeld, Adam L., McEwen, Jean E., Abdallah, Assya, Juenger, Christopher R., Clemm, Nicholas C., Duncanson, Audrey, Green, Eric D., Guyer, Mark S., and Peterson, Jane L.

Published
2010
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31. Extending reference assembly models

Author

Church, Deanna M, Schneider, Valerie A, Steinberg, Karyn Meltz, Schatz, Michael C, Quinlan, Aaron R, Chin, Chen-Shan, Kitts, Paul A, Aken, Bronwen, Marth, Gabor T, Hoffman, Michael M, Herrero, Javier, Mendoza, M Lisandra Zepeda, Durbin, Richard, and Flicek, Paul

Published
2015
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34. Novel temporal and spatial patterns of metastatic colonization from rapid-autopsy tumor biopsies

Author

Huang, Xiaomeng, primary, Qiao, Yi, additional, Brady, Samuel W., additional, Factor, Rachel E., additional, Downs-Kelly, Erinn, additional, Farrell, Andrew, additional, McQuerry, Jasmine A., additional, Shrestha, Gajendra, additional, Jenkins, David, additional, Johnson, W. Evan, additional, Cohen, Adam L., additional, Bild, Andrea H., additional, and Marth, Gabor T., additional

Published
2021
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36. A breast cancer patient-derived xenograft and organoid platform for drug discovery and precision oncology

Author

Guillen, Katrin P., primary, Fujita, Maihi, additional, Butterfield, Andrew J., additional, Scherer, Sandra D., additional, Bailey, Matthew H., additional, Chu, Zhengtao, additional, DeRose, Yoko S., additional, Zhao, Ling, additional, Cortes-Sanchez, Emilio, additional, Yang, Chieh-Hsiang, additional, Toner, Jennifer, additional, Wang, Guoying, additional, Qiao, Yi, additional, Huang, Xiaomeng, additional, Greenland, Jeffery A., additional, Vahrenkamp, Jeffery M., additional, Lum, David H., additional, Factor, Rachel E., additional, Nelson, Edward W., additional, Matsen, Cindy B., additional, Poretta, Jane M., additional, Rosenthal, Regina, additional, Beck, Anna C., additional, Buys, Saundra S., additional, Vaklavas, Christos, additional, Ward, John H., additional, Jensen, Randy L., additional, Jones, Kevin B., additional, Li, Zheqi, additional, Oesterreich, Steffi, additional, Dobrolecki, Lacey E., additional, Pathi, Satya S., additional, Woo, Xing Yi, additional, Berrett, Kristofer C., additional, Wadsworth, Mark E., additional, Chuang, Jeffrey H., additional, Lewis, Michael T., additional, Marth, Gabor T., additional, Gertz, Jason, additional, Varley, Katherine E., additional, Welm, Bryan E., additional, and Welm, Alana L., additional

Published
2021
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37. The allele frequency spectrum in genome-wide human variation data reveals signals of differential demographic history in three large world populations

Author

Marth, Gabor T., Czabarka, Eva, Murvai, Janos, and Sherry, Stephen T.

Subjects
Biological sciences
Abstract

We have studied a genome-wide set of single-nucleotide polymorphism (SNP) allele frequency measures for African-American, East Asian, and European-American samples. For this analysis we derived a simple, closed mathematical formulation for the spectrum of expected allele frequencies when the sampled populations have experienced nonstationary demographic histories. The direct calculation generates the spectrum orders of magnitude faster than coalescent simulations do and allows us to generate spectra for a large number of alternative histories on a multidimensional parameter grid. Model-fitting experiments using this grid reveal significant population-specific differences among the demographic histories that best describe the observed allele frequency spectra. European and Asian spectra show a bottleneck-shaped history: a reduction of effective population size in the past followed by a recent phase of size recovery. In contrast, the African-American spectrum shows a history of moderate but uninterrupted population expansion. These differences are expected to have profound consequences for the design of medical association studies. The analytical methods developed for this study, i.e., a closed mathematical formulation for the allele frequency spectrum, correcting the ascertainment bias introduced by shallow SNP sampling, and dealing with variable sample sizes provide a general framework for the analysis of public variation data.

Published
2004

40. The variant call format and VCFtools

Author

Danecek, Petr, Auton, Adam, Abecasis, Goncalo, Albers, Cornelis A., Banks, Eric, DePristo, Mark A., Handsaker, Robert E., Lunter, Gerton, Marth, Gabor T., Sherry, Stephen T., McVean, Gilean, and Durbin, Richard

Published
2011
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46. Copy Number Variation detection from 1000 Genomes project exon capture sequencing data

Author

Wu Jiantao, Grzeda Krzysztof R, Stewart Chip, Grubert Fabian, Urban Alexander E, Snyder Michael P, and Marth Gabor T

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background DNA capture technologies combined with high-throughput sequencing now enable cost-effective, deep-coverage, targeted sequencing of complete exomes. This is well suited for SNP discovery and genotyping. However there has been little attention devoted to Copy Number Variation (CNV) detection from exome capture datasets despite the potentially high impact of CNVs in exonic regions on protein function. Results As members of the 1000 Genomes Project analysis effort, we investigated 697 samples in which 931 genes were targeted and sampled with 454 or Illumina paired-end sequencing. We developed a rigorous Bayesian method to detect CNVs in the genes, based on read depth within target regions. Despite substantial variability in read coverage across samples and targeted exons, we were able to identify 107 heterozygous deletions in the dataset. The experimentally determined false discovery rate (FDR) of the cleanest dataset from the Wellcome Trust Sanger Institute is 12.5%. We were able to substantially improve the FDR in a subset of gene deletion candidates that were adjacent to another gene deletion call (17 calls). The estimated sensitivity of our call-set was 45%. Conclusions This study demonstrates that exonic sequencing datasets, collected both in population based and medical sequencing projects, will be a useful substrate for detecting genic CNV events, particularly deletions. Based on the number of events we found and the sensitivity of the methods in the present dataset, we estimate on average 16 genic heterozygous deletions per individual genome. Our power analysis informs ongoing and future projects about sequencing depth and uniformity of read coverage required for efficient detection.

Published
2012
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50. Expression divergence measured by transcriptome sequencing of four yeast species

Author

Busby Michele A, Gray Jesse M, Costa Allen M, Stewart Chip, Stromberg Michael P, Barnett Derek, Chuang Jeffrey H, Springer Michael, and Marth Gabor T

Subjects
RNA-Seq, Comparative transcriptomics, S. cerevisiae, S. paradoxus, S. mikatae, S. bayanus, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial. Results We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of Saccharomyces species grown under the same condition to investigate the evolution of gene expression. We found that variation in expression is gene-dependent with large variations in each gene's expression between replicates of the same species. This confounds the identification of genes differentially expressed across species. To address this, we developed a statistical approach to establish significance bounds for inter-species differential expression in RNA-Seq data based on the variance measured across biological replicates. This metric estimates the combined effects of technical and environmental variance, as well as Poisson sampling noise by isolating each component. Despite a paucity of large expression changes, we found a strong correlation between the variance of gene expression change and species divergence (R2 = 0.90). Conclusion We provide an improved methodology for measuring gene expression changes in evolutionary diverged species using RNA Seq, where experimental artifacts can mimic evolutionary effects. GEO Accession Number: GSE32679

Published
2011
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