A general framework for predicting the transcriptomic consequences of non-coding variation
A general framework for predicting the transcriptomic consequences of non-coding variation
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预测非编码变异转录组后果的通用框架
DOI：
10.1101/279323
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Abdalla M
中科院分区：
文献类型：
--
作者：
Abdalla M
复杂性状的全基因组关联研究（GWAS）涉及数千个遗传位点。大多数GWAS提名的变体位于非编码区，使这些发现到功能理解的系统翻译变得复杂。在这里，我们利用卷积神经网络来帮助应对这一挑战。我们的计算框架peaBrain将组织的转录机制建模为两个阶段的过程：第一，预测所有基因的平均组织特异性丰度，第二，将基因型变异的转录组学后果结合起来，以逐个主题的方式预测个体丰度。我们证明，peaBrain占大多数组织中平均转录本丰度观察到的方差的大部分（>50%），并且在预测个体基因型变异的后果方面优于正则化线性模型。我们通过计算与核苷酸进化约束相关的非编码影响分数来强调peaBrain模型的有效性，这些核苷酸进化约束也预测疾病相关变异和等位基因特异性转录因子结合。我们进一步展示了如何利用这些组织特异性peaBrain评分来确定复杂性状背后的功能组织，优于依赖于eQTL和GWAS信号共定位的方法。随后，我们推导出用于下游应用的基因的连续密集嵌入，并确定了高通量实验方法所错过的pupillary功能eQTL。
Genome wide association studies (GWASs) for complex traits have implicated thousands of genetic loci. Most GWAS-nominated variants lie in noncoding regions, complicating the systematic translation of these findings into functional understanding. Here, we leverage convolutional neural networks to assist in this challenge. Our computational framework, peaBrain, models the transcriptional machinery of a tissue as a two-stage process: first, predicting the mean tissue specific abundance of all genes and second, incorporating the transcriptomic consequences of genotype variation to predict individual abundance on a subject-by-subject basis. We demonstrate that peaBrain accounts for the majority (>50%) of variance observed in mean transcript abundance across most tissues and outperforms regularized linear models in predicting the consequences of individual genotype variation. We highlight the validity of the peaBrain model by calculating non-coding impact scores that correlate with nucleotide evolutionary constraint that are also predictive of disease-associated variation and allele-specific transcription factor binding. We further show how these tissue-specific peaBrain scores can be leveraged to pinpoint functional tissues underlying complex traits, outperforming methods that depend on colocalization of eQTL and GWAS signals. We subsequently derive continuous dense embeddings of genes for downstream applications, and identify putatively functional eQTLs that are missed by high-throughput experimental approaches.
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等位基因特异性转录因子结合作为评估变异影响预测因子的基准
DOI：
10.1101/253427
发表时间：
2018
期刊：
bioRxiv
影响因子：
--
作者：
O. Wagih;D. Merico;Andrew Delong;B. Frey
通讯作者：
B. Frey
影响因子：
30.8
作者：
Willer, Cristen J;Schmidt, Ellen M;Sengupta, Sebanti;Peloso, Gina M;Gustafsson, Stefan;Kanoni, Stavroula;Ganna, Andrea;Chen, Jin;Buchkovich, Martin L;Mora, Samia;Beckmann, Jacques S;Bragg-Gresham, Jennifer L;Chang, Hsing-Yi;Demirkan, Ayse;Den Hertog, Heleen M;Do, Ron;Donnelly, Louise A;Ehret, Georg B;Esko, Tonu;Feitosa, Mary F;Ferreira, Teresa;Fischer, Krista;Fontanillas, Pierre;Fraser, Ross M;Freitag, Daniel F;Gurdasani, Deepti;Heikkila, Kauko;Hypponen, Elina;Isaacs, Aaron;Jackson, Anne U;Johansson, Asa;Johnson, Toby;Kaakinen, Marika;Kettunen, Johannes;Kleber, Marcus E;Li, Xiaohui;Luan, Jian'an;Lyytikainen, Leo-Pekka;Magnusson, Patrik K E;Mangino, Massimo;Mihailov, Evelin;Montasser, May E;Muller-Nurasyid, Martina;Nolte, Ilja M;O'Connell, Jeffrey R;Palmer, Cameron D;Perola, Markus;Petersen, Ann-Kristin;Sanna, Serena;Saxena, Richa;Service, Susan K;Shah, Sonia;Shungin, Dmitry;Sidore, Carlo;Song, Ci;Strawbridge, Rona J;Surakka, Ida;Tanaka, Toshiko;Teslovich, Tanya M;Thorleifsson, Gudmar;Van den Herik, Evita G;Voight, Benjamin F;Volcik, Kelly A;Waite, Lindsay L;Wong, Andrew;Wu, Ying;Zhang, Weihua;Absher, Devin;Asiki, Gershim;Barroso, Ines;Been, Latonya F;Bolton, Jennifer L;Bonnycastle, Lori L;Brambilla, Paolo;Burnett, Mary S;Cesana, Giancarlo;Dimitriou, Maria;Doney, Alex S F;Doring, Angela;Elliott, Paul;Epstein, Stephen E;Ingi Eyjolfsson, Gudmundur;Gigante, Bruna;Goodarzi, Mark O;Grallert, Harald;Gravito, Martha L;Groves, Christopher J;Hallmans, Goran;Hartikainen, Anna-Liisa;Hayward, Caroline;Hernandez, Dena;Hicks, Andrew A;Holm, Hilma;Hung, Yi-Jen;Illig, Thomas;Jones, Michelle R;Kaleebu, Pontiano;Kastelein, John J P;Khaw, Kay-Tee;Kim, Eric;Klopp, Norman;Komulainen, Pirjo;Kumari, Meena;Langenberg, Claudia;Lehtimaki, Terho;Lin, Shih-Yi;Lindstrom, Jaana;Loos, Ruth J F;Mach, Francois;McArdle, Wendy L;Meisinger, Christa;Mitchell, Braxton D;Muller, Gabrielle;Nagaraja, Ramaiah;Narisu, Narisu;Nieminen, Tuomo V M;Nsubuga, Rebecca N;Olafsson, Isleifur;Ong, Ken K;Palotie, Aarno;Papamarkou, Theodore;Pomilla, Cristina;Pouta, Anneli;Rader, Daniel J;Reilly, Muredach P;Ridker, Paul M;Rivadeneira, Fernando;Rudan, Igor;Ruokonen, Aimo;Samani, Nilesh;Scharnagl, Hubert;Seeley, Janet;Silander, Kaisa;Stancakova, Alena;Stirrups, Kathleen;Swift, Amy J;Tiret, Laurence;Uitterlinden, Andre G;van Pelt, L Joost;Vedantam, Sailaja;Wainwright, Nicholas;Wijmenga, Cisca;Wild, Sarah H;Willemsen, Gonneke;Wilsgaard, Tom;Wilson, James F;Young, Elizabeth H;Zhao, Jing Hua;Adair, Linda S;Arveiler, Dominique;Assimes, Themistocles L;Bandinelli, Stefania;Bennett, Franklyn;Bochud, Murielle;Boehm, Bernhard O;Boomsma, Dorret I;Borecki, Ingrid B;Bornstein, Stefan R;Bovet, Pascal;Burnier, Michel;Campbell, Harry;Chakravarti, Aravinda;Chambers, John C;Chen, Yii-Der Ida;Collins, Francis S;Cooper, Richard S;Danesh, John;Dedoussis, George;de Faire, Ulf;Feranil, Alan B;Ferrieres, Jean;Ferrucci, Luigi;Freimer, Nelson B;Gieger, Christian;Groop, Leif C;Gudnason, Vilmundur;Gyllensten, Ulf;Hamsten, Anders;Harris, Tamara B;Hingorani, Aroon;Hirschhorn, Joel N;Hofman, Albert;Hovingh, G Kees;Hsiung, Chao Agnes;Humphries, Steve E;Hunt, Steven C;Hveem, Kristian;Iribarren, Carlos;Jarvelin, Marjo-Riitta;Jula, Antti;Kahonen, Mika;Kaprio, Jaakko;Kesaniemi, Antero;Kivimaki, Mika;Kooner, Jaspal S;Koudstaal, Peter J;Krauss, Ronald M;Kuh, Diana;Kuusisto, Johanna;Kyvik, Kirsten O;Laakso, Markku;Lakka, Timo A;Lind, Lars;Lindgren, Cecilia M;Martin, Nicholas G;Marz, Winfried;McCarthy, Mark I;McKenzie, Colin A;Meneton, Pierre;Metspalu, Andres;Moilanen, Leena;Morris, Andrew D;Munroe, Patricia B;Njolstad, Inger;Pedersen, Nancy L;Power, Chris;Pramstaller, Peter P;Price, Jackie F;Psaty, Bruce M;Quertermous, Thomas;Rauramaa, Rainer;Saleheen, Danish;Salomaa, Veikko;Sanghera, Dharambir K;Saramies, Jouko;Schwarz, Peter E H;Sheu, Wayne H-H;Shuldiner, Alan R;Siegbahn, Agneta;Spector, Tim D;Stefansson, Kari;Strachan, David P;Tayo, Bamidele O;Tremoli, Elena;Tuomilehto, Jaakko;Uusitupa, Matti;van Duijn, Cornelia M;Vollenweider, Peter;Wallentin, Lars;Wareham, Nicholas J;Whitfield, John B;Wolffenbuttel, Bruce H R;Ordovas, Jose M;Boerwinkle, Eric;Palmer, Colin N A;Thorsteinsdottir, Unnur;Chasman, Daniel I;Rotter, Jerome I;Franks, Paul W;Ripatti, Samuli;Cupples, L Adrienne;Sandhu, Manjinder S;Rich, Stephen S;Boehnke, Michael;Deloukas, Panos;Kathiresan, Sekar;Mohlke, Karen L;Ingelsson, Erik;Abecasis, Goncalo R
通讯作者：
Abecasis, Goncalo R
深度（呃）学习。
DOI：
10.1523/jneurosci.0153-18.2018
发表时间：
2018
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Srinivasan,Shyam;Greenspan,RalphJ;Stevens,CharlesF;Grover,Dhruv
通讯作者：
Grover,Dhruv
影响因子：
46.9
作者：
Alipanahi, Babak;Delong, Andrew;Frey, Brendan J.
通讯作者：
Frey, Brendan J.
影响因子：
30.8
作者：
Ongen, Halit;Brown, Andrew A.;Dermitzakis, Emmanouil T.
通讯作者：
Dermitzakis, Emmanouil T.