A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.
A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.
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DOI：
10.1016/j.cels.2017.09.004
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发表时间：
2017-11-22
期刊：
影响因子：
9.3
通讯作者：
Margolin AA
中科院分区：
文献类型：
--
作者：
Gönen M;Weir BA;Cowley GS;Vazquez F;Guan Y;Jaiswal A;Karasuyama M;Uzunangelov V;Wang T;Tsherniak A;Howell S;Marbach D;Hoff B;Norman TC;Airola A;Bivol A;Bunte K;Carlin D;Chopra S;Deran A;Ellrott K;Gopalacharyulu P;Graim K;Kaski S;Khan SA;Newton Y;Ng S;Pahikkala T;Paull E;Sokolov A;Tang H;Tang J;Wennerberg K;Xie Y;Zhan X;Zhu F;Broad-DREAM Community;Aittokallio T;Mamitsuka H;Stuart JM;Boehm JS;Root DE;Xiao G;Stolovitzky G;Hahn WC;Margolin AA
我们报告了一项DREAM挑战的结果，该挑战旨在基于一个新的数据集来预测相对遗传必要性，该数据集测试了98，000个shRNA对149个分子特征的癌细胞系。我们在4个月的时间里分析了3,000多份提交的结果。我们发现，将多个基因的重要性数据相结合的算法显示出更高的准确性;基因表达是信息量最大的分子数据类型;被预测基因的身份远比建模策略重要;预测良好的基因和选定的分子特征显示出功能类别的富集;经常选择的表达特征与原发性肿瘤的生存相关。这项研究建立了基因重要性预测的基准，提出了一个社区资源，为未来的比较与此基准，并提供了深入了解影响因素的能力，预测基因的重要性，从功能遗传筛选。这项研究还证明了公开发布出版前数据以使社区参与开放式研究合作的价值。
We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens. This study also demonstrates the value of releasing pre-publication data publicly to engage the community in an open research collaboration.
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影响因子：
64.5
作者：
Basu A;Bodycombe NE;Cheah JH;Price EV;Liu K;Schaefer GI;Ebright RY;Stewart ML;Ito D;Wang S;Bracha AL;Liefeld T;Wawer M;Gilbert JC;Wilson AJ;Stransky N;Kryukov GV;Dancik V;Barretina J;Garraway LA;Hon CS;Munoz B;Bittker JA;Stockwell BR;Khabele D;Stern AM;Clemons PA;Shamji AF;Schreiber SL
通讯作者：
Schreiber SL
DOI：
10.1038/nrc1299
发表时间：
2004-03
期刊：
Nature reviews. Cancer
影响因子：
--
作者：
通讯作者：
--
影响因子：
12.3
作者：
Boutros PC;Margolin AA;Stuart JM;Califano A;Stolovitzky G
通讯作者：
Stolovitzky G
影响因子：
56.9
作者：
Liu, JD;Carmell, MA;Hannon, GJ
通讯作者：
Hannon, GJ
影响因子：
30.8
作者：
Ciriello, Giovanni;Miller, Martin L.;Aksoy, Buelent Arman;Senbabaoglu, Yasin;Schultz, Nikolaus;Sander, Chris
通讯作者：
Sander, Chris