4.8 Article

Pathway-level information extractor (PLIER) for gene expression data

期刊

NATURE METHODS
卷 16, 期 7, 页码 607-+

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/s41592-019-0456-1

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资金

  1. US National Institutes of Health (NIH) [U54HG008540, 5R03MH109008, 1R01HG009299, 5U19AI117873, 5U24DK112331]
  2. Netherlands Scientific Organization [904-61-090, 904-61-193, 480-04-004, 400-05-717]
  3. Netherlands Organisation for Scientific Research (NWO) Genomics [SPI 56-464-1419]
  4. Centre for Neurogenomics and Cognitive Research (CNCR-VU)
  5. European Union [EU/WLRT-2001-01254]
  6. ZonMW [10-000-1002]
  7. NIMH [RO1 MH059160]
  8. NESDA
  9. NTR

向作者/读者索取更多资源

A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in celltype proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER) (https://github. com/wgmao/PLIER and http://gobie. csb. pitt. edu/PLIER), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.

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