LCE: an open web portal to explore gene expression and clinical associations in lung cancer

Ling Cai; Shin Yi Lin; Luc Girard; Yunyun Zhou; Lin Yang; Bo Ci; Qinbo Zhou; Danni Luo; Bo Yao; Hao Tang; Jeffrey Allen; Kenneth Huffman; Adi Gazdar; John Heymach; Ignacio Wistuba; Guanghua Xiao; John Minna; Yang Xie

doi:10.1038/s41388-018-0588-2

LCE: an open web portal to explore gene expression and clinical associations in lung cancer

Ling Cai, Shin Yi Lin, Luc Girard, Yunyun Zhou, Lin Yang, Bo Ci, Qinbo Zhou, Danni Luo, Bo Yao, Hao Tang, Jeffrey Allen, Kenneth Huffman, Adi Gazdar, John Heymach, Ignacio Wistuba, Guanghua Xiao, John Minna, Yang Xie

Research output: Contribution to journal › Article › peer-review

64 Scopus citations

Abstract

We constructed a lung cancer-specific database housing expression data and clinical data from over 6700 patients in 56 studies. Expression data from 23 genome-wide platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource—the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs non-malignant tissue (normal) differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.

Original language	English (US)
Pages (from-to)	2551-2564
Number of pages	14
Journal	Oncogene
Volume	38
Issue number	14
DOIs	https://doi.org/10.1038/s41388-018-0588-2
State	Published - Apr 4 2019

ASJC Scopus subject areas

Molecular Biology
Genetics
Cancer Research

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title = "LCE: an open web portal to explore gene expression and clinical associations in lung cancer",

abstract = "We constructed a lung cancer-specific database housing expression data and clinical data from over 6700 patients in 56 studies. Expression data from 23 genome-wide platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource—the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs non-malignant tissue (normal) differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.",

author = "Ling Cai and Lin, {Shin Yi} and Luc Girard and Yunyun Zhou and Lin Yang and Bo Ci and Qinbo Zhou and Danni Luo and Bo Yao and Hao Tang and Jeffrey Allen and Kenneth Huffman and Adi Gazdar and John Heymach and Ignacio Wistuba and Guanghua Xiao and John Minna and Yang Xie",

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doi = "10.1038/s41388-018-0588-2",

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T2 - an open web portal to explore gene expression and clinical associations in lung cancer

AU - Cai, Ling

AU - Lin, Shin Yi

AU - Girard, Luc

AU - Zhou, Yunyun

AU - Yang, Lin

AU - Ci, Bo

AU - Zhou, Qinbo

AU - Luo, Danni

AU - Yao, Bo

AU - Tang, Hao

AU - Allen, Jeffrey

AU - Huffman, Kenneth

AU - Gazdar, Adi

AU - Heymach, John

AU - Wistuba, Ignacio

AU - Xiao, Guanghua

AU - Minna, John

AU - Xie, Yang

PY - 2019/4/4

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AB - We constructed a lung cancer-specific database housing expression data and clinical data from over 6700 patients in 56 studies. Expression data from 23 genome-wide platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource—the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs non-malignant tissue (normal) differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.

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LCE: an open web portal to explore gene expression and clinical associations in lung cancer

Abstract

ASJC Scopus subject areas

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