The Library of Integrated Cellular Signatures (LINCS) project provides 
comprehensive transcriptome profiling of human cell lines before and after 
chemical and genetic perturbations. Its L1000 platform utilizes 978 landmark 
genes to infer the transcript levels of 14,292 genes computationally. Here we 
conducted the L1000 data quality control analysis by using MCF7, PC3, and A375 
cell lines as representative examples. Before perturbations, a promising 80% 
correlation in transcriptome was observed between L1000- and Affymetrix 
HU133A-platforms. After library-based shRNA perturbations, a moderate 30% of 
differentially expressed genes overlapped between any two selected controls 
viral vectors using the L1000 platform. The mitogen-activated protein kinase, 
vascular endothelial growth factor, and T-cell receptor pathways were identified 
as the most significantly shared pathways between chemical and genetic 
perturbations in cancer cells. In conclusion, L1000 platform is reliable in 
assessing transcriptome before perturbation. Its response to perturbagens needs 
to be interpreted with caution. A quality control analysis pipeline of L1000 is 
recommended before addressing biological questions.