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Cancer Genomics Center


Bioinformatics Service


Our bioinformatics unit is designed to provide advanced bioinformatics services to researchers. We offer state-of-the-art genomics technologies, comprehensive and professional services, and multi-level professional training, enabling these services more efficient for your basic and translational research. Additionally, we provide consultation of study design, grant proposal development and post-sequencing analysis consultation. The team has experience in collaboration with more than 100 investigators, co-authored numerous publications (e.g. Nature Medicine, Cancer Discovery, Blood), and helped getting funding more than $100M.

Bioinformatics service

  • NGS data analysis (WGS, WES, microRNA, ChIP-seq, single cell RNA-seq data, methylation, etc.)
  • Array data analysis including GWAS, CNV and methylation data
  • Advanced bioinformatics services including gene set enrichment analysis (Gene Ontology, pathways, etc.), network analysis, disease association analysis, functional genomics analysis, results interpretation, machine learning and applications, databases, pharmacogenetics and pharmacogenomics data analysis, among others.

Other service:

  • Consultation on study design
  • Grant proposal development
  • NGS training in bioinformatics

Reference: Ding et al. Hum Mol Genet 2010, 19: R188–R196

Selected publications:

NGS for disease studies:

  1. Dahlman KB, Xia J, Hutchinson K, Ng C, Hucks D, Jia P, Atefi M, Su Z, Branch S, Lyle P, Hicks D, Bozon V, Glaspy J, Netterville JL, Vnencak-Jones C, Sosman J*, Ribas A*, Zhao Z*, Pao W* (2012) BRAF L597 mutations in melanoma are associated with sensitivity to MEK inhibitors. Cancer Discovery 2(9):791-797 [cover page] [WGS]
  2. Jia P, Jin H, Meador CB, Xia J, Ohashi K, Liu L, Pirazzoli V, Dahlman KB, Politi K, Michor F, Zhao Z*, Pao W* (2013) Next-generation sequencing of paired tyrosine kinase inhibitor-sensitive and -resistant EGFR mutant lung cancer cell lines identifies spectrum of DNA changes associated with drug resistance. Genome Research 23:1434-1445 [cover image/artwork of the issue] [WGS, WES, RNA-seq]
  3. Xia J, Jia P, Hutchinson KE, Dahlman KB, Johnson D, Sosman J, Pao W, Zhao Z* (2014) A meta-analysis of somatic mutations from next generation sequencing of 241 melanomas: a road map for the study of genes with potential clinical relevance. Molecular Cancer Therapeutics, 13(7):1918-28 [WES, WGS]
  4. Lovly CM, McDonald NT, Chen H, Ortiz-Cuaran S, Heukamp LC, Yan Y, Florin A, Ozreti? L, Lim D, Wang L, Chen Z, Chen X, Lu P, Paik PK, Shen R, Jin H, Buettner R, Ansén S, Perner S, Brockmann M, Bos M, Wolf J, Gardizi M, Wright GM, Solomon B, Russell PA, Rogers TM, Suehara Y, Red-Brewer M, Tieu R, de Stanchina E, Wang Q, Zhao Z, Johnson DH, Horn L, Wong KK, Thomas RK, Ladanyi M, Pao W (2014) Rationale for co-targeting IGF-1R and ALK in ALK fusion positive lung cancer. Nature Medicine 20(9):1027-34 [WGS]
  5. Zhao Z, Xu J, Chen J, Kim S, Reimers M, Bacanu SA, Yu H, Liu C, Sun J, Wang Q, Jia P, Xu F, Zhang Y, Kendler KS, Peng Z, Chen X (2015) Transcriptome sequencing and genome-wide association analyses reveal lysosomal function and actin cytoskeleton remodeling in schizophrenia and bipolar disorder. Molecular Psychiatry, 20(5):563-572 [RNA-seq]
  6. Thomas LR, Wang Q, Dey S, Howard GC, Ess K, Grieb B, Eischen C, Lorey S, Foshage A, Fesik S, Zhao Z, Clark T, Tansey TP (2015) Interaction with WDR5 promotes target gene recognition and tumorigenesis by MYC. Molecular Cell, 58(3): 440-452 [ChIP-seq]
  7. McGirt LY, Jia P, Baerenwald DA, Dahlman K, Zic JA, Zwerner JP, Hucks D, Dave U, Zhao Z, Eischen CM (2015) Whole genome analysis reveals oncogenic alterations in mycosis fungoides. Blood 126(4): 508-519 [WGS-seq]
  8. Cogan J, Loyd JE, Zhao Z, Gaskill C, Jetter C, Kropski JA, Majka SM, Austin ED (2016) Critical genomic networks and vasoreactive variants in idiopathic pulmonary arterial hypertension. The American Journal of Respiratory and Critical Care Medicine (AJRCCM) 194(4):464-75 [WES]
  9. Huang Y, Wang J, Jia P, Li X, Pei G, Wang C, Fang X, Zhao Z, Cai Z, Yi X, Wu S, Zhang B (2019) Clonal architectures predict clinical outcome in clear cell renal cell carcinoma. Nature Communications 10(1):1245 [WGS]
  10. Gallant JN, Sewell A, Almodovar K, Wang Q, Dahlman KB, Abramson RG, Kapp ME, Brown BT, Boyd KL, Gilbert J, Cohen DN, Yarbrough WG*, Zhao Z*, Lovly CM* (2019) Genomic landscape of a metastatic malignant proliferating tricholemmal tumor and its response to PI3K inhibition. Nature Precision Oncology 3:5 [WGS]

NGS technique, methodology, and tool publications:

  1. Jia P, Li F, Xia J, Chen H, Ji H, Pao W, Zhao Z* (2012) Consensus rules in variant detection from next-generation sequencing data. PLoS ONE 7(5): e38470
  2. Wang Q, Jia P, Zhao Z* (2013) VirusFinder: software for efficient and accurate detection of viruses and their integration sites in host genomes through next generation sequencing data. PLoS ONE 8(5):e64465
  3. Zhao M, Wang Q, Wang Q, Jia P, Zhao Z* (2013) Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives. BMC Bioinformatics 14(Suppl 11):S1  
  4. Wang Q, Jia P, Li F, Hucks D, Dahlman K, Ji H, Chen H, Pao W, Zhao Z* (2013) Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers. Genome Medicine 5:91
  5. Jia P, Zhao Z* (2014) VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data. PLoS Computational Biology 10(2): e1003460
  6. Jia P, Wang Q, Chen Q, Hutchinson K, Pao W, Zhao Z* (2014) MSEA: detection and quantification of mutation hotspots through mutation set enrichment analysis. Genome Biology15:489
  7. Wang Q, Jia P, Zhao Z* (2015) VERSE: a novel approach to detect virus integration in host genomes through reference genome customization. Genome Medicine 7:2
  8. O’Brien TD, Jia P, Xia J, Saxena U, Jin H, Vuong H, Kim P, Wang Q, Aryee MJ, Mino-Kenudson M, Engelman JA, Le L, Iafrate AJ, Heist RS, Pao W, Zhao Z* (2015) Inconsistency and features of single nucleotide variants detected in whole exome sequencing versus transcriptome sequencing: A case study in lung cancer. Methods, 83:118-127
  9. Cao Y, Zhu J, Jia P, Zhao Z* (2017) scRNASeqDB: a database for gene expression profiling in human single cell by RNA-seq. [bioRxiv, 104810], Genes 8, 368; doi:10.3390/genes8120368
  10. Eraslan G, Simon LM, Mircea M, Mueller NS, Theis FJ (2019) Single-cell RNA-seq denoising using a deep count autoencoder. Nature Communications 2019, 10(1):390.