Optimal deconvolution of transcriptional profiling data using quadratic programming with application to complex clinical blood samples

PLoS ONE

Volumn 6, Issue 11, 2011, Pages

  Gong, Ting ^a   Hartmann, Nicole ^b   Kohane, Isaac S ^c   Brinkmann, Volker ^b   Staedtler, Frank ^b   Letzkus, Martin ^b   Bongiovanni, Sandrine ^b   Szustakowski, Joseph D ^a  

^a NOVARTIS INSTITUTES FOR BIOMEDICAL RESEARCH   (United States)

^b NOVARTIS PHARMA AG   (Switzerland)

^c BOSTON CHILDREN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FINGOLIMOD; MESSENGER RNA; PLACEBO;

ACCURACY; ANALYTIC METHOD; ARTICLE; BLOOD SAMPLING; CELL COUNT; CELL POPULATION; CELL TYPE; COMPUTER MODEL; COMPUTER PROGRAM; CONTROLLED STUDY; DATA ANALYSIS; DECONVOLUTION METHOD; DOUBLE BLIND PROCEDURE; FLOW CYTOMETRY; GENE EXPRESSION PROFILING; GENETIC TRANSCRIPTION; HUMAN; HUMAN CELL; HUMAN TISSUE; LEUKOCYTE MIGRATION; MULTICENTER STUDY; MULTIPLE SCLEROSIS; PHENOTYPE; PREDICTION; RANDOMIZED CONTROLLED TRIAL; STATISTICAL ANALYSIS; STATISTICAL MODEL; TISSUE TYPES; ADULT; ALGORITHM; BIOLOGY; BLOOD; CELL LINE; FEMALE; GENETICS; METABOLISM; METHODOLOGY; REGRESSION ANALYSIS;

ADULT; ALGORITHMS; BLOOD; CELL LINE; COMPUTATIONAL BIOLOGY; FEMALE; GENE EXPRESSION PROFILING; HUMANS; LEAST-SQUARES ANALYSIS; LINEAR MODELS; RNA, MESSENGER; TRANSCRIPTION, GENETIC;

EID: 81155135154     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0027156     Document Type: Article

References (30)

1. Liotta L, Petricoin E, (2000) Molecular profiling of human cancer. Nat Rev Genet 1: 48-56.
2. Coleman WB, Tsongalis GJ, (2009) Molecular Pathology: The Molecular Basis of Human Disease: Academic Press; 1 edition (March 16, 2009).
3. Shen-Orr SS, Tibshirani R, Khatri P, Bodian DL, Staedtler F, et al. (2010) Cell type-specific gene expression differences in complex tissues. Nat Methods 7: 287-289.
4. Lahdesmaki H, Shmulevich l, Dunmire V, Yli-Harja O, Zhang W, (2005) In silico microdissection of microarray data from heterogeneous cell populations. BMC Bioinformatics 6: 54.
5. Wang M, Master S, Chodosh L, (2006) Computational expression deconvolution in a complex mammalian organ. BMC Bioinformatics 7: 328.
6. Tureci O, Ding J, Hilton H, Bian H, Ohkawa H, et al. (2003) Computational dissection of tissue contamination for identification of colon cancer-specific expression profiles. Faseb J 17: 376-385.
7. Clarke J, Seo P, Clarke B, (2010) Statistical expression deconvolution from mixed tissue samples. Bioinformatics 26: 1043-1049.
8. Abbas AR, Wolslegel K, Seshasayee D, Modrusan Z, Clark HF, (2009) Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus. PLoS One 4: e6098.
9. Quon G, Morris Q, (2009) ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing. Bioinformatics 25: 2882-2889.
10. Stuart RO, Wachsman W, Berry CC, Wang-Rodriguez J, Wasserman L, et al. (2004) In silico dissection of cell-type-associated patterns of gene expression in prostate cancer. Proceedings of the National Academy of Sciences of the United States of America 101: 615-620.
11. Lu P, Nakorchevskiy A, Marcotte EM, (2003) Expression deconvolution: a reinterpretation of DNA microarray data reveals dynamic changes in cell populations. Proc Natl Acad Sci U S A 100: 10370-10375.
12. Bolstad BM, Irizarry RA, Astrand M, Speed TP, (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19: 185-193.
13. Guo L, Lobenhofer EK, Wang C, Shippy R, Harris SC, et al. (2006) Rat toxicogenomic study reveals analytical consistency across microarray platforms. Nat Biotechnol 24: 1162-1169.
14. Edgar R, Domrachev M, Lash AE, (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30: 207-210.
15. Nikolsky Y, Kirillov E, Zuev R, Rakhmatulin E, Nikolskaya T, (2009) Functional analysis of OMICs data and small molecule compounds in an integrated "knowledge-based" platform. Methods Mol Biol 563: 177-196.
16. Mehling M, Brinkmann V, Antel J, Bar-Or A, Goebels N, et al. (2008) FTY720 therapy exerts differential effects on T cell subsets in multiple sclerosis. Neurology 71: 1261-1267.
17. Erkkila T, Lehmusvaara S, Ruusuvuori P, Visakorpi T, Shmulevich I, et al. (2010) Probabilistic analysis of gene expression measurements from heterogeneous tissues. Bioinformatics 26: 2571-2577.
18. Repsilber D, Kern S, Telaar A, Walzl G, Black GF, et al. (2010) Biomarker discovery in heterogeneous tissue samples-taking the in-silico deconfounding approach. BMC Bioinformatics 11: 27.
19. Abbas AR, Baldwin D, Ma Y, Ouyang W, Gurney A, et al. (2005) Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data. Genes Immun 6: 319-331.
20. Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, et al. (2008) Alternative isoform regulation in human tissue transcriptomes. Nature 456: 470-476.
21. Kappos L, Antel J, Comi G, Montalban X, O'Connor P, et al. (2006) Oral fingolimod (FTY720) for relapsing multiple sclerosis. N Engl J Med 355: 1124-1140.
22. (2002) World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. J Postgrad Med 48: 206-208.
23. (2006) Guideline for good clinical practice E6 (R1) Geneva International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use 1996 Jun 10.
24. Alter O, Brown PO, Botstein D, (2000) Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci U S A 97: 10101-10106.
25. Liebermeister W, (2002) Linear modes of gene expression determined by independent component analysis. Bioinformatics 18: 51-60.
26. Smyth GK, (2004) Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3: Article3.
27. Lawson CL, Hanson RJ, Lawson CL, Hanson RJ, (1995) pp. 1-337 Solving least squares problems.
28. Mackey MD, Mackey DJ, Higgins HW, Wright SW, (1996) CHEMTAX- a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton. Marine Ecology Progress Series 144: 265-283.
29. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, et al. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5: R80.
30. Mellick AS, Day CJ, Weinstein SR, Griffiths LR, Morrison NA, (2002) Differential gene expression in breast cancer cell lines and stroma-tumor differences in microdissected breast cancer biopsies revealed by display array analysis. Int J Cancer 100: 172-180.