Robert Tibshirani

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. ncbi request reprint Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins
    Sandip Ray
    Satoris, Inc, 2686 Middlefield Road, Suite E, Redwood City, California 94063, USA
    Nat Med 13:1359-62. 2007
  2. ncbi request reprint Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia
    Lars Bullinger
    Department of Pathology, Stanford University, Stanford, Calif, USA
    N Engl J Med 350:1605-16. 2004
  3. pmc Early detection of breast cancer based on gene-expression patterns in peripheral blood cells
    Praveen Sharma
    DiaGenic ASA, Oslo, Norway
    Breast Cancer Res 7:R634-44. 2005
  4. ncbi request reprint Sample classification from protein mass spectrometry, by 'peak probability contrasts'
    Robert Tibshirani
    Department of Health, Research and Policy, Stanford University, CA 94305, USA
    Bioinformatics 20:3034-44. 2004
  5. pmc A simple method for assessing sample sizes in microarray experiments
    Robert Tibshirani
    Health Research and Policy, Stanford University, Stanford, CA 94305, USA
    BMC Bioinformatics 7:106. 2006
  6. doi request reprint hCAP-D3 expression marks a prostate cancer subtype with favorable clinical behavior and androgen signaling signature
    Jacques Lapointe
    Department of Pathology, Stanford University, Stanford, CA 94305 51, USA
    Am J Surg Pathol 32:205-9. 2008
  7. pmc Alteration of gene expression signatures of cortical differentiation and wound response in lethal clear cell renal cell carcinomas
    Hongjuan Zhao
    Department of Urology, Stanford University, Stanford, CA, USA
    PLoS ONE 4:e6039. 2009
  8. ncbi request reprint Expression and prognostic significance of a panel of tissue hypoxia markers in head-and-neck squamous cell carcinomas
    Quynh Thu Le
    Department of Radiation Oncology, Stanford University, Stanford, CA 94305 5847, USA
    Int J Radiat Oncol Biol Phys 69:167-75. 2007
  9. pmc Discovery and validation of breast cancer subtypes
    Amy V Kapp
    Department of Statistics, Stanford University, Stanford, CA, USA
    BMC Genomics 7:231. 2006
  10. pmc Complementary hierarchical clustering
    Gen Nowak
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 9:467-83. 2008

Collaborators

Detail Information

Publications70

  1. ncbi request reprint Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins
    Sandip Ray
    Satoris, Inc, 2686 Middlefield Road, Suite E, Redwood City, California 94063, USA
    Nat Med 13:1359-62. 2007
    ..Biological analysis of the 18 proteins points to systemic dysregulation of hematopoiesis, immune responses, apoptosis and neuronal support in presymptomatic Alzheimer's disease...
  2. ncbi request reprint Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia
    Lars Bullinger
    Department of Pathology, Stanford University, Stanford, Calif, USA
    N Engl J Med 350:1605-16. 2004
    ..However, the current classification system does not fully reflect the molecular heterogeneity of the disease, and treatment stratification is difficult, especially for patients with intermediate-risk AML with a normal karyotype...
  3. pmc Early detection of breast cancer based on gene-expression patterns in peripheral blood cells
    Praveen Sharma
    DiaGenic ASA, Oslo, Norway
    Breast Cancer Res 7:R634-44. 2005
    ..In this study, we investigated whether early detection of breast cancer is possible by analyzing gene-expression patterns in peripheral blood cells...
  4. ncbi request reprint Sample classification from protein mass spectrometry, by 'peak probability contrasts'
    Robert Tibshirani
    Department of Health, Research and Policy, Stanford University, CA 94305, USA
    Bioinformatics 20:3034-44. 2004
    ..We illustrate the method on matrix-assisted laser desorption and ionization mass spectrometry data from a study of ovarian cancers...
  5. pmc A simple method for assessing sample sizes in microarray experiments
    Robert Tibshirani
    Health Research and Policy, Stanford University, Stanford, CA 94305, USA
    BMC Bioinformatics 7:106. 2006
    ..In this short article, we discuss a simple method for assessing sample size requirements in microarray experiments...
  6. doi request reprint hCAP-D3 expression marks a prostate cancer subtype with favorable clinical behavior and androgen signaling signature
    Jacques Lapointe
    Department of Pathology, Stanford University, Stanford, CA 94305 51, USA
    Am J Surg Pathol 32:205-9. 2008
    ..019). Our findings identify hCAP-D3 as a new biomarker for subtype-1 tumors that improves prognostication, and reveal androgen signaling as an important biologic feature of this potentially clinically favorable molecular subtype...
  7. pmc Alteration of gene expression signatures of cortical differentiation and wound response in lethal clear cell renal cell carcinomas
    Hongjuan Zhao
    Department of Urology, Stanford University, Stanford, CA, USA
    PLoS ONE 4:e6039. 2009
    ..Our findings suggest that critical biological features of lethal ccRCC include loss of normal cortical differentiation and activation of programs associated with wound healing...
  8. ncbi request reprint Expression and prognostic significance of a panel of tissue hypoxia markers in head-and-neck squamous cell carcinomas
    Quynh Thu Le
    Department of Radiation Oncology, Stanford University, Stanford, CA 94305 5847, USA
    Int J Radiat Oncol Biol Phys 69:167-75. 2007
    ..To investigate the expression pattern of hypoxia-induced proteins identified as being involved in malignant progression of head-and-neck squamous cell carcinoma (HNSCC) and to determine their relationship to tumor pO(2) and prognosis...
  9. pmc Discovery and validation of breast cancer subtypes
    Amy V Kapp
    Department of Statistics, Stanford University, Stanford, CA, USA
    BMC Genomics 7:231. 2006
    ..The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+...
  10. pmc Complementary hierarchical clustering
    Gen Nowak
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 9:467-83. 2008
    ..The complementary clustering reveals a grouping of the patients which is uncorrelated with a number of known prognostic signatures and significantly differing distant metastasis-free probabilities...
  11. ncbi request reprint Disease-specific genomic analysis: identifying the signature of pathologic biology
    Monica Nicolau
    Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
    Bioinformatics 23:957-65. 2007
    ..Genomic high-throughput technology generates massive data, providing opportunities to understand countless facets of the functioning genome. It also raises profound issues in identifying data relevant to the biology being studied...
  12. ncbi request reprint Signature patterns of gene expression in mouse atherosclerosis and their correlation to human coronary disease
    Raymond Tabibiazar
    Donald W Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford, CA, USA
    Physiol Genomics 22:213-26. 2005
    ....
  13. pmc Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression
    Kunju Sridhar
    Hematology Division, Stanford University Medical Center, 875 Blake Wilbur Drive, Stanford, CA 94305, USA
    Blood 114:4847-58. 2009
    ....
  14. pmc Semi-supervised methods to predict patient survival from gene expression data
    Eric Bair
    Department of Statistics, Stanford University, Palo Alto, USA
    PLoS Biol 2:E108. 2004
    ..This has the potential to be a powerful tool for diagnosing and treating cancer...
  15. ncbi request reprint Spatial smoothing and hot spot detection for CGH data using the fused lasso
    Robert Tibshirani
    Department of Health, Stanford University Stanford, CA 94305, USA
    Biostatistics 9:18-29. 2008
    ..Estimates of false-discovery rate are also provided. Our studies show that the new method generally outperforms competing methods for calling gains and losses in CGH data...
  16. pmc A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
    Daniela M Witten
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 10:515-34. 2009
    ..We apply this penalized CCA method to simulated data and to a genomic data set consisting of gene expression and DNA copy number measurements on the same set of samples...
  17. pmc Boolean implication networks derived from large scale, whole genome microarray datasets
    Debashis Sahoo
    Department of Computer Science, Stanford University, Stanford, CA 94305, USA
    Genome Biol 9:R157. 2008
    ..These relationships capture gender differences, tissue differences, development, and differentiation. New relationships are discovered that are preserved across all three species...
  18. ncbi request reprint Regularized linear discriminant analysis and its application in microarrays
    Yaqian Guo
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 8:86-100. 2007
    ..It is also suitable for feature elimination purpose and can be used as gene selection method. The open source R package for this method (named "rda") is available on CRAN (http://www.r-project.org) for download and testing...
  19. pmc Temporal changes in gene expression induced by sulforaphane in human prostate cancer cells
    Suvarna Bhamre
    Department of Urology, Stanford University, Stanford, California 4305 5118, USA
    Prostate 69:181-90. 2009
    ..To better understand the temporal effects of sulforaphane and broccoli sprouts on gene expression in prostate cells, we carried out comprehensive transcriptome analysis using cDNA microarrays...
  20. pmc Repeated observation of breast tumor subtypes in independent gene expression data sets
    Therese Sorlie
    Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 100:8418-23. 2003
    ..Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities...
  21. ncbi request reprint Outlier sums for differential gene expression analysis
    Robert Tibshirani
    Department of Health Research and Policy, Stanford University, Stanford, CA 94305, USA
    Biostatistics 8:2-8. 2007
    ..We also compare our approach to the recent cancer profile outlier analysis proposal of Tomlins and others (2005)...
  22. ncbi request reprint An evaluation of tumor oxygenation and gene expression in patients with early stage non-small cell lung cancers
    Quynh Thu Le
    Department of Radiation Oncology, Stanford University Medical Center, Stanford, California 94305 5847, USA
    Clin Cancer Res 12:1507-14. 2006
    ..To directly assess tumor oxygenation in resectable non-small cell lung cancers (NSCLC) and to correlate tumor pO2 and the selected gene and protein expression to treatment outcomes...
  23. pmc Gene expression profiling predicts survival in conventional renal cell carcinoma
    Hongjuan Zhao
    Department of Urology, Stanford University School of Medicine, Stanford, California, USA
    PLoS Med 3:e13. 2006
    ..Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival...
  24. doi request reprint Survival analysis with high-dimensional covariates
    Daniela M Witten
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Stat Methods Med Res 19:29-51. 2010
    ..Due to the high dimensionality of this data, most classical statistical methods for survival analysis cannot be applied directly. Here, we review a number of methods from the literature that address these two problems...
  25. pmc Local false discovery rate facilitates comparison of different microarray experiments
    Wan Jen Hong
    Department of Medicine, Department of Biochemistry, Department of Statistics and Health Research and Policy, Stanford University Medical Center, Stanford, CA 94305, USA
    Nucleic Acids Res 37:7483-97. 2009
    ..Genes responsive to UV but not IR were depleted for cell adhesion functions. Genes responsive to tobacco smoke were enriched for detoxification functions. Thus, LFDR reveals differences and similarities among experiments...
  26. pmc Array-based comparative genomic hybridization identifies localized DNA amplifications and homozygous deletions in pancreatic cancer
    Murali D Bashyam
    Department of Pathology, Stanford University, Stanford, CA, USA
    Neoplasia 7:556-62. 2005
    ..Our findings suggest candidate genes and pathways, which may contribute to the development or progression of pancreatic cancer...
  27. pmc Cancer characterization and feature set extraction by discriminative margin clustering
    Kamesh Munagala
    Department of Biochemistry, Stanford University School of Medicine, 466 Gates Computer Science, Stanford, CA 94305, USA
    BMC Bioinformatics 5:21. 2004
    ..A central challenge in the molecular diagnosis and treatment of cancer is to define a set of molecular features that, taken together, distinguish a given cancer, or type of cancer, from all normal cells and tissues...
  28. pmc Adaptive index models for marker-based risk stratification
    Lu Tian
    Department of Health Research and Policy, Stanford University, Stanford, CA 94305, USA
    Biostatistics 12:68-86. 2011
    ..We also extend the procedure to create indices for detecting treatment-marker interactions. The methods are illustrated on a study with protein biomarkers as well as a large microarray gene expression study...
  29. pmc Sparse inverse covariance estimation with the graphical lasso
    Jerome Friedman
    Department of Statistics, Stanford University, CA 94305, USA
    Biostatistics 9:432-41. 2008
    ..It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics...
  30. pmc Gene expression patterns in ovarian carcinomas
    Marci E Schaner
    Stanford University School of Medicine, Stanford, California 94305 5151, USA
    Mol Biol Cell 14:4376-86. 2003
    ....
  31. ncbi request reprint A tail strength measure for assessing the overall univariate significance in a dataset
    Jonathan Taylor
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 7:167-81. 2006
    ..It also has a simple relationship to the false discovery rate of the collection of tests. We derive the asymptotic distribution of the tail strength measure, and illustrate its use on a number of real datasets...
  32. pmc DR-Integrator: a new analytic tool for integrating DNA copy number and gene expression data
    Keyan Salari
    Department of Pathology, Stanford University, Stanford, CA, USA
    Bioinformatics 26:414-6. 2010
    ....
  33. ncbi request reprint A method for calling gains and losses in array CGH data
    Pei Wang
    Department of Statistics, Stanford University, CA, 94305, USA
    Biostatistics 6:45-58. 2005
    ..We illustrate the method using an application of CLAC on a lung cancer microarray CGH data set as well as a BAC array CGH data set of aneuploid cell strains...
  34. pmc Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival
    Howard Y Chang
    Program in Epithelial Biology, Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 102:3738-43. 2005
    ....
  35. pmc Genome-wide measurement of RNA folding energies
    Yue Wan
    Howard Hughes Medical Institute and Program in Epithelial Biology, Stanford University, Stanford, CA 94305, USA
    Mol Cell 48:169-81. 2012
    ..Thus, genome-wide structural dynamics of RNA can parse functional elements of the transcriptome and reveal diverse biological insights...
  36. pmc Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls
    Daniela Witten
    Department of Statistics, Stanford University, Stanford, California 94305 4065, USA
    BMC Biol 8:58. 2010
    ..Small RNA populations are particularly well suited to this analysis, as many different small RNAs can be completely sequenced in a single instrument run...
  37. pmc Toxicity from radiation therapy associated with abnormal transcriptional responses to DNA damage
    Kerri E Rieger
    Department of Medicine and Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 101:6635-40. 2004
    ..Of the five patients with toxicity and normal responses, two were treated with protocols that proved to be highly toxic. These results may enable physicians to predict toxicity and tailor treatment for individual patients...
  38. pmc CD81 protein is expressed at high levels in normal germinal center B cells and in subtypes of human lymphomas
    Robert F Luo
    Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA
    Hum Pathol 41:271-80. 2010
    ....
  39. ncbi request reprint Mouse strain-specific differences in vascular wall gene expression and their relationship to vascular disease
    Raymond Tabibiazar
    Donald W Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
    Arterioscler Thromb Vasc Biol 25:302-8. 2005
    ..In this study, we sought to identify the genetic pathways that are differentially activated in the aortas of these mice...
  40. pmc Notch signals positively regulate activity of the mTOR pathway in T-cell acute lymphoblastic leukemia
    Steven M Chan
    Division of Immunology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
    Blood 110:278-86. 2007
    ..T-ALL cell growth was suppressed in a highly synergistic manner by simultaneous treatment with the mTOR inhibitor rapamycin and GSI, which represents a rational drug combination for treating this aggressive human malignancy...
  41. pmc Cell type-specific gene expression differences in complex tissues
    Shai S Shen-Orr
    Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
    Nat Methods 7:287-9. 2010
    ....
  42. ncbi request reprint Are clusters found in one dataset present in another dataset?
    Amy V Kapp
    Department of Statistics, Stanford University, Stanford, CA 94305 4065, USA
    Biostatistics 8:9-31. 2007
    ..An implementation of this algorithm is in a package called "clusterRepro" available through The Comprehensive R Archive Network (http://cran.r-project.org)...
  43. doi request reprint C-C chemokine receptor 1 expression in human hematolymphoid neoplasia
    Matthew W Anderson
    Dept of Pathology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA
    Am J Clin Pathol 133:473-83. 2010
    ..These data suggest that CCR1 may be useful for lymphoma classification and support a role for chemokine signaling in the pathogenesis of hematolymphoid neoplasia...
  44. pmc Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors
    Jonathan R Pollack
    Departments of Pathology, Genetics, Surgery, Health Research and Policy, and Biochemistry, and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 99:12963-8. 2002
    ..These findings provide evidence that widespread DNA copy number alteration can lead directly to global deregulation of gene expression, which may contribute to the development or progression of cancer...
  45. ncbi request reprint Efficient quadratic regularization for expression arrays
    Trevor Hastie
    Departments of Statistics, and Health Research and Policy, Stanford University, Sequoia Hall, CA 94305, USA
    Biostatistics 5:329-40. 2004
    ..For all of these models, we show that dramatic computational savings are possible over naive implementations, using standard transformations in numerical linear algebra...
  46. pmc IRF9 and STAT1 are required for IgG autoantibody production and B cell expression of TLR7 in mice
    Donna L Thibault
    Department of Medicine, Division of Immunology and Rheumatology, Stanford University School of Medicine, Stanford, California 94305, USA
    J Clin Invest 118:1417-26. 2008
    ..Our results suggest that IFN-I is upstream of TLR signaling in the activation of autoreactive B cells in SLE...
  47. ncbi request reprint The 'miss rate' for the analysis of gene expression data
    Jonathan Taylor
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 6:111-7. 2005
    ..The false discovery rate has become a popular measure in this setting. Here we discuss a complementary measure, the 'miss rate', and show how to estimate it in practice...
  48. pmc Gene expression profiling differentiates germ cell tumors from other cancers and defines subtype-specific signatures
    Dejan Juric
    Oncology Division, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305 5151, USA
    Proc Natl Acad Sci U S A 102:17763-8. 2005
    ..Dynamic computation of interaction networks and mapping to existing pathways knowledge databases revealed a potential role of EGR1 in p21-induced cell cycle arrest and intrinsic chemotherapy resistance of mature teratomas...
  49. pmc Gene expression profiling identifies clinically relevant subtypes of prostate cancer
    Jacques Lapointe
    Department of Pathology, Stanford University, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 101:811-6. 2004
    ..Our results suggest that prostate tumors can be usefully classified according to their gene expression patterns, and these tumor subtypes may provide a basis for improved prognostication and treatment stratification...
  50. ncbi request reprint The use of plasma surface-enhanced laser desorption/ionization time-of-flight mass spectrometry proteomic patterns for detection of head and neck squamous cell cancers
    Scott G Soltys
    Department of Radiation Oncology, and Health Policy and Research, Stanford University, Stanford, California 94305 5847, USA
    Clin Cancer Res 10:4806-12. 2004
    ....
  51. pmc Disease signatures are robust across tissues and experiments
    Joel T Dudley
    Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
    Mol Syst Biol 5:307. 2009
    ....
  52. pmc Transcriptional programs activated by exposure of human prostate cancer cells to androgen
    Samuel E DePrimo
    Department of Urology, Room S 287, Stanford University School of Medicine, Stanford, CA 94305, USA
    Genome Biol 3:RESEARCH0032. 2002
    ..We used DNA microarrays, representing approximately 18,000 genes, to examine the temporal program of gene expression following treatment of the human prostate cancer cell line LNCaP with a synthetic androgen...
  53. ncbi request reprint LMO2 protein expression predicts survival in patients with diffuse large B-cell lymphoma treated with anthracycline-based chemotherapy with and without rituximab
    Yasodha Natkunam
    Department of Pathology, Division of Oncology, Stanford University School of Medicine, Stanford, CA, USA
    J Clin Oncol 26:447-54. 2008
    ..Here, we tested the prognostic impact of LMO2 protein expression in DLBCL patients treated with anthracycline-based chemotherapy with or without rituximab...
  54. pmc Normalization, testing, and false discovery rate estimation for RNA-sequencing data
    Jun Li
    Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Biostatistics 13:523-38. 2012
    ..In summary, this work provides a pipeline for the significance analysis of sequencing data...
  55. ncbi request reprint Statistical methods for identifying differentially expressed genes in DNA microarrays
    John D Storey
    Department of Statistics, Stanford University, Palo Alto, CA, USA
    Methods Mol Biol 224:149-57. 2003
  56. ncbi request reprint Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data
    Jun Li
    1Department of Statistics, Stanford University, Stanford, CA 94305, USA
    Stat Methods Med Res 22:519-36. 2013
    ..We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. ..
  57. pmc Diagnosis of multiple cancer types by shrunken centroids of gene expression
    Robert Tibshirani
    Department of Health, Research and Policy, and Statistics, Stanford University, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 99:6567-72. 2002
    ..The technique is general and can be used in many other classification problems. To demonstrate its effectiveness, we show that the method was highly efficient in finding genes for classifying small round blue cell tumors and leukemias...
  58. pmc Human transcriptome array for high-throughput clinical studies
    Weihong Xu
    Stanford Genome Technology Center and Department of Biochemistry, Stanford University, Palo Alto, CA 94304, USA
    Proc Natl Acad Sci U S A 108:3707-12. 2011
    ....
  59. ncbi request reprint Empirical bayes methods and false discovery rates for microarrays
    Bradley Efron
    Department of Statistics and Division of Biostatistics, Stanford University, Stanford, California 94305, USA
    Genet Epidemiol 23:70-86. 2002
    ..It turns out that the two methods are closely related and can be used together to produce sensible simultaneous inferences...
  60. ncbi request reprint Global transcriptional response to interferon is a determinant of HCV treatment outcome and is modified by race
    Xiao Song He
    Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
    Hepatology 44:352-9. 2006
    ....
  61. ncbi request reprint Immune signatures in follicular lymphoma
    Robert Tibshirani
    N Engl J Med 352:1496-7; author reply 1496-7. 2005
  62. ncbi request reprint Comment on "The consensus coding sequences of human breast and colorectal cancers"
    Gad Getz
    Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
    Science 317:1500. 2007
    ..When these concerns are addressed, few genes with significantly elevated mutation rates remain. Although the biological methodology in Sjöblom et al. is sound, more samples are needed to achieve sufficient power...
  63. ncbi request reprint Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer
    Anna Bergamaschi
    Department of Genetics, Institute for Cancer Research, Rikshospitalet Radiumhospitalet Medical Center, Oslo, Norway
    Genes Chromosomes Cancer 45:1033-40. 2006
    ..This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat..
  64. ncbi request reprint HGAL is a novel interleukin-4-inducible gene that strongly predicts survival in diffuse large B-cell lymphoma
    Izidore S Lossos
    Division of Oncology, Department of Medicine and the Department of Health Research and Policy, Stanford University School of Medicine, CA, USA
    Blood 101:433-40. 2003
    ..This association was independent of the clinical international prognostic index. High HGAL mRNA expression should be used as a prognostic factor in DLBCL...
  65. pmc Statistical significance for genomewide studies
    John D Storey
    Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
    Proc Natl Acad Sci U S A 100:9440-5. 2003
    ..Our approach avoids a flood of false positive results, while offering a more liberal criterion than what has been used in genome scans for linkage...
  66. ncbi request reprint Averaged gene expressions for regression
    Mee Young Park
    Google Inc, Mountain View, CA 94043, USA
    Biostatistics 8:212-27. 2007
    ..Our methods are supported with theoretical justifications and demonstrated on simulated and real data sets...
  67. ncbi request reprint Hybrid hierarchical clustering with applications to microarray data
    Hugh Chipman
    Department of Mathematics and Statistics, Acadia University, Wolfville, NS, Canada B4P 2R6
    Biostatistics 7:286-301. 2006
    ..We illustrate the technique on simulated and real microarray datasets...
  68. ncbi request reprint Gene expression profiles at diagnosis in de novo childhood AML patients identify FLT3 mutations with good clinical outcomes
    Norman J Lacayo
    Division of Pediatric Hematology Oncology, Stanford University School of Medicine, Palo Alto, CA, USA
    Blood 104:2646-54. 2004
    ..0001). Thus, gene expression profiling identified AML patients with divergent prognoses within the FLT3-MU group, and the RUNX3 to ATRX expression ratio should be a useful prognostic indicator in these patients...
  69. doi request reprint Genomics of childhood leukemias: the virtue of complexity
    Branimir I Sikic
    J Clin Oncol 26:4367-8. 2008
  70. doi request reprint An FLT3 gene-expression signature predicts clinical outcome in normal karyotype AML
    Lars Bullinger
    Department of Internal Medicine III, University of Ulm, Ulm, Germany
    Blood 111:4490-5. 2008
    ..Our findings support the potential clinical utility of a gene expression-based measure of FLT3 pathway activation in AML...