Supplements

Below are specific supplements, which may include figures, tables, data, and/or analysis code for manuscripts published by researchers at MD Anderson:

• PanCan 11
  Supplementary data in support of the paper: A pan-cancer proteomic perspective on The Cancer Genome Atlas, by Akbani R, Ng PKS, Werner HMJ, et al. Nature Communications 2014; 5:3877.

• PanCan 12 Subtypes
  Supplementary data in support of the paper: Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin, by Hoadley KA, Yao C, Wolf DM, et al., Cell 2014; 158(4):929-944.

• Chemosensitivity and Cell Lines
  Supplementary data in support of the paper:Deriving Chemosensitivity from Cell Lines: Forensic Bioinformaticsand Reproducible Research in High-Throughput Biology, by Baggerly KA and Coombes KR, Annals of Applied Statistics 2009; 3(4):1309-1334.

• Alternative Splicing in Glioblastoma
  Supplementary datasets in support of the paper:Global Analysis of Aberrant pre-mRNA Splicing in Glioblastoma Using Exon Expression Arrays, by Cheung HC, Baggerly KA, Tsavachidis S, Bachinski LL, Neubauer VL, Nixon TJ, Aldape KD, Cote GJ, Krahe R. These include CEL files for 24 glioblastoma samples (around 550Mb zipped), CEL files for 12 normal brain samples (around 266Mb zipped), and a text file with file names and tumor/normal status (1K).

• Topographical Normalization
  Supplementary dataset, containing code and data in support of the paper:Topographical Normalization of Reverse Phase Protein Arrays, by Neeley ES, Baggerly KA, Kornblau SM.

• RPPA Data for Variable Slope Normalization
  Supplementary dataset, containing code and clinical and RPPA protein datain support of the paper: Variable Slope Normalization of Reverse Phase Protein Arrays, by Neeley ES, Kornblau SM, Coombes KR, Baggerly KA.

• RPPA Data in AML
  Supplementary dataset, containing clinical and RPPA protein data on 256 newly diagnosed AML patients, in support of the paper: Functional Proteomic Profiling of AML Predicts Response and Survival, by Kornblau SM, Tibes R, Qiu YH, CHen W, Kantarjian H, Andreeff M, Coombes KR, Mills GB. Blood, to appear.

• Run Batch Effects and Ovarian Cancer
  Complete source code and results for the analysis described in: Run batch effects potentially compromise the usefulness of genomicsignatures for ovarian cancer, by Baggerly KA, Neeley ES, Coombes KR. J Clin Oncol. 2008; 26(7):1186-1187. Dressman et al. replied to our correspondence. Our own reply-to-their-reply wil be posted on our addendum to our first web site.

• (Ir)reproducibility of chemopredictors
  Complete source code and results for the analysis described in: Microarrays: retracing steps, by Coombes KR, Wang J, Baggerly KA. Nature Medicine. 2007; 3(11):1276-1277. (Formerlyknown as: Genomic signatures based on the NCI60 cell lines do notpredict patient response to chemotherapy.) Potti and Nevins replied to our correspondence. Our own reply-to-their-reply can be found on our addendum to our first web site.

• Microenvironment Gene List
  Supplementary table for: Gene Expression Profile of Metastatic Human Pancreatic Cancer Cells Depends on the Organ Microenvironment, by Najamura T, Fidler IJ, Coombes KR. Cancer Res. 2007; 67:139-48.

• Wavelet-Based Functional Mixed Models
  Supplementary material, including description of Metroplis-Hastingsand some MCMC trace plots, for Wavelet-based Functional Mixed Models by Morris and Carroll.

• UniGene Affiliation
  Supplementary material for Gene Sequence Signatures Revealed by Mining the UniGene Affiliation Network, by Zhang J, Zhang L, Coombes KR. Bioinformatics. 2006; 22:385-91

• Validation by QRT-PCR on Low-Density Arrays
  Supplementary figures and data Validation of oligonucleotide microarray data using microfluidiclow-density arrays: a new statistical method to normalize real-timeRT-PCR data, by Abruzzo LV, Lee KY, Fuller A, Silverman A, Keating MJ, Medeiros LJ, Coombes KR. Biotechniques. 2005; 38:785-92

• List of Significant Peaks in Pancreatic Cancer
  Supplementary Table S1 for: Plasma Protein Profiling for Diagnosis of Pancreatic Cancer Reveals the Presence of Host Response Proteins. by Koomen JM, Shih LN, Coombes KR, Li D, Xiao LC, Fidler IJ, Abbruzzese JL, Kobayashi R.Clin Cancer Res. 2005; 11:1110-1118.

• Peak detection for MALDI using the average spectrum
  Supplementary material for Feature Extraction and Quantification for Mass Spectrometry Data in Biomedical Applications Using the Mean Spectrum, by Morris JS, Coombes KR, Kooman J, Baggerly KA, and Kobayashi R. Bioinformatics 2005; 21:1764-75.

• Diagnostic Protein Discovery using LCMS for Proteolytic Peptide Targeting
  Supplementary material for: Diagnostic Protein Discovery using Proteolytic Peptide Targeting and Identification, by John M. Koomen, Haitao Zhao, Donghui Li, James L. Abbruzzese, Keith A. Baggerly, Ryuji Kobayashi. Rapid Communications in Mass Spectrometry, 2005; 18:2537-48.

• Reproducibility of SELDI-TOF
  Supplementary material, including Matlab and Perl code and additional Figures to accompany Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments, by Baggerly KA, Morris JS, Coombes KR. Bioinformatics 2004; 20:777-85

• Signal in Noise
  Supplementary material, including Matlab scripts and processed data to accompany Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer, by Baggerly KA, Edmonson SR, Morris JS, Coombes KR. Endocr Relat Cancer. 2004; 11:583-4

• Processing Proteomics Spectra, Version 1
  Supplements to: Quality control and peak finding for proteomics data collected from nipple aspirate fluid by surface-enhanced laser desorption and ionization, by Coombes KR, Fritsche HA Jr, Clarke C, Chen JN, Baggerly KA, Morris JS, Xiao LC, Hung MC, Kuerer HM. ClinChem. 2003; 49:1615-23

• Between Library Variation in SAGE
  Supplements to: Differential expression in SAGE: accounting for normal between-library variation, by Baggerly KA, Deng L, Morris JS, Aldaz CM. Bioinformatics. 2003; 19:1477-83.

• CAMDA 2001 Supplement
  Supplementary material for our presentation at CAMDA 2001

• PCANOVA
  Description of the PCANOVA method for evaluating the amount of group structure present in microarray data.

• EGFR.signature.zip
  Supplementary material for the EGFR.signature.