Cancer Program Datasets

Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment

Example datasets

High-resolution mapping of copy-number alterations with massively parallel sequencing

Alignment positions of sequence reads (hg18) arachne_qltout_marks.tar.gz
Matlab files with alignable coordinates hg18_alignable_N36_D2.tar.gz
Matlab source code, SegSeq version 1.0.1 SegSeq_1.0.1.tar.gz

Subclass Mapping: Identifying Common Subtypes in Independent Disease Data Sets

Breast-A: data set Breast_A.gct
Breast-A: class labels Breast_A.cls
Breast-B: data set Breast_B.gct
Breast-B: class labels Breast_B.cls
Multi-A: data set Multi_A.gct
Multi-A: class labels Multi_A.cls
Multi-B: data set Multi_B.gct
Multi-B: class labels Multi_B.cls
DLBCL-A: data set DLBCL_A.gct
DLBCL-A: class labels DLBCL_A.cls
DLBCL-B: data set DLBCL_B.gct
DLBCL-B: class labels DLBCL_B.cls
DLBCL-C: data set DLBCL_C.gct
DLBCL-C: class labels DLBCL_C.cls
DLBCL-D: dara set DLBCL_D.gct
DLBCL-D: class labels DLBCL_D.cls
HCclustid (generates .cls files from a clustering result)

Metagene projection for cross platform, cross species characterization of global transcriptional states

Readme file with instructions about how to run the code readme.txt
Leukemia 1 example: R code and datasets
Leukemia 2 example: R code and datasets
Lung example: R code and datasets

Metagenes and molecular pattern discovery using matrix factorization

ALL-AML gene expression data ALL_AML_data.txt
ALL-AML samples ALL_AML_samples.txt
ALL-AML genes ALL_AML_genes.txt
Medulloblastomas gene expression data Medulloblastoma_data.txt
Medulloblastomas samples Medulloblastomas_samples.txt
Medulloblastomas genes Medulloblastoma_genes.txt
Matlab M-file for NMF nmf.m
Matlab M-file for reordering NMF consensus matrices nmforderconsensus.m
supplemental information NMF_final_supplement.pdf
Matlab M-file for NMF (model selection) nmfconsensus.m
Some papers making use of NMF codes (as of 8/07) NMF_code_used_8_07.doc
NMF codes FAQ NMF_codes_FAQ.doc

GeneCluster 2.0: An advanced toolset for bioarray analysis

Manuscript Bioinformatics manuscript.pdf

Estimating Dataset Size Requirements for Classifying DNA Microarray Data

Draft Manuscript Sample_size_fin.pdf

Consensus Clustering: A resampling-based method for class discovery and visualization of gene expression microarray data

Technical Report consensus4pdflatex.pdf
Leukemia data ALB_ALT_AML.1000genes.res
Leukemia class template ALB_ALT_AML.cls
Novartis multi-tissue data Novartis_BPLC.top1000.gct
Novartis multi-tissue class template Novartis_BPLC.cls
St. Jude Leukemia data leukemia.top1000.gct
St. Jude Leukemia class template leukemia.cls
Lung cancer data LungA_1000genes.gct
Lung cancer class template LungA_local.cls
CNS tumors data brain_morpho.1000genes.res
CNS tumors class template brain_morpho.cls
Normal tissues data cGCM_9_15000_nml_90.top100.res
Normal tissues class template cGCM_9_15000_nml_90.cls
Uniform1 uniform1.gct.gz
Gaussian1 gaussian1.gct.gz
Gaussian3 gaussian3.gct.gz
Gaussian3 class template gaussian3.cls
Gaussian4 gaussian4.gct.gz
Gaussian4 class template gaussian4.cls
Gaussian5.delta2 gaussian5.delta2.gct.gz
Gaussian5.delta3 gaussian5.delta3.gct.gz
Gaussia5 class template gaussian5.cls
Simulated6 artificial_dataset1.gct.gz
Simulated6 class template artificial_dataset1.cls

An Analytical Method For Multi-class Molecular Cancer Classification

Paper (Word document) multiclass.siam_final_March_12_2003.pdf

A Strategy for Oligonucleotide Microarray Probe Reduction

Description of these files AboutTheseFiles.doc
Paper in pdf format Antipova_et_al_2002.pdf
Raw feature data for all the genes on the chips RawFeatureData.tar.gz
Unscaled Delta(h), random Deltas, and Average Difference UnscaledResFiles.tar.gz
Scaled Delta(h), random Deltas, and Average Difference ScaledResFiles.tar.gz
Cls files, idealized expression vectors for class assignments ClsFiles.tar.gz
Expanded Figure 2 Fig2Features.xls
Expanded Table 1, includes classification parameters Table1Features.xls
List of selected Delta(h) probes ListOfDeltaHprobes.xls

Multi-Class Cancer Diagnosis Using Tumor Gene Expression Signatures

Manuscript (PDF) GCM.pdf
Supplementary Information (PDF) PNAS_Supplementary_Information.pdf
GCM_Training.res GCM_Training.res
GCM_Training.cls GCM_Training.cls
GCM_Test.res GCM_Test.res
GCM_Test.cls GCM_Test.cls
GCM_PD.res GCM_PD.res
GCM_PD.cls GCM_PD.cls
GCM_Total.res GCM_Total.res
GCM_Total.cls GCM_Total.cls

Molecular Classification of Multiple Tumor Types

Paper (PDF) Bioinformatics_200107.pdf

Interpreting patterns of gene expression with self-organizing maps

Experimental protocol (.html) protocol.html
Dataset description Datasets_description.txt
Dataset data_set_HL60 (Excel) data_set_HL60.tsv
Dataset data_set_HL60_U937_NB4_Jurkat (text) data_set_HL60_U937_NB4_Jurkat.txt
Dataset data_set_HL60_U937_NB4_Jurkat (Excel) data_set_HL60_U937_NB4_Jurkat.tsv
Dataset data_set_HL60_U937_NB4_Jurkat (Excel) data_set_HL60_U937_NB4_Jurkat.tsv

Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma

Manuscript GISTIC_071020.pdf
Supplemental Information GISTIC_Supplement_071020.pdf
Segmented Data segmented_data_080520.seg
Array List File for GISTIC Glioma_array_list_080423.txt
Copy-number Polymorphisms (100K SNP only) 100K_CNVs_080423.txt
Marker Positions 100K_markerpositions.hg16.txt
Sample information (txt format) Sample_info_070424.txt
Array List File for GISTICPreprocessing Gliomas_normals_array_list_080522.txt
GISTICPreprocessing for 64-bit Linux PREPROCESSING.tar.gz
GISTIC for 64-bit Linux GISTIC_0_9_2.tar.gz

Gene expression-based classification of malignant gliomas correlates better with survival than histological classification

Paper Nutt et al - revised manuscript with references.doc
Figures Figures 1, 2 and 3.ppt
Supplement Supplementary Information - Cancer Research.doc
Classics Res File Brain_Classics.res
Classics Class File Brain_Classics.cls
NonClassics Res File Brain_NonClassics.res
NonClassics Class File Brain_NonClassics.cls
CEL Files Glioma CEL

Gene Expression-Based Classification and Outcome Prediction of Central Nervous System Embryonal Tumors

Manuscript (PDF) Brain_Nature.pdf
Supplementary Information document (MS Word) Pomeroy_et_al_0G04850_11142001_suppl_info.doc
Figures (MS Power Point) Pomeroy_et_al_0G04850_11142001_figures.ppt
Datasets and clinical table (ZIP, 13 Mbytes)
Sample list CNS_samples_CEL_files_list.xls
Raw data 1/4 (57 MB) scans_pt1.tar.gz
Raw data 2/4 (57 MB) scans_pt2.tar.gz
Raw data 3/4 (58 MB) scans_pt3.tar.gz
Raw data 4/4 (58 MB) scans_pt4.tar.gz
Dataset C (gene expression) RES file format Dataset_C_MD_outcome.res
Dataset C (class labels) CLS file format Dataset_C_MD_outcome.cls
Dataset C (clinical table) ASCII file format Brain_4_MD_outcome_2.survival.tex

COT drives resistance to RAF inhibition through MAP kinase pathway reactivation

DNA copy-number (segfile) of chromosome 10 in cell lines (CCLE) CCLE_Chrom10_MAP3K8_segfile.seg.txt
DNA copy-number of MAP3K8/COT in cell lines (CCLE) CCLE_MAP3K8_copy-number.txt
mRNA expression level of MAP3K8/COT in cell lines (CCLE) CCLE_MAP3K8_expressionAffy.txt

A zebrafish bmyb mutation causes genome instability and increased cancer susceptibility

MAGE formatted zebra fish crb mutant expression dataset
Whitehead gct formatted zebra fish crb mutant expression dataset crash_and_burn.gct
Class labels for the zebra fish expression dataset crash_and_burn.cls
Global Cancer Map (GCM) dataset GCM_All.gct
Acute Lymphoblastic Leukemia (Golub et al) ALL_vs_AML_U95_test.res
Adenocarcinoma with p53 mutation status (Beer et al) beer_lung_for_p53.gct
Anaplastic Oligodendroglioma (Nutt et al) glioma_classic_hist.gct
Classic Glioblastoma (Nutt et al) glioma_classic_hist.gct
Glioblastoma Survival (Nutt et al) glioma_nutt_combo.gct
Hepatic Carcinoma (Iizuka et al) hep_japan.gct
Lung Adenocarcinoma Outcome (Beer et al) lung_annarbor_outcome_only.gct
Lung Cancer Outcome (Bhatacharjee et al) lung_datasetB_outcome.gct
Lymph Node Metastatic Gastric Adenocarcinoma (Chen et al) gastric_full_from_smad.paired_14.f1.5_g0.6.pcl
Medulloblastoma (McDonald et al) med_macdonald_from_childrens.gct
Medulloblastoma (Pomeroy et al) medullo_datasetC_outcome.gct
Metastatic Tumors (Ramawamy et al) met.gct
References to published datasets used in this analysis references_and_URLS_of_datasets.html
Bmyb signature -- with expression levels (Table S1 full) bymb_signature_genes.htm
Bmyb signature -- list of unique human genes bmyb_crb_plus_signature_genes.html
Zebra fish p53 mutant and wild type CEL files
Zebra fish HU, Aph and control CEL files
Zebra fish 8g and MO treatment CEL files
Zebra fish bmyb crb, mo and control CEL files
Zebra fish cyclin WT and mutant CEL files
README for a description of zebrafish datasets used README_FOR_INFO_ON_ZF_DATASETS.html

An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis

All datasets in a single zipped file DATASETS.RAR
All figures and tables in a single zipped file figuresandtables.rar
All gene sets in a single zipped file GENESETS.RAR
Supplementary methods and description (ms doc) 4679_3_supp_0_1100271809.doc

Identification of AML1-ETO Modulators by Chemical Genomics

Text file describing supplemental information contents README.AE
Supplementary Tables and Figures Corsello_SupplementaryTablesFigures.pdf
Supplementary Methods Corsello_SupplementaryMethods.pdf
Kasumi AML1-ETO Knockdown Data Kasumi_AML1-ETO_complete_200410.res
U937 AML1-ETO Induced Data U937_AMLeto_inducible_ams.res
Kasumi AML1-ETO Knockdown Data CEL Files
U937 AML1-ETO Induced Data CEL Files

Expression-based Screening Identifies the Combination of Histone Deacetylase Inhibitors and Retinoids for Neuroblastoma Differentiation

Plain text file describing available supplementary information README.NB
Neuroblastoma microarray data NeuroCellLines_060628_ams.res
CEL files for neuroblastoma data

Signature-Based Small Molecule Screening Identifies Cytosine Arabinoside as an EWS/FLI Modulator in Ewing Sarcoma

Manuscript 10.1371_journal.pmed.0040122-L.pdf
Microsoft Excel sheet with supplementary tables Stegmaier_Supplementary_Tables.xls
Data file with compound treated cell lines HTA_Ewings_CmpdTest_060510_ams.res
Untreated control sample CEL files
ARA-C treated samples CEL files
Doxorubicin treated samples CEL files
Puromycin treated samples CEL files
Supplementary Figure 1 Stegmaier_Supplementary_Figure1.pdf
Supplementary Figure 2 Stegmaier_Supplementary_Figure2.pdf
Supplementary Figure 3 Stegmaier_Supplementary_Figure3.pdf
Supplementary Figure 4 Stegmaier_Supplementary_Figure4.pdf
Supplementary Table 1 Stegmaier_Supplement.Table1.pdf
Supplementary Table 2 Stegmaier_Supplement.Table2.pdf
Supplementary Table 3 Stegmaier_Supplement.Table3.pdf
Supplementary Table 4 Stegmaier_Supplement.Table4.pdf
Supplementary Table 5 Stegmaier_Supplement.Table5.pdf

Gefitinib (Iressa) induces myeloid differentiation of acute myeloid leukemia

Plain text file describing available supplementary information README
Manuscript blank.pdf
Microsoft Excel sheet with supplementary information StegmaierSupplementalData050516.xls
Gefitinib treated HL-60 cell line data Iressa_HL60_MeansScaling.res
Gefitinib treated Kasumi cell line data Iressa_Kasumi_041201_ams.res
Patient 1 (M3-AML) sample data Iressa_Patient1_ams.gct
Patient 2 (M5-AML) sample data Iressa_Patient2_ams.res
Patient 7 (M4-AML) sample data Iressa_Patient7_ams.res
Primary patient AML cells sample data Myeloid_Screen1_newData_021203_ams.AML_poly_mono.gct
Gefitinib treated HL-60 cell line data CEL files
Gefitinib treated Kasumi cell line data CEL files
Patient 1 (M3-AML) sample data CEL files
Patient 2 (M5-AML) sample data CEL files
Patient 7 (M4-AML) sample data CEL files
Primary patient AML cells sample data CEL files
Manuscript Figure 1 Stegmaier_Fig1_Final.pdf
Manuscript Figure 2 Stegmaier_Fig2_Final.pdf
Manuscript Figure 3 Stegmaier_Fig3_Final.pdf
Manuscript Figure 4 Stegmaier_Fig4_Final.pdf
Manuscript Figure 5 Stegmaier_Fig5_Final.pdf
Manuscript Figure 6 Stegmaier_Fig6_Final.pdf

Gene Expression-Based High Throughput Screening (GE-HTS) and Application to Leukemia Differentiation

Text file describing supplemental information contents README
Manuscript ng1305.pdf
Manuscript Figure 1 Fig1_edited.pdf
Manuscript Figure 2 Fig2_edited.pdf
Manuscript Figure 3 Fig3_edited.pdf
Manuscript Figure 4 Fig4_edited.pdf
Manuscript Figure 5 Fig5_edited.pdf
Supplemental Information Document Stegmaier_SupplementaryMethodsFiguresTables.pdf
Supplemental Information Excel Worksheets Stegmaier_SupplementaryData.xls
Initial Myeloid Primary Cell Data Myeloid_primarycells.res
Initial HL-60 Cell Data HL60_undiff_PMA_ATRA.res
Compound Treated HL-60 Cell Data Myeloid_Screen_Compound_Eval.res
Primary Patient APL Cell Data Myeloid_APL_compound_eval.res
Initial Myeloid Primary Cell Data CEL Files Myeloid_primarycells_CELfiles.tar.gz
Initial HL-60 Cell Data CEL Files HL60_undiff_PMA_ATRA_CELfiles.tar.gz
Compound Treated HL-60 Cell Data CEL Files Myeloid_Screen_Compound_Eval_CELfiles.tar.gz
Primary Patient APL Cell Data CEL Files Myeloid_APL_compound_eval_CELfiles.tar.gz
Nature Genetics GE-HTS News and Views GE-HTS_NandV.pdf

Chemosensitivity Prediction by Transcriptional Profiling

Scaled expression data w/A_P calls NCI60_aug99_resfile.txt
Drug sensitivity GI50 raw GI50_RAW.txt.gz
List of scan names samples_for_nci60paper.txt
Raw CEL files, part 1 (20 scans, ~44MB) nci60_scans_part1.tar.gz
Raw CEL files, part 2 (20 scans, ~44MB) nci60_scans_part2.tar.gz
Raw CEL files, part 3 (20 scans, ~44MB) nci60_scans_part3.tar.gz
Paper (PDF) Staunton_et_al_2001.pdf

An erythroid differentiation signature predicts response to lenalidomide in Myelodysplastic Syndrome

Datasets files and prediction program (R script)
Sample annotation file journal.pmed.0050035.st001.xls
CEL files revlimid_files (1).zip

Identification of RPS14 as a 5q- syndrome gene by RNA interference screen

Sample information and data matrix (Excel) 5q_shRNA_affy.xls
GCT gene expression dataset 5q_GCT_file.gct
RES gene expression dataset 5q_GCT_file.res
CEL files set

An RNA interference model of RPS19 deficiency in Diamond Blackfan Anemia recapitulates defective hematopoiesis and rescue by dexamethasone: identification of dexamethasone responsive genes by microarray

Manuscript Ebert, RPS19 and dex in DBA, Blood 2005.pdf
Commentary in Blood RPS19 paper commentary, Blood 2005.pdf
Gene expression data: CEL files
Supplementary Figure S1 Figure S1.pdf
Supplementary Table S1 TableS1.xls
Supplementary Table S2 TableS2.xls
Supplementary Table S3 TableS3.xls
Supplementary Table S4 TableS4.xls
Supplementary Table S5 TableS5.xls

Identification of endoglin as a functional marker that defines long-term repopulating hematopoietic stem cells

Supplementary information endoglin.doc

Integrative Transcriptome Analysis Reveals Common Molecular Subclasses of Human Hepatocellular Carcinoma

HCC subclass meta-analysis signature genes Hoshida_HCC_meta_analysis_3subclass_signature.txt

Sanger Cell Line Project

Sanger Cell Line Project Affymetrix Data Sanger_Cell_Line_Project_Affymetrix_QCed_Data_n798.gct
Sanger Cell Line Project Affymetrix Data Information Sanger_affy_n798_sample_info_published.xls
Instruction to obtain CEL files for Affymetrix Data How_to_obtain_CEL_files_for_SCLP_Affymetrix_data.doc
Sanger Cell Line Project miR Raw Data
Sanger Cell Line Project miR Normalized Data
Sanger Cell Line Project miR Sample Info Sanger800_miRNA.stl

Gene expression-based chemical genomics identifies rapamycin as a modulator of MCL-1 and glucocorticoid resistance in leukemia

ALL Patient Samples Children_NE.gct
Rapamycin treated CEM-C1 cell line(24 hour). Rap24hour_Control.gct
Rapamycin treated CEM-C1 cell line(3 hour). Rap3hour_control.gct
Resistant Markers p-value <=0.0005 Res_p0005.gct
Sensitive Markers p-value <=0.0005 Sens_p0005.gct
Resistant Markers p-value <=0.001 Res_p001.gct
Sensitive Markers p-value <=0.001 Sens_p001.gct
Zip of all CEL files

Transformation from committed progenitor to leukaemia stem cell initiated by MLL-AF9

Normal Progenitor And Leukemic Samples Normals_Leu.gct
MLL-AF9 Immediate Samples MLL_AF9.gct
Metric:SNR; # significant genes 1334 (FDR<=0.02) HSC_FDR002.gct
SNR;592 genes;p-value<=0.01;FDR<=0.023 leuGMP.gct
Filtering: max-min=80;max/min=2.5 Normals_Leu.threshold_FDR01.gct
Filtering: max-min=80;max/min=2.5 300_HSCLeu_dn_0306.gct
Zip of CEL Files
Sample Key SampleKey.xls

Identification of distinct molecular phenotypes in acute megakaryoblastic leukemia by gene expression profiling

AMKL dataset, raw CEL files AMKL
AMKL dataset, sample information file Sample Information AMKL dataset.xls
consensus clustering of non-DS AMKL Consensus_Clustering_nonDS_AMKL.xls
marker selection by SAM: DS-TMD vs. DS-AMKL Marker_selection_SAM_DS_versus_TMD.xls
marker selection by SAM: DS-AMKL vs. non-DS-AMKL Marker_selection_SAM_DS_vs_NDS.xls
predictor of DS-AMKL vs. non-DS-AMKL PredictiionResults_d.xls
PDF copy of preprint bourquin_pnas_2006.pdf

MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia

File info MLL_supplemental_file_info.txt
Scan ids, scaling factors and figure key scaling_factors_and_fig_key.txt
Expression data, scaled (Affymetrix expression_data.txt
Expression data as above, with Affymetrix A/P calls expression_data_plus_APcalls.txt
Raw data (CEL files) ALL scans part 1 (40MB) mll_scans_ALL1.tar.gz
Raw data (CEL files) ALL scans part 2 (41MB) mll_scans_ALL2.tar.gz
Raw data (CEL files) MLL scans part 1 (47MB) mll_scans_MLL1.tar.gz
Raw data (CEL files) MLL scans part 2 (47MB) mll_scans_MLL2.tar.gz
Raw data (CEL files) AML scans part 1 (33MB) mll_scans_AML1.tar.gz
Raw data (CEL files) AML scans part 2 (34MB) mll_scans_AML2.tar.gz

Class prediction and discovery using gene expression data

Paper (PDF) Slonim_et_al_2000.pdf
Paper (PS)

Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression

Paper (PDF) Golub_et_al_1999.pdf
Files description Files_descriptions.txt
Experimental protocol protocol.html
Rescaling factors table_ALL_AML_rfactors.txt
Samples table (Word) table_ALL_AML_samples.rtf
Samples table (text) table_ALL_AML_samples.txt
Train dataset (Excel) data_set_ALL_AML_train.tsv
Train dataset (text) data_set_ALL_AML_train.txt
Test datset (Excel) data_set_ALL_AML_independent.tsv
Test dataset (text) data_set_ALL_AML_independent.txt
Prediction results (Word) table_ALL_AML_predic.rtf
Prediction results (text) table_ALL_AML_predic.txt
Original and supplemental figures (Powerpoint) Figures_original_plus_suppl.ppt
Train dataset in WI format ALL_vs_AML_train_set_38_sorted.res
Train dataset class vector in WI format ALL_vs_AML_train_set_38_sorted.cls
Test dataset in WI format Leuk_ALL_AML.test.res
Test dataset class vector in WI format Leuk_ALL_AML.test.cls

A Transcriptional Profiling Study of CAAT/Enhancer Binding Protein Targets Identifies Hepatocyte Nuclear Factor 3beta as a Novel Tumor Suppressor in Lung Cancer

Raw data CAN_6-15-04_Halmos.xls

Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes

Key to scan names datasetA_scans.txt
Raw data (CEL files) ADENOS part 1 (~53MB) LUNG_scans_ADENO_part1.tar.gz
Raw data (CEL files) ADENOS part 2 (~53MB) LUNG_scans_ADENO_part2.tar.gz
Raw data (CEL files) ADENOS part 3 (~53MB) LUNG_scans_ADENO_part3.tar.gz
Raw data (CEL files) ADENOS part 4 (~54MB) LUNG_scans_ADENO_part4.tar.gz
Raw data (CEL files) ADENOS part 5 (~53MB) LUNG_scans_ADENO_part5.tar.gz
Raw data (CEL files) ADENOS part 6 (~53MB) LUNG_scans_ADENO_part6.tar.gz
Raw data (CEL files) ADENOS part 7 (~54MB) LUNG_scans_ADENO_part7.tar.gz
Raw data (CEL files) ADENOS part 8 (~55MB) LUNG_scans_ADENO_part8.tar.gz
Raw data (CEL files) ADENOS part 9 (~55MB) LUNG_scans_ADENO_part9.tar.gz
Raw data (CEL files) ADENOS part 10 (~53MB) LUNG_scans_ADENO_part10.tar.gz
Raw data (CEL files) Normal Lung (~48MB) LUNG_scans_NORM.tar.gz
Raw data (CEL files) Small Cell (~17MB) LUNG_scans_SMC.tar.gz
Raw data (CEL files) Squamous (~61MB) LUNG_scans_SQ.tar.gz
Raw data (CEL files) Carcinoids (~56MB) LUNG_scans_COID.tar.gz
DatasetA, all genes, rank-inv. scaled, averaged DatasetA_12600gene.txt.gz
All scans, raw AFFY av.diff and A/P vals Lung_DATASETA_scans_noscale.res.gz
Variable genes used to cluster DatasetA DatasetA_3312genesetdescription_sd50.txt
DatasetB, all genes, rank inv. scaled, av'd DatasetB_12600gene_Fig2order.txt.gz
DatasetB, 675 genes DatasetB_675gene.txt.gz

Lesional gene expression profiling in cutaneous T-cell lymphoma reveals natural clusters associated with disease outcome

Samples' Annotation SampleAnnotation.xls
RMA, un-log2 transformed data ('.res' format) ctl.rma2.res.gz
Raw '.CEL' files (1st 21 chips)
Raw '.CEL' files (2nd 21 chips)
Raw '.CEL' files (last 21 chips)

NFkB activity, function and target gene signatures in primary mediastinal large B-cell lymphoma and diffuse large B-cell lymphoma subtypes

Manuscript FF_NFKB_manuscr_revised.pdf
Supplementary Information FF_NFKB_suppl_revised.pdf
ASH '04 slides ASH04_friedrich.pdf
Super-repressor expression data (RMA) super.rma.res.gz
Super-repressor expression data (MAS5) super.mas5.res.gz

Molecular profiling of diffuse large B-cell lymphoma reveals a novel disease subtype with brisk host inflammatory response and distinct genetic features

Manuscript DLBCL_manuscript.pdf
Figures DLBCL_manuscript.ppt
References DLBCL_manuscript.enl
Supplementary Information DLBCL_supplement.pdf
Raw data (mean scaled, see supplement) LF_ms_dlbcl_new_womedia.res.gz
Raw data (unscaled) LF_dlbcl_new_womedia.res.gz
Sample annotation sample_annotation.xls
2118 genes (Top 5% by F statistic) genelist.50mean.fstat95.txt
4246 genes (Top 10% by F statistic) genelist.50mean.fstat90.txt
ASH meeting presentation (slides) ASH04.pdf
ASH meeting presentation (handouts) ASH04handouts.pdf
UNIGENE and GenBank annotation of Affymetrix Affy2UnigeneGenBank.xls
UNIGENE and GenBank annotation of Lymphochip Lymphochip2UnigeneGenBank.xls
Lymphochip 2 Affymetrix mapping Lymphochip2Affy.xls
Consensus Clusters' Markers LF_ms_dlbcl_new_womedia_fstat95.DB2.unique.xls

The molecular signature of mediastinal large B-cell lymphoma differs from that of other diffuse large B-cell lymphomas and shares features with classical Hodgkin lymphoma

Raw (unormalized) data ('.res' format) gzip compressed Mediastinal.res.gz
Class membership (DLBCL or MLBCL?) Mediastinal.txt
Supplementary Information SupplementaryInfo.pdf
CEL files (A chip)
CEL files (B chip)
Chip-to-sample mapping scan2sample.txt

Diffuse Large B-Cell Lymphoma Outcome Prediction by Gene Expression Profiling and Supervised Machine Learning

Supplemental Information (Microsoft Word) Shipp_et_al_Supplementary_Information_v5.doc
Supplemental Information (pdf) Shipp_et_al_Supplementary_Information_v5.pdf
DLBCL vs. FL morphology res file lymphoma_8_lbc_fscc2_rn.res
DLBCL vs. FL morphology cls file lymphoma_8_lbc_fscc2.cls
DLBCL outcome res file lymphoma_8_lbc_outcome_rn.res
DLBCL outcome cls file lymphoma_8_lbc_outcome.cls
Clinical Data Table lymphoma_clinical_011127.xls
Validation Marker Mapping - UniGene Mapping lymphoma_common_unigene.xls
DLBCL CEL files (DLBC1 - DLBC29) (66M) Lymph_LBC_1-29.CEL.tar.gz
DLBCL CEL files (DLBC30 - DLBC58) (66M) Lymph_LBC_30-58.CEL.tar.gz
FSCC CEL files (FSCC1 - FSCC19) (43M) Lymph_FSCC_1-19.CEL.tar.gz
Expanded Figure 5 from paper Lymphoma_Shipp_et_al_Fig5.xls
README describing downloadable files Readme
Paper (PDF) Shipp_et_al_2002.pdf

Genomic analysis of metastasis reveals an essential role for RhoC

Paper (PDF) Clark_et_al_2000.pdf
Human A375 Table I (Excel) Human_data_set_A375_table_I.xls
Human A375 Table II (Excel) Human_data_set_A375_table_II.xls
Mouse B16 Table I (Excel) Mouse_data_set_B16_table_I.xls
Human A375 Table I (Textl) Human_data_set_A375_raw1.txt
Human A375 Table II (Text) Human_data_set_A375_raw2.txt
Mouse B16 Table I (Text) Mouse_data_set_B16_raw.txt

Erra and Gabpa/b specify PGC-1a-dependent oxidative phosphorylation gene expression that is altered in diabetic muscle

PGC-1-alpha timecourse (scaled expression data) Scaled_Expression_Data.xls
Mouse promoters refGene_mm3_PERI_TSS_1000
Mouse:human masked promoters mm3_1k_1k_70_10_mouse
Gene list for Figure 1 correlogram 5034_Genes_Correlogram_Figure_1.xls

Integrated Analysis of Protein Composition, Tissue Diversity, and Gene Regulation in Mouse Mitochondria

Supplemental Table S1 Supplemental Table S1.xls
Supplemental Table S2 Supplemental Table S2.xls
Supplemental Table S3 Supplemental Table S3.xls
Supplemental Table S4 Supplemental Table S4.xls

PGC-1a Responsive Genes Involved in Oxidative Phosphorylation are Coordinately Downregulated in Human Diabetes

Human diabetes expression data reannotate_select_cal.eis.gz
Phenotype data Phenotype_Data.xls
Probe sets corresponding to gene sets all_pathways.tar.gz
GSEA results for NGT versus DM2 GSEA_results_NGT_vs_DM2.xls
OXPHOS homolog expression in mouse mouse_expression.tar.gz

Evidence for a Molecular Signature of Metastasis in Primary Solid Tumors

Manuscript Metastases_Nature_Genetics_030131_ng1060.pdf
Supplement Mets_Supplement_Revised_Final_110802_SR.pdf
Supplemental Information Mets_Supplement_Information_041110_KR.xls
Dataset A - Global Cancer Map Tumor vs. Met. DatasetA_Tum_vs_Met.res
Dataset B - Lung Outcome DatasetB_Lung_outcome.res
Dataset C - Rosetta Breast Outcome DatasetC_Rosetta_breast_outcome.res
Dataset D - Prostate Outcome DatasetD_prostate_outcome.res
Dataset E - Medulloblastoma Outcome DatasetE_medulloblastoma_outcome.res
Dataset F - LBC Lymphoma Outcome DatasetF_lymphoma_outcome.res
Table of Contents Table_of_Contents.pdf

Gene Expression Correlates of Clinical Prostate Cancer Behavior

Prostate tumor and normal samples Prostate_TN_final0701_allmeanScale.res
Prostate tumor samples Prostate_T_allmeansquare.res
Prostate capsular penetration samples Prostate_CapPen_061901_allmeanscale.res
Prostate surgical margin samples Prostate_Margin_allmeanscale.res
Prostate outcome samples Prostate_nonrecur_vs_recur_scaled.res
Document describing each of the downloadable files. Readme
Prostate Normal Sample CEL files (N01 - N31) (65M) prostate_normal_N01-N31.CEL.tar.gz
Prostate Normal Sample CEL Files (N32 - N62) (65M) prostate_normal_N32-N62.CEL.tar.gz
Prostate Tumor Sample CEL files (T01 - T30) (66M) prostate_tumor_T01-T30.CEL.tar.gz
Prostate Tumor Sample CEL files (T31 - T62) (66M) prostate_tumor_T31-T62.CEL.tar.gz
Supplementary Information (pdf) SuppInfo_CCv3.pdf
Figure 1, 2 and 3 from paper (pdf) Figure1_2and3.pdf
Table 1 from paper (pdf). Table1v2.pdf
Supplementary Figure 1 (pdf) Supplemental_Figure1.pdf
Supplementary Figures 2 and 3 (pdf) Supplemental_Figure2and3.pdf
Supplementary Figure 4 (pdf) Supplemental_Figure4.pdf
Supplementary Figure 5 (pdf) Supplemental_Figure5.pdf
Supplementary Figure Legends (pdf) SupplementalFigureLegendsRv1.pdf

Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1.

B-scores data file AchillesData19celllines.txt
B-scores data file description AchillesData19celllines File Description.doc

Genomic Approaches to Hematologic Malignancies

Manuscript Review Genomics of Heme Malig, Blood 2004.pdf

Microarray Data Mining: Facing the Challenges

Article Microarray_data_mining_facing _the_challenges.pdf

DNA Microarrays in Cancer: Realising the Promise of Personalised Medicine

Paper Lancet Commentary.pdf

Cancer Genomics and Molecular Pattern Recognition

Paper (PDF) Humana_final_Ch_06_23_2002 SR.pdf

DNA Microarrays in Clinical Oncology

Review Article JCO.pdf

Genome-Wide Views of Cancer

Paper (PDF) Golub_2001.pdf

GENOMICS: Journey to the Center of Biology

paper (PDF) LanderWeinberg.pdf

Characterizing the cancer genome in lung adenocarcinoma

Paper text Weir_Nature2007.doc
Figure 1 fig1.pdf
Figure 2 fig2.pdf
Figure 3 fig3.pdf
Full supplementary information Weir_supplement.pdf
Sample information file - TSP samples Newsampleinfo_TSP.xls
Sample information file - non-TSP samples sampleinfo_non-TSP.xls
Viewable file of GISTIC scores for high threshold TSP_highthresh_scores.txt
Viewable file of GISIC scores for low threshold TSP_lowthresh_scores.txt

Allele-specific amplification in cancer revealed by SNP array analysis.

Manuscript LaFramboise.pdf

Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma.

Supplementary Figure S1 Garraway-s1.pdf
Supplementary Figure S2 Garraway-s2.pdf
Supplementary Figure S3 Garraway-s3.pdf
Supplementary Figure S4 Garraway-s4.pdf
Supplementary Figure S5 Garraway-s5.pdf
Supplementary Figure Legends Garraway-s6.doc
Supplementary Methods Garraway-s7.doc
Supplementary Table S1 Garraway-s8.doc
Supplementary Table S2 Garraway-s9.doc
Supplementary Table S3 Garraway-s10.doc
Supplementary Notes Garraway-s11.doc
Manuscript Garraway.pdf

Homozygous deletions and chromosome amplifications in human lung carcinomas revealed by single nucleotide polymorphism array analysis.

Supplemental data Zhao_2005_Suppl.pdf
Manuscript Zhao_2005.pdf

Molecular characterization of the tumor microenvironment in breast cancer.

Manuscript Allinen.pdf

Genome coverage and sequence fidelity of phi29 polymerase-based multiple strand displacement whole genome amplification.

Manuscript Paez_NAR.pdf

An integrated view of copy number and allelic alterations in the cancer genome using single nucleotide polymorphism arrays.

Manuscript Zhao_2004.pdf

High-resolution single-nucleotide polymorphism array and clustering analysis of loss of heterozygosity in human lung cancer cell lines.

Supplemental Figure 1 Janne_s1.jpg
Supplemental Tables Janne_supp_tables.doc
Manuscript Janne.pdf

dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data.

Manuscript Lin.pdf

Loss of heterozygosity and its correlation with expression profiles in subclasses of invasive breast cancers.

Manuscript Wang.pdf

Genome-wide loss of heterozygosity analysis from laser capture microdissected prostate cancer using single nucleotide polymorphic allele (SNP) arrays and a novel bioinformatics platform dChipSNP.

Manuscript Lieberfarb.pdf
Supplementary Figure 1 Lieberfarb_s1.pdf
Supplementary Table 1 Lieberfarb_s2.pdf
LOH Data LieberfarbSummary LOH data.txt

Loss-of-heterozygosity analysis of small-cell lung carcinomas using single-nucleotide polymorphism arrays.

Manuscript Lindblad-Toh.pdf

Expression profiling of EWS/FLI identifies NKX2.2 as a critical target gene in Ewing's sarcoma

Manuscript Smith et al.pdf
Preview article Cancer Cell preview.pdf
CEL file descriptions Smith_et_al_CEL_file_list.xls
CEL files for knockdown samples
CEL files for inducible samples
Supplemental appendix 1 Smith, et al., supplemental appendix 1.doc
Supplemental appendix 2 Smith, et al., supplemental appendix 2.xls
Supplemental appendix 3 Smith, et al., supplemental appendix 3.xls

The Ewing's Sarcoma Oncoprotein EWS/FLI Induces a p53-Dependent Growth Arrest in Primary Human Fibroblasts

Manuscript (PDF) CCELL.1_4_393.56.pdf
Appendix 1: Overview of appendices and methods (MS Word) Appendix 1.doc
Appendix 1: Overview of appendices and methods (PDF) Appendix 1.pdf
Appendix 2: Expression data from the tet-EF cell expt (Excel) Appendix_2.xls
Appendix 3: cls file for tet-EF cell knn analysis from fig. 2 Appendix_3.cls
Appendix 4a: cls file for Ewing's sarcoma Appendix_4a.cls
Appendix 4b: cls file for Burkitt's lymphoma Appendix_4b.cls
Appendix 4c: cls file for neuroblastoma Appendix_4c.cls
Appendix 4d: cls file for rhabdomyosarcoma Appendix_4d.cls
Appendix 5: limited tet-EF dataset (Excel) from fig. 2 Appendix_5.xls
Appendix 6: Limited SRCT dataset (Excel) from fig. 2 Appendix_6.xls
Appendix 7a: Ewing's-specific genes (Excel) Appendix_7a.xls
Appendix 7b: Burkitt's-specific genes (Excel) Appendix_7b.xls
Appendix 7c: neuroblastoma-specific genes (Excel) Appendix_7c.xls
Appendix 7d: rhabdomyosarcoma-specific genes (Excel) Appendix_7d.xls
Appendix 8: tet-EF cell upregulated genes (Excel) Appendix_8.xls
Appendix 9: SOM clusters from tet-EF cells (Excel) Appendix_9.xls
CEL files 1/2 (zip file, 15 MB) run1.tar.gz
CEL files 2/2 (zip file, 14 MB) run2.tar.gz
Sample descriptions for CEL files run_samples.txt

The Six1 Homeoprotein Stimulates Tumorigenesis via Reactivation of Cyclin A1

gene expression data data.res

A Mechanism of Cyclin D1 Action Encoded in the Patterns of Gene Expression in Human Cancer

Supplementary Information 1 (cyclin D1 nearest neighbors) SI1.txt
Supplementary Information 2 (GCM KSS) SI2.txt
Supplementary Information 3 (prostate KSS) SI3.txt
Supplementary Information 4 (lung KSS) SI4.txt
Supplementary Information 5 (brain KSS) SI5.txt
Supplementary Information 6 (NCI60 KSS) SI6.txt
Supplementary Information 7 (chromosome coordinates) SI7.pdf
Supplementary Information 8 (competitor oligonucleotides) SI8.pdf
Supplementary Information 9 (additional panels for Figure 6D) SI9.pdf
Supplementary Information 10 (additional panels for Figure 6E) SI10.pdf
raw gene expression data raw_data.res

c-Myc is a critical target for c/EBPalpha in granulopoiesis.

Paper (PDF) Johansen_et_al_2000.pdf

Expression analysis with oligonucleotide microarrays reveals that MYC regulates genes involved in growth, cell cycle, signaling, and adhesion

Supplementary datasets and tables data_set_myc_genes.html
Supplementary figures figures_myc_genes.html
MYC genes dataset: ASCII data_set_myc_genes.txt
MYC genes dataset: Excel data_set_myc_genes.xls
Paper (PDF) Coller_et_all_2000.pdf

MicroRNA Dynamics in the Stages of Tumorigenesis Correlate with Hallmark Capabilities of Cancer

Supplemental Table 1 OlsonSupTable1.xls
Supplemental Table 2 OlsonSupTable2.xls
Supplemental Table 3 OlsonSupTable3.doc
Supplemental Table 4 OlsonSupTable4.xls

microRNA-mediated control of cell fate in megakaryocyte-erythrocyte progenitors

Supplemental Data in pdf Lu_Supplemental_Data_dev_cell.pdf
Table S1 Supplementary_Table1.xls
Table S2 Supplementary_Table2.xls
Table S3 Supplementary_Table3.xls
Table S4, normalized expression data megamiR_data.normalized.log2.th6.gct

MicroRNA Expression Profiles Classify Human Cancers

Supplementary Table 1, probe information supplementary_table_1.xls
Supplementary Table 2, sample information supplementary_table_2.xls
Supplementary Table 3, N vs T predition result supplementary_table_3.xls
Suppl. Table 4, poorly differentiated tumor prediction result supplementary_table_4.xls
microRNA data, miGCM_218 collection miGCM_218.gct
microRNA data, acute lymphoblastic leukemia ALL.gct
microRNA data, for samples with both miRNA and mRNA data Common_miRNA.gct
microRNA data, mouse lung samples mLung.gct
microRNA data, poorly differentiated tumors PDT_miRNA.gct
microRNA data, HL-60 differentiation HL60.gct
microRNA data, erythroid differentiation Erythroid.gct
mRNA data, for samples with both miRNA and mRNA data
mRNA data, poorly differentiated tumors
microRNA data, raw data
Expression data in MAGE-ML format
Raw data in MAGE-ML format
Frequently Asked Questions FAQ_miGCM.html
Paper Nature_miR_classify_cancer.pdf
Supplementary Notes Supplementary_Notes.pdf