gse4335pheno: Phenotype data of GSE4335.
In survJamda.data: Data for Package 'survJambda'
Description
Usage
Format
Source
References
See Also
Examples
Description
Data such as patients' information, tumor characteristics, samples information related to GSE4335.
Usage
1
Format
A data frame with 115 observations on the following 17 variables.
Array_IDa factor with levels shac091 shac092 shac093 shac100 shac107 shac110 shac112 shac113 shaz104 shaz110 shaz112 shaz114 shaz116 shaz121 shaz124 shaz125 shaz126 shaz129 shaz131 shaz132 shaz133 shaz134 shaz135 shaz140 shbg109 shbg110 shbg128 shby020 shby021 shby022 shby028 shby033 shby035 shby037 shby038 shby039 shby040 shby041 shby042 shby043 shby046 shby049 shby050 shby051 shby236 shby245 shby249 svcc100 svcc101 svcc104 svcc105 svcc106 svcc107 svcc1077 svcc108 svcc111 svcc1114 svcc115 svcc118 svcc119 svcc120 svcc122 svcc124 svcc130 svcc131 svcc132 svcc134 svcc137 svcc51 svcc53 svcc55 svcc61 svcc68 svcc76 svcc78 svcc81 svcc83 svcc84 svcc87 svcc88 svcc89 svcc92 svcc93 svcc96 svcc98 svcc99 svj104 svl002 svl003 svl006 svl007 svl012 svl015 svl016 svl018 svl020 svl022 svl026 svl027 svl029 svl031 svl033 svl034 svl035 svl036 svl037 svl039 svl041 svl103 svl106 svl108 svl109 svl110 svn007 svn015
Patient_IDa factor with levels new_york_1 New_York_2 New_York_3 Norway_06FU Norway_10 Norway_100 Norway_101 Norway_102 Norway_104 Norway_109 Norway_11 Norway_111 Norway_112 Norway_12 Norway_14 Norway_15 Norway_16 Norway_17 Norway_18 Norway_19 Norway_2 Norway_21 Norway_22 Norway_24 Norway_26 Norway_27 Norway_29 Norway_32 Norway_37 Norway_39 Norway_4 Norway_41 Norway_43 Norway_47 Norway_48 Norway_5 Norway_51 Norway_53 Norway_55 Norway_56 Norway_57 Norway_6 Norway_61 Norway_63 Norway_64 Norway_65 Norway_7 Norway_74 Norway_75 Norway_8 Norway_80 Norway_81 Norway_83 Norway_85 Norway_90 Norway_92 Norway_95 Norway_96 Norway_98 Norway_FU01 Norway_FU02 Norway_FU04 Norway_FU05 Norway_FU07 Norway_FU08 Norway_FU09 Norway_FU10 Norway_FU11 Norway_FU12 Norway_FU14 Norway_FU15 Norway_FU16 Norway_FU17 Norway_FU18 Norway_FU19 Norway_FU20 Norway_FU22 Norway_FU23 Norway_FU24 Norway_FU25 Norway_FU26 Norway_FU27 Norway_FU29 Norway_FU30 Norway_FU35 Norway_FU37 Norway_FU39 Norway_FU40 Norway_FU41 Norway_FU43 Norway_FU44 Norway_FU45 Norway_H2 Norway_H3 Norway_H4 Norway_H5 Norway_H6 Stanford_14 Stanford_16 Stanford_17 Stanford_18 Stanford_2 Stanford_23 Stanford_24 Stanford_31 Stanford_35 Stanford_38 Stanford_4 Stanford_40 Stanford_44 Stanford_45 Stanford_46 Stanford_48 Stanford_6 Stanford_A
Sample_IDa factor with levels BC102B-BE BC104A-BE BC105A-BE BC106B-BE BC107B-BE BC108A-BE BC110B-BE BC111A-BE BC111B-BE BC112B-BE BC114A-BE BC115B-BE BC116A-BE BC117A-BE BC118B-BE BC119A-BE BC120A-BE BC121B-BE BC123B-BE BC124A-BE BC1257 BC125A-BE BC1369 BC14 BC16 BC17 BC18 BC2 BC201B-BE BC205A-BE BC206A-BE BC208A-BE BC210B-AF BC213B-BE BC214B-BE BC23 BC24 BC303B-BE BC305A-BE BC307B-BE BC308B-BE BC309A-BE BC31-0 BC35-0 BC38 BC40 BC402B-BE BC404B-BE BC405A-BE BC406A-2ndTUMOR BC44 BC45 BC46-LN46 BC48-0 BC4-LN4 BC503B-BE BC6 BC601A-BE BC605B-BE BC606B-AF BC608B-BE BC610A-BE BC702B-BE BC703B-BE BC704B-AF BC706A-BE BC708B-BE BC709B-BE BC710A-BE BC711B-BE BC713A-BE BC790 BC805A-BE BC807A-BE BC808A-BE BC-A BC-HBC2 BC-HBC3 BC-HBC4-T1 BC-HBC5 BC-HBC6 FU_01-BE FU_02-BE FU_04-BE FU_05-BE FU_06-BE FU_07-BE FU_08-BE FU_09-BE FU_10-BE FU_11-BE FU_12-BE FU_14-BE FU_15-BE FU_16-BE FU_17-AF FU_18-BE FU_19-BE FU_20-BE FU_22-BE FU_23-BE FU_24-BE FU_25-BE FU_26-BE FU_27-BE FU_29-BE FU_30-AF FU_35-BE FU_37-BE FU_39-BE FU_40-BE FU_41-BE FU_43-BE FU_44-BE FU_45-BE
Age_at_diagnosisa numeric vector
X.Status_0.A._1.AWD._2.DOD._3.DOC.a numeric vector
Overall_survival_.months.a numeric vector
Relapse.free_survival_.months.a numeric vector
X._ER_status_.0.neg._1.pos..a factor with levels 0 1 na
T_.tumor_size.a factor with levels 1 2 3 4 na
N_.node_status.a factor with levels 0 1 2 na x
M_.metastasis.a numeric vector
Gradea factor with levels 1 2 3 na
Histologya factor with levels DCIS Ductal Lobular Mucinous Papillary Pleomorph Undifferentiated
reference_sample_batch_ID_a factor with levels CRA CRB CRD CRF CRG
Microarray_batch..genesa factor with levels shac-23k shaz-49k shbg-49k shby-43k svcc-8k svj-8k svl-8k svn-8k
Commentsa factor
Previously_publisheda factor with levels no yes
Source
http://genome-www.stanford.edu/breast_cancer/robustness/data/SupplTable2.xls
References
Yasrebi H, Sperisen P, Praz V, Bucher P, 2009 Can Survival Prediction Be Imp
roved By Merging Gene Expression Data Sets?. PLoS ONE 4(10): e7431. doi:10.1371/journal.pone.0007431
See Also
Examples
1
survJamda.data documentation built on May 2, 2019, 2:13 p.m.
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Description Usage Format Source References See Also Examples
Description
Data such as patients' information, tumor characteristics, samples information related to GSE4335.
Usage
1 |
Format
A data frame with 115 observations on the following 17 variables.
Array_IDa factor with levels
shac091shac092shac093shac100shac107shac110shac112shac113shaz104shaz110shaz112shaz114shaz116shaz121shaz124shaz125shaz126shaz129shaz131shaz132shaz133shaz134shaz135shaz140shbg109shbg110shbg128shby020shby021shby022shby028shby033shby035shby037shby038shby039shby040shby041shby042shby043shby046shby049shby050shby051shby236shby245shby249svcc100svcc101svcc104svcc105svcc106svcc107svcc1077svcc108svcc111svcc1114svcc115svcc118svcc119svcc120svcc122svcc124svcc130svcc131svcc132svcc134svcc137svcc51svcc53svcc55svcc61svcc68svcc76svcc78svcc81svcc83svcc84svcc87svcc88svcc89svcc92svcc93svcc96svcc98svcc99svj104svl002svl003svl006svl007svl012svl015svl016svl018svl020svl022svl026svl027svl029svl031svl033svl034svl035svl036svl037svl039svl041svl103svl106svl108svl109svl110svn007svn015Patient_IDa factor with levels
new_york_1New_York_2New_York_3Norway_06FUNorway_10Norway_100Norway_101Norway_102Norway_104Norway_109Norway_11Norway_111Norway_112Norway_12Norway_14Norway_15Norway_16Norway_17Norway_18Norway_19Norway_2Norway_21Norway_22Norway_24Norway_26Norway_27Norway_29Norway_32Norway_37Norway_39Norway_4Norway_41Norway_43Norway_47Norway_48Norway_5Norway_51Norway_53Norway_55Norway_56Norway_57Norway_6Norway_61Norway_63Norway_64Norway_65Norway_7Norway_74Norway_75Norway_8Norway_80Norway_81Norway_83Norway_85Norway_90Norway_92Norway_95Norway_96Norway_98Norway_FU01Norway_FU02Norway_FU04Norway_FU05Norway_FU07Norway_FU08Norway_FU09Norway_FU10Norway_FU11Norway_FU12Norway_FU14Norway_FU15Norway_FU16Norway_FU17Norway_FU18Norway_FU19Norway_FU20Norway_FU22Norway_FU23Norway_FU24Norway_FU25Norway_FU26Norway_FU27Norway_FU29Norway_FU30Norway_FU35Norway_FU37Norway_FU39Norway_FU40Norway_FU41Norway_FU43Norway_FU44Norway_FU45Norway_H2Norway_H3Norway_H4Norway_H5Norway_H6Stanford_14Stanford_16Stanford_17Stanford_18Stanford_2Stanford_23Stanford_24Stanford_31Stanford_35Stanford_38Stanford_4Stanford_40Stanford_44Stanford_45Stanford_46Stanford_48Stanford_6Stanford_ASample_IDa factor with levels
BC102B-BEBC104A-BEBC105A-BEBC106B-BEBC107B-BEBC108A-BEBC110B-BEBC111A-BEBC111B-BEBC112B-BEBC114A-BEBC115B-BEBC116A-BEBC117A-BEBC118B-BEBC119A-BEBC120A-BEBC121B-BEBC123B-BEBC124A-BEBC1257BC125A-BEBC1369BC14BC16BC17BC18BC2BC201B-BEBC205A-BEBC206A-BEBC208A-BEBC210B-AFBC213B-BEBC214B-BEBC23BC24BC303B-BEBC305A-BEBC307B-BEBC308B-BEBC309A-BEBC31-0BC35-0BC38BC40BC402B-BEBC404B-BEBC405A-BEBC406A-2ndTUMORBC44BC45BC46-LN46BC48-0BC4-LN4BC503B-BEBC6BC601A-BEBC605B-BEBC606B-AFBC608B-BEBC610A-BEBC702B-BEBC703B-BEBC704B-AFBC706A-BEBC708B-BEBC709B-BEBC710A-BEBC711B-BEBC713A-BEBC790BC805A-BEBC807A-BEBC808A-BEBC-ABC-HBC2BC-HBC3BC-HBC4-T1BC-HBC5BC-HBC6FU_01-BEFU_02-BEFU_04-BEFU_05-BEFU_06-BEFU_07-BEFU_08-BEFU_09-BEFU_10-BEFU_11-BEFU_12-BEFU_14-BEFU_15-BEFU_16-BEFU_17-AFFU_18-BEFU_19-BEFU_20-BEFU_22-BEFU_23-BEFU_24-BEFU_25-BEFU_26-BEFU_27-BEFU_29-BEFU_30-AFFU_35-BEFU_37-BEFU_39-BEFU_40-BEFU_41-BEFU_43-BEFU_44-BEFU_45-BEAge_at_diagnosisa numeric vector
X.Status_0.A._1.AWD._2.DOD._3.DOC.a numeric vector
Overall_survival_.months.a numeric vector
Relapse.free_survival_.months.a numeric vector
X._ER_status_.0.neg._1.pos..a factor with levels
01naT_.tumor_size.a factor with levels
1234naN_.node_status.a factor with levels
012naxM_.metastasis.a numeric vector
Gradea factor with levels
123naHistologya factor with levels
DCISDuctalLobularMucinousPapillaryPleomorphUndifferentiatedreference_sample_batch_ID_a factor with levels
CRACRBCRDCRFCRGMicroarray_batch..genesa factor with levels
shac-23kshaz-49kshbg-49kshby-43ksvcc-8ksvj-8ksvl-8ksvn-8kCommentsa factor
Previously_publisheda factor with levels
noyes
Source
http://genome-www.stanford.edu/breast_cancer/robustness/data/SupplTable2.xls
References
Yasrebi H, Sperisen P, Praz V, Bucher P, 2009 Can Survival Prediction Be Imp roved By Merging Gene Expression Data Sets?. PLoS ONE 4(10): e7431. doi:10.1371/journal.pone.0007431
See Also
Examples
1 |
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