Thyroid Adenocarcinoma: Copy number analysis (GISTIC2)
(follicular cohort)
Maintained by Dan DiCara (Broad Institute)
Overview
Introduction

GISTIC identifies genomic regions that are significantly gained or lost across a set of tumors. The pipeline first filters out normal samples from the segmented copy-number data by inspecting the TCGA barcodes and then executes GISTIC version 2.0.17a (Firehose task version: 0.0.8).

Summary

There were 75 tumor samples used in this analysis: 10 significant arm-level results, 0 significant focal amplifications, and 7 significant focal deletions were found.

Results
Focal results

Figure 1. Genomic positions of amplified regions: the X-axis represents the normalized amplification signals (top) and significance by Q value (bottom). The green line represents the significance cutoff at Q value=0.25.

Figure 2. Genomic positions of deleted regions: the X-axis represents the normalized deletion signals (top) and significance by Q value (bottom). The green line represents the significance cutoff at Q value=0.25.

Table 1. Get Full Table Deletions Table - 7 significant deletions found. Click the link in the last column to view a comprehensive list of candidate genes. If no genes were identified within the peak, the nearest gene appears in brackets.

Cytoband | Q value | Residual Q value | Wide Peak Boundaries | # Genes in Wide Peak
--- | --- | --- | --- | ---
10q23.2 | 0.0039497 | 0.0039497 | chr10:78642142-94835212 | 111
Xq22.3 | 0.03092 | 0.03092 | chrX:107872289-108781115 | 2
3q13.31 | 0.084796 | 0.084796 | chr3:113800787-113953752 | 1
16q22.1 | 0.061838 | 0.084796 | chr16:61684449-90354753 | 304
4q25 | 0.14317 | 0.14317 | chr4:113203925-113439819 | 2
8q24.22 | 0.15515 | 0.14905 | chr8:56679786-134246717 | 361
4q31.21 | 0.23818 | 0.23818 | chr4:1-191154276 | 903
22q11.21 | 0.26482 | 0.23818 | chr22:1-51304566 | 560

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 10q23.2.

Table S1. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
BMPR1A
PTEN
hsa-mir-107
hsa-mir-346
ACTA2
ANXA11
FAS
GLUD1
GRID1
HHEX
HTR7
IDE
IFIT2
IFIT1
IFIT3
KCNMA1
KIF11
LIPA
MAT1A
PPP1R3C
RGR
RPS24
SFTPD
SNCG
MBL1P
LIPF
CH25H
BTAF1
PAPSS2
DLG5
MINPP1
KIF20B
PPIF
RPP30
NRG3
C10orf116
POLR3A
LDB3
CPEB3
WAPAL
IFIT5
LRIT1
ANKRD1
GHITM
PANK1
FAM190B
EXOC6
FAM35A
MARCH5
RNLS
ZMIZ1
STAMBPL1
MMRN2
FAM213A
TNKS2
TSPAN14
C10orf58
DYDC2
PCGF5
ATAD1
CDHR1
OPN4
ANKRD22
NUDT9P1
AGAP11
LIPJ
CFL1P1
DYDC1
EIF5AL1
HECTD2
FGFBP3
LOC170425
LOC219347
PLAC9
ZCCHC24
FLJ37201
LOC283050
LIPM
CYP26C1
LRIT2
SH2D4B
C10orf99
SLC16A12
MIR107
LOC439990
LOC439994
IFIT1B
MIR346
LOC642361
FAM25A
LIPK
LIPN
LOC643529
LOC650623
SFTPA1
FAM22A
FAM22D
LOC728190
LOC728218
SFTPA2
LOC100128292
LOC100132987
KLLN
LOC100188947
LOC100288974
FAS-AS1
LOC100507470
MARK2P9
MIR4679-1
MIR4679-2
MIR4678

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for Xq22.3.

Table S2. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
GUCY2F
IRS4

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 3q13.31.

Table S3. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
DRD3

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 16q22.1.

Table S4. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
CBFA2T3
CBFB
CDH1
CDH11
FANCA
MAF
hsa-mir-1910
hsa-mir-3182
hsa-mir-1972-2
hsa-mir-140
hsa-mir-1538
hsa-mir-328
AARS
AP1G1
AFG3L1P
AGRP
APRT
ZFHX3
C16orf3
CA5A
CA7
CALB2
CDH3
CDH5
CDH8
CDH13
CDH15
CDH16
COX4I1
CTRB1
CTRL
CYBA
DHODH
NQO1
DYNC1LI2
DPEP1
E2F4
FOXF1
FOXL1
FOXC2
GALNS
GAS8
GCSH
GLG1
HAS3
HP
HPR
HSBP1
HSD11B2
HSD17B2
HSF4
IRF8
KARS
LCAT
MC1R
CHST6
MVD
NFATC3
CHMP1A
PLCG2
PSKH1
PSMB10
PSMD7
RPL13
RRAD
ST3GAL2
SLC9A5
SLC12A4
SNTB2
SPG7
TAT
TERF2
TK2
ZNF19
ZNF23
GAN
SLC7A5
CDK10
TRADD
MBTPS1
CES2
NAE1
NOL3
TAF1C
SLC7A6
USP10
ATP6V0D1
BCAR1
C16orf7
KIAA0513
PIEZO1
DHX38
IST1
ATP2C2
CLEC3A
CHST4
MPHOSPH6
NUTF2
COX4NB
TUBB3
CFDP1
CTCF
NFAT5
WWP2
PRDM7
DDX19B
GABARAPL2
MON1B
TCF25
PHLPP2
ZCCHC14
KIAA0182
ATMIN
COTL1
MLYCD
SF3B3
CES3
ADAT1
CHST5
EDC4
PLA2G15
COG4
PLEKHG4
LRRC29
CPNE7
VPS4A
IL17C
NOB1
TMEM208
FHOD1
ANKRD11
ZDHHC1
OSGIN1
PARD6A
CKLF
NIP7
FAM96B
GINS2
TPPP3
TRAPPC2L
WWOX
BCMO1
TERF2IP
PRMT7
NECAB2
KLHDC4
HYDIN
DEF8
DUS2L
CHTF8
TXNL4B
BANP
PDPR
RFWD3
LRRC36
DDX19A
FBXL8
SMPD3
ZNF821
ZDHHC7
VAC14
FTSJD1
DDX28
TSNAXIP1
CENPN
C16orf61
THAP11
JPH3
PDP2
RANBP10
VAT1L
KIAA1609
WFDC1
PDF
DPEP2
DPEP3
MTHFSD
ACD
DBNDD1
FA2H
FAM65A
TMEM231
TMCO7
WDR59
ELMO3
KLHL36
FBXO31
ESRP2
CENPT
C16orf70
CYB5B
CMIP
GFOD2
CDT1
MAP1LC3B
PMFBP1
DYNLRB2
HSDL1
CRISPLD2
C16orf48
SLC7A6OS
COG8
SPIRE2
ZNF469
B3GNT9
CIRH1A
ZNRF1
CNTNAP4
MARVELD3
MTSS1L
CENPBD1
ZNF276
KCNG4
SDR42E1
CMTM1
PKD1L2
RNF166
EXOSC6
C16orf46
DNAAF1
NRN1L
CMTM3
SPATA2L
C16orf55
ZC3H18
CDYL2
TMEM170A
SLC38A8
ZFP90
RLTPR
KCTD19
CMTM4
CMTM2
BEAN1
SLC22A31
IL34
TMED6
FLJ30679
LOC146513
ZFPM1
ADAD2
ZFP1
ADAMTS18
MGC23284
LINC00311
LDHD
FUK
MLKL
ZNF778
ACSF3
CCDC79
CES4A
EXOC3L1
LINC00304
LOC283867
HTA
LOC283922
NUDT7
PDXDC2P
CLEC18C
SNAI3
FAM92B
ATXN1L
PKD1L3
CLEC18A
CTU2
C16orf86
PABPN1L
LOC400548
LOC400550
LOC400558
C16orf74
MIR140
CTRB2
MIR328
CLEC18B
SNORD68
KIAA0895L
SNORD71
SNORD111
LOC727710
LOC729513
LOC732275
SNORD111B
LOC100128881
LOC100129617
LOC100130015
LOC100130894
SYCE1L
LOC100287036
MIR1538
MIR1972-1
MIR1910
SNORA70D
MIR3182
MIR1972-2
LOC100505865
LOC100506083
LOC100506172
C16orf95
CKLF-CMTM1
MIR4720
MIR4722
MIR4719

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 4q25.

Table S5. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
NEUROG2
ALPK1

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 8q24.22.

Table S6. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
COX6C
EXT1
MYC
PLAG1
NCOA2
CHCHD7
hsa-mir-1208
hsa-mir-1207
hsa-mir-1205
hsa-mir-1204
hsa-mir-548d-1
hsa-mir-2053
hsa-mir-548a-3
hsa-mir-3151
hsa-mir-1273
hsa-mir-875
hsa-mir-3150
hsa-mir-3149
hsa-mir-2052
hsa-mir-124-2
ADCY8
ANGPT1
ANXA13
ASPH
ATP6V1C1
OSGIN2
CA1
CA2
CA3
CA8
CALB1
RUNX1T1
CDH17
CRH
CYP7A1
DECR1
DPYS
E2F5
EYA1
FABP4
FABP5
GEM
HAS2
HNF4G
IL7
IMPA1
EIF3E
KCNQ3
KCNS2
LYN
MATN2
MMP16
MOS
MYBL1
NBN
NDUFB9
NOV
ODF1
TNFRSF11B
PDE7A
ENPP2
PENK
PMP2
POLR2K
POU5F1B
PKIA
PVT1
PEX2
RAB2A
RAD21
RPL7
RPL30
RPS20
SDC2
SDCBP
SLA
SNTB1
SPAG1
SQLE
STK3
TAF2
TCEB1
TERF1
TG
KLF10
TPD52
TRHR
TRPS1
TTPA
COL14A1
UQCRB
YWHAZ
FZD6
NSMAF
EIF3H
RIPK2
GGH
WISP1
CPNE3
TRPA1
CCNE2
EBAG9
MSC
KCNB2
CYP7B1
MTFR1
TTC35
RIMS2
TOX
MTSS1
PTDSS1
KIAA0196
HHLA1
TRIB1
HRSP12
PGCP
ARFGEF1
COLEC10
POP1
COPS5
WWP1
STMN2
RNF139
ZHX1
ZHX2
EFR3A
RRS1
SULF1
ZFPM2
HEY1
TRAM1
LRRC6
LY96
SGK3
RAD54B
DCAF13
RNF19A
KIAA1429
C8orf71
RGS22
PTTG3P
SNORA72
SNORD54
PABPC1
KCNV1
STAU2
MTBP
BHLHE22
MRPS28
MRPL13
ATAD2
ASAP1-IT1
LRP12
RRM2B
ASAP1
MTERFD1
PI15
ZC2HC1A
PHF20L1
LACTB2
FAM82B
ZNF706
UBR5
FAM49B
AZIN1
OTUD6B
GDAP1
PDP1
CNGB3
ESRP1
IMPAD1
TMEM70
TRMT12
OXR1
WDYHV1
ARMC1
UBE2W
LAPTM4B
C8orf39
TMEM55A
CHD7
SYBU
INTS8
PAG1
GSDMC
C8orf44
JPH1
ENY2
CPA6
PRDM14
SNX16
NECAB1
DEPTOR
ZBTB10
DSCC1
DERL1
PLEKHF2
ZFAND1
ZFHX4
NIPAL2
CSPP1
BAALC
GRHL2
VCPIP1
PREX2
SLC25A32
TM7SF4
SLCO5A1
CRISPLD1
TATDN1
NACAP1
NCALD
UTP23
TRIM55
C8orf76
NUDCD1
FAM83A
LRRCC1
TSPYL5
DNAJC5B
PSKH2
FAM110B
MED30
TMEM67
MTDH
CHMP4C
PKHD1L1
WDR67
HPYR1
TP53INP1
TGS1
MAL2
CSMD3
FBXO32
SLC26A7
CTHRC1
OSR2
C8orf34
ZNF572
FAM92A1
C8orf38
ABRA
TMEM71
ADHFE1
UBXN2B
DCAF4L2
RALYL
TMEM65
LOC157381
RDH10
C8orf56
ANKRD46
FAM84B
C8orf37
VPS13B
SLC7A13
TMEM74
FAM91A1
C8orf45
CLVS1
C8orf84
CNBD1
SLC30A8
SNX31
TMEM64
SDR16C5
C8orf47
ATP6V0D2
YTHDF3
C8orf46
REXO1L1
NSMCE2
C8orf83
DPY19L4
FBXO43
LOC286177
NKAIN3
LOC286184
LOC286186
PPP1R42
LOC286189
LOC286190
KLHL38
RSPO2
SLC10A5
CA13
XKR9
LOC389676
RBM12B
LOC392232
GDF6
LOC401463
C8orf59
SAMD12
MIR124-2
FER1L6-AS1
FLJ39080
FLJ46284
FLJ42969
C8orf85
LINC00251
SAMD12-AS1
HAS2-AS1
ZNF704
C8orf69
SNHG6
SNORD87
LINC00535
UG0898H09
RAD21-AS1
FABP9
FABP12
FER1L6
MIR599
LOC727677
LOC728724
OC90
MIR875
LOC100127983
LOC100128126
TCF24
LOC100130155
LOC100130231
LOC100130298
LOC100130301
LRRC69
LOC100131726
LOC100132891
LOC100192378
REXO1L2P
LOC100288748
MIR1205
MIR1206
MIR1207
MIR1204
MIR2053
MIR2052
MIR1208
MIR3150A
MIR3151
LOC100499183
LOC100500773
MIR3150B
MIR3610
LOC100505659
LOC100505676
LOC100505718
LOC100507117
LOC100507632
LOC100507651
C8orf44-SGK3
ZHX1-C8ORF76
MIR378D2
MIR4661
MIR4663
MIR4471
MIR4470
LOC100616530
PCAT1
LINC00536
FSBP

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 4q31.21.

Table S7. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
FGFR3
IL2
KDR
KIT
PDGFRA
RAP1GDS1
WHSC1
PHOX2B
DUX4
CHIC2
TET2
FBXW7
FIP1L1
hsa-mir-1305
hsa-mir-4276
hsa-mir-548t
hsa-mir-1979
hsa-mir-3140
hsa-mir-548g
hsa-mir-3139
hsa-mir-2054
hsa-mir-1973
hsa-mir-577
hsa-mir-1243
hsa-mir-302b
hsa-mir-297
hsa-mir-576
hsa-mir-1255a
hsa-mir-575
hsa-mir-1269
hsa-mir-574
hsa-mir-1255b-1
hsa-mir-4275
hsa-mir-573
hsa-mir-218-1
hsa-mir-572
hsa-mir-3138
hsa-mir-548i-2
hsa-mir-95
hsa-mir-4274
hsa-mir-943
hsa-mir-571
ADD1
ADH1A
ADH1B
ADH1C
ADH4
ADH5
ADH6
ADH7
ADRA2C
AFM
AFP
AGA
ALB
AMBN
ANK2
SLC25A4
ANXA2P1
ANXA3
ANXA5
APBB2
AREG
RHOH
ART3
ATOH1
ATP5I
NKX3-2
BMP3
BMPR1B
BST1
BTC
CAMK2D
CASP3
CASP6
CCKAR
CCNA2
CCNG2
SCARB2
CD38
LRBA
CDS1
CLGN
CENPC1
CENPE
CLCN3
CNGA1
CPE
CRMP1
CSN1S1
CSN2
CSN3
CTBP1
CTSO
DGKQ
DCK
DCTD
DHX15
DMP1
DRD5
DSPP
EDNRA
EGF
EIF4E
ELF2
ENPEP
EPHA5
EREG
ETFDH
EVC
F11
FABP2
ACSL1
FAT1
FGA
FGB
FGF2
FGF5
FGG
FRG1
GAB1
GABRA2
GABRA4
GABRB1
GABRG1
GAK
GC
GK2
GK3P
GLRB
GNRHR
GPM6A
GRK4
GRIA2
GRID2
CXCL1
CXCL2
CXCL3
GRSF1
GUCY1A3
GUCY1B3
GYPA
GYPB
GYPE
H2AFZ
HADH
HTT
HGFAC
UBE2K
HMGB2
HMX1
HNRNPD
HPGD
HSP90AA4P
HSP90AB3P
HTN1
HTN3
IBSP
IDUA
CFI
IGFBP7
IGJ
RBPJ
IL8
IL15
ING2
CXCL10
IRF2
KLKB1
LETM1
LRPAP1
MAD2L1
SMAD1
MANBA
MGST2
CXCL9
AFF1
NR3C2
MSX1
MTNR1A
MTTP
MUC7
MYL5
NDUFC1
NEK1
NFKB1
NKX6-1
NPY1R
NPY2R
NPY5R
PCDH7
PDE6B
PDHA2
PET112
PF4
PF4V1
PITX2
PKD2
PLRG1
EXOSC9
POLR2B
POU4F2
PPEF2
PPAT
PPBP
PPID
PPP2R2C
PPP3CA
PRKG2
MAPK10
PTPN13
QDPR
REST
RFC1
RGS12
RNF4
ABCE1
RPL9
RPL34
RPS3A
S100P
MSMO1
CXCL6
CXCL11
CXCL5
SFRP2
SGCB
SH3BP2
SNCA
SOD3
SPINK2
SPP1
SRP72
STATH
SULT1E1
TACR3
TDO2
TEC
TLL1
TLR1
TLR2
TLR3
TRPC3
TXK
UBE2D3
UCHL1
UCP1
UGDH
UGT2B4
UGT2B7
UGT2B10
UGT2B15
UGT2B17
UGT8
VEGFC
WFS1
WHSC2
ZNF141
SLBP
GLRA3
ACOX3
SPARCL1
SMARCA5
SORBS2
PRSS12
CPZ
NOP14
FAM193A
USO1
UNC5C
LAMTOR3
PDE5A
SLC4A4
SAP30
INPP4B
PROM1
HERC3
SNORD73A
STBD1
CDKL2
PAPSS1
LDB2
LRAT
AIMP1
NDST3
SLIT2
RAB28
TMPRSS11D
ABCG2
HAND2
ADAMTS3
CLOCK
CEP135
RAPGEF2
KIAA0232
MFAP3L
SEC24D
G3BP2
WDR1
HS3ST1
FGFBP1
HNRPDL
TSPAN5
ENAM
C4orf6
FAM13A
MFSD10
SPRY1
MAEA
TLR6
PCGF3
ANAPC10
ATP8A1
SPON2
PGRMC2
SEC24B
TACC3
SLC30A9
CXCL13
SLC34A2
MAB21L2
PAICS
MXD4
PDLIM5
RRH
CORIN
UGT2B11
PLK4
PTTG2
CPLX1
HPSE
SLC26A1
NMU
SMR3B
NPFFR2
PPARGC1A
PPBPL2
UGT2A1
CCNI
LIAS
ADAM29
PRDM5
LSM6
NUDT6
ANXA10
KLHL2
SCRG1
HSPA4L
SEC31A
RUFY3
MMRN1
LIMCH1
WDFY3
PALLD
DCUN1D4
TBC1D9
METAP1
TBC1D1
SEL1L3
KIAA0922
PDS5A
LPHN3
TRIM2
MAN2B2
ANP32C
SLC7A11
CCRN4L
PARM1
FAM149A
RCHY1
ANKRD17
STAP1
FBXL5
FBXO8
DUX2
SMR3A
D4S234E
PPA2
DAPP1
DKK2
FAM184B
INTU
NAAA
GPR78
COQ2
ARFIP1
SULT1B1
PDLIM3
HPGDS
ZNF330
TMPRSS11E
ZCCHC4
ANAPC4
SPOCK3
MRPS18C
LAP3
KLHL5
SEPSECS
COPS4
AADAT
HSD17B11
LEF1
HERC5
KLF3
FAM198B
PLAC8
LARP7
EMCN
MYOZ2
ACCN5
GALNT7
NUDT9
NUP54
STX18
FGFRL1
CLDN22
CYTL1
GAR1
SH3TC1
UGT2B28
RBM47
PCDH18
USP53
DKFZP434I0714
OTUD4
DCHS2
ARHGEF38
PIGG
DCAF16
OCIAD1
COMMD8
ODAM
C4orf27
HERC6
CCDC109B
MARCH1
BANK1
LARP1B
SDAD1
TMEM33
LGI2
BBS7
UBA6
NEIL3
PGM2
C4orf19
TBC1D19
PI4K2B
TMEM144
C4orf43
UFSP2
CNO
C4orf21
STK32B
AP1AR
MAML3
CHRNA9
BMP2K
DDX60
CDKN2AIP
LYAR
ODZ3
N4BP2
TMEM184C
SEPT11
EXOC1
LRP2BP
TMEM165
PDGFC
SLC2A9
FSTL5
BDH2
SMARCAD1
MEPE
STOX2
PRDM8
UTP3
INTS12
ANKRD50
ATP10D
DANCR
KIAA1211
RNF150
KIAA1239
TBC1D14
SORCS2
CC2D2A
KLHL8
PCDH10
KIAA1430
FNIP2
SLAIN2
SHROOM3
STIM2
SH3RF1
KIAA1530
METTL14
WDR19
ZFYVE28
GBA3
ENOPH1
PROL1
OSTC
IL21
RXFP1
AFAP1
GUF1
SPCS3
SCOC
TRAPPC11
NEUROG2
SLC39A8
NCAPG
HHIP
NDST4
AGXT2L1
USP46
MRPL1
RASL11B
ELOVL6
TNIP2
HAUS3
NDNF
FAT4
ARSJ
SRD5A3
ARHGAP10
FLJ13197
MLF1IP
THAP9
NSUN7
UGT2A3
NBLA00301
GSTCD
MAP9
TNIP3
PHF17
ABCA11P
SCD5
DNAJB14
TMEM156
WWC2
FRAS1
NAA15
CWH43
C4orf29
ALPK1
GRPEL1
MED28
CXXC4
KCNIP4
CEP44
SETD7
PLA2G12A
TLR10
SLC25A31
RAB33B
ARHGAP24
FGFBP2
SNX25
TTC29
MND1
SLC10A7
TKTL2
C4orf17
QRFPR
FAM175A
KIAA1109
MFSD7
NOA1
TMEM175
ABLIM2
HOPX
COL25A1
USP38
LNX1
C4orf49
AFAP1-AS1
NAA11
AGPAT9
CBR4
PIGY
TMEM128
CABS1
ZNF518B
FHDC1
FLJ20021
MGC45800
PRMT10
CCDC149
DDX60L
YTHDC1
C4orf42
TMEM129
NAF1
MOB1B
TIFA
FAM114A1
RG9MTD2
MRFAP1
LOC93622
TADA2B
TBCK
HTRA3
HELQ
CYP2U1
C1QTNF7
MRFAP1L1
DDIT4L
CLNK
WDR17
ARAP2
GDEP
ANTXR2
OCIAD2
SCLT1
C4orf33
TMEM155
PABPC4L
ADAD1
ZFP42
LIN54
SPATA18
C4orf32
TMPRSS11B
GNPDA2
SPATA4
CPEB2
EVC2
ARL9
AASDH
PDCL2
C4orf36
PACRGL
TRAM1L1
OTOP1
ENPP6
SLC9B2
ASB5
SLC9B1
ZNF827
SH3D19
NFXL1
NIPAL1
PAQR3
SHISA3
LOC152578
SCFD2
C4orf38
ZNF595
LOC152742
C4orf39
JAKMIP1
THAP6
C4orf26
KLB
FAM53A
PPM1K
C4orf45
METTL19
RASGEF1B
SPATA5
BBS12
DCLK2
GPR125
TRIM60
FREM3
MMAA
ZBTB49
TIGD2
RASSF6
RBM46
SGMS2
COX7B2
GSX2
ZNF721
SYNPO2
C4orf46
SLC10A4
TIGD4
TMEM154
C4orf34
TMEM192
RWDD4
CCDC111
TAPT1
FLJ39653
TRIML2
CNOT6L
TECRL
LCORL
C4orf22
LOC255130
EPGN
ZNF718
ELMOD2
NPNT
CCDC110
MFSD8
LOC256880
CCDC96
BOD1L
FDCSP
NAP1L5
LOC285419
DCAF4L1
CYP4V2
LOC285441
LOC285456
CRIPAK
LOC285484
DOK7
FLJ35424
RNF212
LOC285501
FAM13A-AS1
GPRIN3
COX18
YIPF7
FRYL
RNF175
LOC285540
LOC285547
LOC285548
FAM200B
C4orf37
CSN1S2AP
C4orf10
ZAR1
CCDC158
TMPRSS11A
LOC339975
TRIML1
LRRC66
NAT8L
LOC340017
LOC344967
PRSS48
SOWAHB
LRIT3
C4orf44
SLC10A6
HSD17B13
FAM86EP
ANKRD37
POLN
PCNAP1
KCNIP4-IT1
KCTD8
C4orf52
BEND4
GRXCR1
TMPRSS11F
LOC389247
USP17L6P
USP17
HSP90AB2P
TRIM61
HELT
C4orf48
DTHD1
LOC401127
LOC401134
SYT14L
TMPRSS11BNL
C4orf40
AMTN
FAM190A
FLJ14186
C4orf3
LOC401164
LOC402160
RPL21P44
FAM92A3
WDFY3-AS2
MIR218-1
MIR302A
C4orf11
LOC441009
MTHFD2L
LOC441025
TMEM150C
GUSBP5
HSP90AA6P
C4orf47
DUX4L4
GALNTL6
MIR302B
MIR302C
MIR302D
MIR367
FRG2
CISD2
LOC550112
LOC550113
UGT2A2
LOC641364
LOC641365
LOC641518
ZNF876P
SLED1
LOC644145
LOC644248
DEFB131
TMPRSS11GP
CLRN2
CEP170P1
LOC645513
LOC646576
C4orf51
LOC650293
FLJ38576
DUX4L6
DUX4L5
DUX4L3
ZNF732
SCARNA22
SNORA24
SNORA26
MIR572
MIR573
MIR574
MIR575
MIR577
MIR578
LINC00290
LOC728175
LOC728369
LOC728373
LOC728379
USP17L5
LOC728393
LOC728400
LOC728405
DUX4L2
CETN4P
FAM160A1
FLJ36777
LOC731424
RELL1
PSAPL1
SNHG8
MIR943
FAM47E
LOC100129858
LOC100129917
LOC100129931
FTLP10
LOC100130872
CLDN24
LOC100133461
LOC100144602
PP12613
LOC100288255
ERVMER34-1
MIR1243
MIR2054
MIR1305
MIR548I2
MIR1973
CSN1S2BP
TMED11P
MIR4274
MIR3140
MIR4275
MIR3138
MIR4276
LOC100499177
MIR3945
MIR3684
MIR3688-1
LOC100505545
LOC100505702
LOC100505875
SLIT2-IT1
LOC100505912
LOC100505989
LOC100506013
LOC100506035
LOC100506085
LOC100506122
LOC100506229
LOC100506462
LOC100506564
LOC100506746
LOC100507053
LOC100507096
LOC100507266
1/2-SBSRNA4
MIR4453
MIR378D1
MIR4799
MIR548AJ2
MIR4802
MIR4450
MIR3688-2
MIR4451
MIR4800
MIR4801
MIR4449
MIR4798
FAM47E-STBD1
HTT-AS1

Genes in Wide Peak

This is the comprehensive list of deleted genes in the wide peak for 22q11.21.

Table S8. Genes in bold are cancer genes as defined by The Sanger Institute's Cancer Gene Census [7].

Genes
BCR
EP300
EWSR1
MN1
MYH9
NF2
PDGFB
SMARCB1
CLTCL1
CHEK2
MKL1
hsa-mir-3201
hsa-let-7b
hsa-mir-1249
hsa-mir-33a
hsa-mir-1281
hsa-mir-659
hsa-mir-3200
hsa-mir-3199-2
hsa-mir-548j
hsa-mir-650
hsa-mir-130b
hsa-mir-649
hsa-mir-1286
hsa-mir-1306
hsa-mir-185
hsa-mir-648
hsa-mir-3198
ACR
ACO2
ADORA2A
ADRBK2
ADSL
AP1B1
ARSA
ARVCF
ATF4
ATP6V1E1
BID
BIK
TSPO
MPPED1
CHKB
COMT
CPT1B
CRKL
CRYBA4
CRYBB1
CRYBB2
CRYBB2P1
CRYBB3
CSF2RB
CSNK1E
CYP2D7P1
CYP2D6
DDT
CYB5R3
TYMP
FBLN1
XRCC6
GGT1
GGT3P
GGT5
GNAZ
GP1BB
MCHR1
GSC2
GSTT1
GSTT2
H1F0
SERPIND1
HMOX1
IGLL1
IL2RB
KCNJ4
LGALS1
LGALS2
LIF
LIMK2
MB
MCM5
MFNG
MGAT3
MIF
MMP11
MPST
NAGA
NCF4
NDUFA6
DRG1
NEFH
NHP2L1
OSM
PI4KA
PMM1
SEPT5
POLR2F
PPARA
MAPK1
MAPK11
PRODH
PVALB
RAC2
RANBP1
RANGAP1
RFPL1
RPL3
MAPK12
SBF1
SLC5A1
SMTN
SLC5A4
SLC7A4
SLC25A1
SNRPD3
SOX10
SREBF2
SSTR3
ST13
TBX1
TCF20
TCN2
TEF
TIMP3
CLDN5
TOP1P2
TST
HIRA
UBE2L3
UFD1L
UPK3A
VPREB1
WNT7B
XBP1
YWHAH
ZNF70
ZNF74
DGCR6
LZTR1
DGCR14
SYN3
CDC45
PLA2G6
TPST2
GALR3
NIPSNAP1
APOL1
THOC5
EIF3D
MTMR3
CACNA1I
TOP3B
P2RX6
SYNGR1
LARGE
SNAP29
GRAP2
PICK1
GAL3ST1
GTPBP1
APOBEC3B
RAB36
CELSR1
PPM1F
DEPDC5
PPP6R2
SFI1
ZBED4
JOSD1
RBX1
DGCR2
SCO2
HMGXB4
TOM1
DNAL4
SF3A1
PKDREJ
CACNG2
TAB1
SLC25A17
DDX17
TXNRD2
RASL10A
GAS2L1
RFPL3-AS1
RFPL3
RFPL2
RFPL1-AS1
NUP50
TOB2
KDELR3
IFT27
TRIOBP
CDC42EP1
DMC1
RABL2B
PACSIN2
USP18
MORC2
TNRC6B
HIC2
GRAMD4
TTLL12
MLC1
ZC3H7B
KIAA0930
TTC28
SPECC1L
GCAT
CBX6
NPTXR
PES1
CBX7
CABIN1
PRAME
SLC16A8
SEC14L2
MAPK8IP2
RBFOX2
SEZ6L
RASD2
PATZ1
SH3BP1
TSSK2
PLXNB2
SDF2L1
PPIL2
PITPNB
PISD
OSBP2
MAFF
IL17RA
BRD1
ARHGAP8
APOL2
AP1B1P1
ANKRD62P1-PARP4P3
POTEH
BCL2L13
TFIP11
C22orf31
TBC1D22A
GSTTP1
C22orf24
CBY1
SUN2
DGCR11
DGCR9
FBXO7
RHBDD3
TTLL1
POM121L1P
SAMM50
ATXN10
FAM19A5
TXN2
TMEM184B
SULT4A1
GGA1
RIBC2
DGCR5
DGCR10
FBXW4P1
ARFGAP3
SNORD43
TRMT2A
INPP5J
SMC1B
CYTH4
RTDR1
CSDC2
RRP7A
MCAT
APOBEC3C
PPPDE2
SGSM3
HSFY1P1
CECR6
CECR5
CECR3
CECR2
POM121L9P
CARD10
PARVB
NCAPH2
UQCR10
POM121L8P
YPEL1
ZDHHC8
VPREB3
PLA2G3
C22orf43
EIF3L
C22orf28
GTSE1
MTFP1
MED15
UPB1
TUBA8
CECR1
A4GALT
MOV10L1
SMCR7L
DGCR8
GNB1L
TUG1
FAM118A
TTC38
C22orf26
MIOX
PRR5
PEX26
TRMU
ZMAT5
SEPT3
SUSD2
EIF4ENIF1
PANX2
TOMM22
PDXP
ASPHD2
MICAL3
APOBEC3G
XPNPEP3
PARVG
CERK
EFCAB6
MRPL40
RTN4R
SLC2A11
CENPM
ALG12
NOL12
CRELD2
C22orf46
C22orf29
KCTD17
CCDC134
ADM2
FOXRED2
BAIAP2L2
SCUBE1
TRABD
PNPLA3
THAP7
APOL6
APOL5
APOL4
APOL3
OR11H1
C22orf13
SELO
SLC25A18
L3MBTL2
TBC1D10A
HDAC10
KREMEN1
ZNRF3
ASCC2
TMEM191A
LDOC1L
POLDIP3
C22orf23
MYO18B
PHF5A
KLHL22
KIAA1644
SHANK3
DGCR6L
KIAA1656
RIMBP3
MICALL1
TUBGCP6
KIAA1671
HPS4
LOC90834
SCARF2
GGTLC2
LMF2
GUSBP11
DERL3
IGLL3P
LRP5L
RNF185
ISX
RPS19BP1
C22orf32
RRP7B
SERHL
LOC96610
PHF21B
MGC16703
KLHDC7B
PIK3IP1
FAM83F
ELFN2
C1QTNF6
TNFRSF13C
RNU86
SNORD83A
SNORD83B
GAB4
C22orf39
C22orf25
ZNF280A
SGSM1
EMID1
ANKRD54
APOBEC3D
SELM
ZNF280B
CCT8L2
XKR3
LOC150185
LOC150197
AIFM3
RIMBP3C
YDJC
ZDHHC8P1
C22orf15
HSCB
CCDC117
HORMAD2
DUSP18
MORC2-AS1
C22orf42
ENTHD1
DNAJB7
CHADL
MEI1
FAM109B
NFAM1
PNPLA5
LOC150381
C22orf40
CN5H6.4
CCDC116
CABP7
TMPRSS6
APOBEC3H
WBP2NL
POLR3H
RNF215
APOBEC3A
APOBEC3F
PRR14L
SERHL2
BPIFC
TMEM211
SEC14L3
POM121L4P
RGL4
RNU12
ATP5L2
LOC284865
LOC284889
TTC28-AS1
SEC14L4
LOC284933
RPL23AP82
SLC35E4
LOC339666
C22orf33
BK250D10.8
LOC339685
C22orf34
PI4KAP2
SDC4P
CHKB-CPT1B
TPTEP1
LOC388849
FAM211B
LOC388906
LINC00207
LOC391322
LOC400891
BCRP2
CHCHD10
LOC400927
MIRLET7BHG
FLJ46257
IL17REL
SRRD
MIRLET7A3
MIRLET7B
MIR130B
MIR185
MIR33A
LINC00229
FAM116B
PIM3
THAP7-AS1
P2RX6P
RIMBP3B
PIWIL3
MIAT
SHISA8
ODF3B
CCDC157
PRR5-ARHGAP8
BCRP3
SYCE3
TMEM191C
C22orf45
POM121L10P
LOC646851
LOC648691
CES5AP1
GATSL3
GSTTP2
GSTT2B
MIR648
MIR650
MIR658
MIR659
TMEM191B
PI4KAP1
LOC729444
SEC14L6
LOC730668
DDTL
SNORD125
MIR301B
LOC100128531
LOC100128946
CECR7
CECR5-AS1
LOC100130899
LOC100132273
LOC100144603
FLJ41941
LOC100271722
MIR1286
MIR1249
MIR1306
MIR1281
MIR548J
MIR3200
MIR3201
MIR3199-2
MIR3198-1
MIR3199-1
IGLL5
MIR3909
MIR3619
MIR3653
MIR3618
MIR3928
LOC100506195
LOC100506241
LOC100506472
LOC100506714
SEPT5-GP1BB
MIR4763
MIR4534
MIR4762
MIR4766
MIR4764
MIR4761
MIR4535

Arm-level results

Table 2. Get Full Table Arm-level significance table - 10 significant results found. The significance cutoff is at Q value=0.25.

Arm | # Genes | Amp Frequency | Amp Z score | Amp Q value | Del Frequency | Del Z score | Del Q value
--- | --- | --- | --- | --- | --- | --- | ---
1p | 2121 | 0.00 | -1.19 | 0.891 | 0.03 | 0.475 | 0.776
1q | 1955 | 0.00 | -1.2 | 0.891 | 0.03 | 0.466 | 0.776
2p | 924 | 0.00 | -1.21 | 0.891 | 0.04 | 1.24 | 0.617
2q | 1556 | 0.00 | -1.2 | 0.891 | 0.04 | 1.28 | 0.617
3p | 1062 | 0.00 | -1.22 | 0.891 | 0.03 | 0.42 | 0.776
3q | 1139 | 0.00 | -1.21 | 0.891 | 0.04 | 1.25 | 0.617
4p | 489 | 0.03 | 0.41 | 0.76 | 0.01 | -0.4 | 0.89
4q | 1049 | 0.03 | 0.439 | 0.76 | 0.01 | -0.38 | 0.89
5p | 270 | 0.05 | 2.01 | 0.111 | 0.00 | -1.22 | 0.89
5q | 1427 | 0.05 | 2.1 | 0.111 | 0.00 | -1.19 | 0.89
6p | 1173 | 0.00 | -1.22 | 0.891 | 0.01 | -0.403 | 0.89
6q | 839 | 0.00 | -1.22 | 0.891 | 0.03 | 0.408 | 0.776
7p | 641 | 0.05 | 2.04 | 0.111 | 0.00 | -1.21 | 0.89
7q | 1277 | 0.07 | 2.92 | 0.0287 | 0.00 | -1.19 | 0.89
8p | 580 | 0.01 | -0.411 | 0.891 | 0.01 | -0.411 | 0.89
8q | 859 | 0.01 | -0.401 | 0.891 | 0.01 | -0.401 | 0.89
9p | 422 | 0.03 | 0.407 | 0.76 | 0.01 | -0.402 | 0.89
9q | 1113 | 0.03 | 0.442 | 0.76 | 0.01 | -0.377 | 0.89
10p | 409 | 0.00 | -1.23 | 0.891 | 0.03 | 0.387 | 0.776
10q | 1268 | 0.00 | -1.21 | 0.891 | 0.03 | 0.43 | 0.776
11p | 862 | 0.00 | -1.22 | 0.891 | 0.03 | 0.41 | 0.776
11q | 1515 | 0.00 | -1.2 | 0.891 | 0.04 | 1.28 | 0.617
12p | 575 | 0.07 | 2.86 | 0.0287 | 0.00 | -1.2 | 0.89
12q | 1447 | 0.07 | 2.94 | 0.0287 | 0.00 | -1.18 | 0.89
13q | 654 | 0.01 | -0.351 | 0.891 | 0.07 | 2.9 | 0.0375
14q | 1341 | 0.04 | 1.26 | 0.353 | 0.00 | -1.2 | 0.89
15q | 1355 | 0.00 | -1.21 | 0.891 | 0.03 | 0.435 | 0.776
16p | 872 | 0.04 | 1.23 | 0.353 | 0.00 | -1.21 | 0.89
16q | 702 | 0.04 | 1.22 | 0.353 | 0.00 | -1.22 | 0.89
17p | 683 | 0.05 | 2.1 | 0.111 | 0.03 | 0.48 | 0.776
17q | 1592 | 0.05 | 2.12 | 0.111 | 0.00 | -1.19 | 0.89
18p | 143 | 0.01 | -0.426 | 0.891 | 0.01 | -0.426 | 0.89
18q | 446 | 0.01 | -0.416 | 0.891 | 0.01 | -0.416 | 0.89
19p | 995 | 0.01 | -0.382 | 0.891 | 0.03 | 0.436 | 0.776
19q | 1709 | 0.01 | -0.369 | 0.891 | 0.01 | -0.369 | 0.89
20p | 355 | 0.04 | 1.2 | 0.353 | 0.00 | -1.22 | 0.89
20q | 753 | 0.04 | 1.23 | 0.353 | 0.00 | -1.22 | 0.89
21q | 509 | 0.00 | -1.23 | 0.891 | 0.03 | 0.392 | 0.776
22q | 921 | 0.00 | -1.05 | 0.891 | 0.28 | 16.1 | 0
Xq | 1312 | 0.03 | 0.492 | 0.76 | 0.04 | 1.31 | 0.617

Methods & Data
Input
Description

- Segmentation File: The segmentation file contains the segmented data for all the samples identified by GLAD, CBS, or some other segmentation algorithm. (See GLAD file format in the Genepattern file formats documentation.) It is a six column, tab-delimited file with an optional first line identifying the columns. Positions are in base pair units.The column headers are: (1) Sample (sample name), (2) Chromosome (chromosome number), (3) Start Position (segment start position, in bases), (4) End Position (segment end position, in bases), (5) Num markers (number of markers in segment), (6) Seg.CN (log2() -1 of copy number).

- Markers File: The markers file identifies the marker names and positions of the markers in the original dataset (before segmentation). It is a three column, tab-delimited file with an optional header. The column headers are: (1) Marker Name, (2) Chromosome, (3) Marker Position (in bases).

- Reference Genome: The reference genome file contains information about the location of genes and cytobands on a given build of the genome. Reference genome files are created in Matlab and are not viewable with a text editor.

- CNV Files: There are two options for the cnv file. The first option allows CNVs to be identified by marker name. The second option allows the CNVs to be identified by genomic location. Option #1: A two column, tab-delimited file with an optional header row. The marker names given in this file must match the marker names given in the markers file. The CNV identifiers are for user use and can be arbitrary. The column headers are: (1) Marker Name, (2) CNV Identifier. Option #2: A 6 column, tab-delimited file with an optional header row. The 'CNV Identifier' is for user use and can be arbitrary. 'Narrow Region Start' and 'Narrow Region End' are also not used. The column headers are: (1) CNV Identifier, (2) Chromosome, (3) Narrow Region Start, (4) Narrow Region End, (5) Wide Region Start, (6) Wide Region End

- Amplification Threshold: Threshold for copy number amplifications. Regions with a log2 ratio above this value are considered amplified.

- Deletion Threshold: Threshold for copy number deletions. Regions with a log2 ratio below the negative of this value are considered deletions.

- Cap Values: Minimum and maximum cap values on analyzed data. Regions with a log2 ratio greater than the cap are set to the cap value; regions with a log2 ratio less than -cap value are set to -cap. Values must be positive.

- Broad Length Cutoff: Threshold used to distinguish broad from focal events, given in units of fraction of chromosome arm.

- Remove X-Chromosome: Flag indicating whether to remove data from the X-chromosome before analysis. Allowed values= {1,0} (1: Remove X-Chromosome, 0: Do not remove X-Chromosome.

- Confidence Level: Confidence level used to calculate the region containing a driver.

- Join Segment Size: Smallest number of markers to allow in segments from the segmented data. Segments that contain fewer than this number of markers are joined to the neighboring segment that is closest in copy number.

- Arm Level Peel Off: Flag set to enable arm-level peel-off of events during peak definition. The arm-level peel-off enhancement to the arbitrated peel-off method assigns all events in the same chromosome arm of the same sample to a single peak. It is useful when peaks are split by noise or chromothripsis. Allowed values= {1,0} (1: Use arm level peel off, 0: Use normal arbitrated peel-off).

- Maximum Sample Segments: Maximum number of segments allowed for a sample in the input data. Samples with more segments than this threshold are excluded from the analysis.

Values

List of inputs used for this run of GISTIC2. All files listed should be included in the archived results.

- Segmentation File = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_MergeDataFilesPipeline/THCA-follicular/2851108/2.GDAC_MergeDataFiles.Finished/THCA-follicular.snp__genome_wide_snp_6__broad_mit_edu__Level_3__segmented_scna_minus_germline_cnv_hg19__seg.seg.txt

- Markers File = /xchip/cga/reference/gistic2/genome.info.6.0_hg19.na31_minus_frequent_nan_probes_sorted_2.1.txt

- Reference Genome = /xchip/cga/reference/gistic2/hg19_with_miR_20120227.mat

- CNV Files = /xchip/cga/reference/gistic2/CNV.hg19.bypos.111213.txt

- Amplification Threshold = 0.1

- Deletion Threshold = 0.1

- Cap Values = 1.5

- Broad Length Cutoff = 0.7

- Remove X-Chromosome = 0

- Confidence Level = 0.99

- Join Segment Size = 4

- Arm Level Peel Off = 1

- Maximum Sample Segments = 2000

Table 3. Get Full Table First 10 out of 75 Input Tumor Samples.

Tumor Sample Names
TCGA-BJ-A0YZ-01A-11D-A10T-01
TCGA-BJ-A0Z0-01A-11D-A10T-01
TCGA-BJ-A0Z2-01A-11D-A10T-01
TCGA-BJ-A0Z3-01A-11D-A13V-01
TCGA-BJ-A0ZA-01A-11D-A10T-01
TCGA-BJ-A0ZC-01A-12D-A13V-01
TCGA-BJ-A0ZE-01A-11D-A10T-01
TCGA-BJ-A0ZG-01A-11D-A10T-01
TCGA-BJ-A0ZJ-01A-11D-A10T-01
TCGA-BJ-A18Y-01A-11D-A13V-01

Figure 3. Segmented copy number profiles in the input data

Output
All Lesions File (all_lesions.conf_##.txt, where ## is the confidence level)

The all lesions file summarizes the results from the GISTIC run. It contains data about the significant regions of amplification and deletion as well as which samples are amplified or deleted in each of these regions. The identified regions are listed down the first column, and the samples are listed across the first row, starting in column 10.

Region Data

Columns 1-9 present the data about the significant regions as follows:

1. Unique Name: A name assigned to identify the region.

2. Descriptor: The genomic descriptor of that region.

3. Wide Peak Limits: The 'wide peak' boundaries most likely to contain the targeted genes. These are listed in genomic coordinates and marker (or probe) indices.

4. Peak Limits: The boundaries of the region of maximal amplification or deletion.

5. Region Limits: The boundaries of the entire significant region of amplification or deletion.

6. Q values: The Q value of the peak region.

7. Residual Q values: The Q value of the peak region after removing ('peeling off') amplifications or deletions that overlap other, more significant peak regions in the same chromosome.

8. Broad or Focal: Identifies whether the region reaches significance due primarily to broad events (called 'broad'), focal events (called 'focal'), or independently significant broad and focal events (called 'both').

9. Amplitude Threshold: Key giving the meaning of values in the subsequent columns associated with each sample.

Sample Data

Each of the analyzed samples is represented in one of the columns following the lesion data (columns 10 through end). The data contained in these columns varies slightly by section of the file. The first section can be identified by the key given in column 9 - it starts in row 2 and continues until the row that reads 'Actual Copy Change Given.' This section contains summarized data for each sample. A '0' indicates that the copy number of the sample was not amplified or deleted beyond the threshold amount in that peak region. A '1' indicates that the sample had low-level copy number aberrations (exceeding the low threshold indicated in column 9), and a '2' indicates that the sample had high-level copy number aberrations (exceeding the high threshold indicated in column 9).The second section can be identified the rows in which column 9 reads 'Actual Copy Change Given.' The second section exactly reproduces the first section, except that here the actual changes in copy number are provided rather than zeroes, ones, and twos.The final section is similar to the first section, except that here only broad events are included. A 1 in the samples columns (columns 10+) indicates that the median copy number of the sample across the entire significant region exceeded the threshold given in column 9. That is, it indicates whether the sample had a geographically extended event, rather than a focal amplification or deletion covering little more than the peak region.

Amplification Genes File (amp_genes.conf_##.txt, where ## is the confidence level)

The amp genes file contains one column for each amplification peak identified in the GISTIC analysis. The first four rows are:

1. Cytoband

2. Q value

3. Residual Q value

4. Wide Peak Boundaries

These rows identify the lesion in the same way as the all lesions file.The remaining rows list the genes contained in each wide peak. For peaks that contain no genes, the nearest gene is listed in brackets.

Deletion Genes File (del_genes.conf_##.txt, where ## is the confidence level)

The del genes file contains one column for each deletion peak identified in the GISTIC analysis. The file format for the del genes file is identical to the format for the amp genes file.

Gistic Scores File (scores.gistic)

The scores file lists the Q values [presented as -log10(q)], G scores, average amplitudes among aberrant samples, and frequency of aberration, across the genome for both amplifications and deletions. The scores file is viewable with the Genepattern SNPViewer module and may be imported into the Integrated Genomics Viewer (IGV).

Segmented Copy Number (raw_copy_number.{fig|pdf|png} )

The segmented copy number is a pdf file containing a colormap image of the segmented copy number profiles in the input data.

Amplification Score GISTIC plot (amp_qplot.{fig|pdf|png|v2.pdf})

The amplification pdf is a plot of the G scores (top) and Q values (bottom) with respect to amplifications for all markers over the entire region analyzed.

Deletion Score GISTIC plot (del_qplot.{fig|pdf|png|v2.pdf})

The deletion pdf is a plot of the G scores (top) and Q values (bottom) with respect to deletions for all markers over the entire region analyzed.

Tables (table_{amp|del}.conf_##.txt, where ## is the confidence level)

Tables of basic information about the genomic regions (peaks) that GISTIC determined to be significantly amplified or deleted. These describe three kinds of peak boundaries, and list the genes contained in two of them. The region start and region end columns (along with the chromosome column) delimit the entire area containing the peak that is above the significance level. The region may be the same for multiple peaks. The peak start and end delimit the maximum value of the peak. The extended peak is the peak determined by robust, and is contained within the wide peak reported in {amp|del}_genes.txt by one marker.

Broad Significance Results (broad_significance_results.txt)

A table of per-arm statistical results for the data set. Each arm is a row in the table. The first column specifies the arm and the second column counts the number of genes known to be on the arm. For both amplification and deletion, the table has columns for the frequency of amplification or deletion of the arm, and a Z score and Q value.

Broad Values By Arm (broad_values_by_arm.txt)

A table of chromosome arm amplification levels for each sample. Each row is a chromosome arm, and each column a sample. The data are in units of absolute copy number -2.

All Data By Genes (all_data_by_genes.txt)

A gene-level table of copy number values for all samples. Each row is the data for a gene. The first three columns name the gene, its NIH locus ID, and its cytoband - the remaining columns are the samples. The copy number values in the table are in units of (copy number -2), so that no amplification or deletion is 0, genes with amplifications have positive values, and genes with deletions are negative values. The data are converted from marker level to gene level using the extreme method: a gene is assigned the greatest amplification or the least deletion value among the markers it covers.

Broad Data By Genes (broad_data_by_genes.txt)

A gene-level table of copy number data similar to the all_data_by_genes.txt output, but using only broad events with lengths greater than the broad length cutoff. The structure of the file and the methods and units used for the data analysis are otherwise identical to all_data_by_genes.txt.

Focal Data By Genes (focal_data_by_genes.txt)

A gene-level table of copy number data similar to the all_data_by_genes.txt output, but using only focal events with lengths greater than the focal length cutoff. The structure of the file and the methods and units used for the data analysis are otherwise identical to all_data_by_genes.txt.

All Thresholded By Genes (all_thresholded.by_genes.txt)

A gene-level table of discrete amplification and deletion indicators at for all samples. There is a row for each gene. The first three columns name the gene, its NIH locus ID, and its cytoband - the remaining columns are the samples. A table value of 0 means no amplification or deletion above the threshold. Amplifications are positive numbers: 1 means amplification above the amplification threshold; 2 means amplifications larger to the arm level amplifications observed for the sample. Deletions are represented by negative table values: -1 represents deletion beyond the threshold; -2 means deletions greater than the minimum arm-level deletion observed for the sample.

Sample Cutoffs (sample_cutoffs.txt)

A table of the per-sample threshold cutoffs (in units of absolute copy number -2) used to distinguish the high level amplifications (+/-2) from ordinary amplifications (+/-1) in the all_thresholded.by_genes.txt output file. The table contains three columns: the sample identifier followed by the low (deletion) and high (amplification) cutoff values. The cutoffs are calculated as the minimum arm-level amplification level less the deletion threshold for deletions and the maximum arm-level amplification plus the amplification threshold for amplifications.

Focal Input To Gistic (focal_input.seg.txt)

A list of copy number segments describing just the focal events present in the data. The segment amplification/deletion levels are in units of (copy number -2), with amplifications positive and deletions negative numbers. This file may be viewed with IGV.

Gene Counts vs. Copy Number Alteration Frequency (freqarms_vs_ngenes.{fig|pdf})

An image showing the correlation between gene counts and frequency of copy number alterations.

Confidence Intervals (regions_track.conf_##.bed, where ## is the confidence level)

A file indicating the position of the confidence intervals around GISTIC peaks that can be loaded as a track in a compatible viewer browser such as IGV or the UCSC genome browser.

GISTIC

GISTIC identifies genomic regions that are significantly gained or lost across a set of tumors. It takes segmented copy number ratios as input, separates arm-level events from focal events, and then performs two tests: (i) identifies significantly amplified/deleted chromosome arms; and (ii) identifies regions that are significantly focally amplified or deleted. For the focal analysis, the significance levels (Q values) are calculated by comparing the observed gains/losses at each locus to those obtained by randomly permuting the events along the genome to reflect the null hypothesis that they are all 'passengers' and could have occurred anywhere. The locus-specific significance levels are then corrected for multiple hypothesis testing. The arm-level significance is calculated by comparing the frequency of gains/losses of each arm to the expected rate given its size. The method outputs genomic views of significantly amplified and deleted regions, as well as a table of genes with gain or loss scores. A more in depth discussion of the GISTIC algorithm and its utility is given in [1], [3], and [5].

CNV Description

Regions of the genome that are prone to germ line variations in copy number are excluded from the GISTIC analysis using a list of germ line copy number variations (CNVs). A CNV is a DNA sequence that may be found at different copy numbers in the germ line of two different individuals. Such germ line variations can confound a GISTIC analysis, which finds significant somatic copy number variations in cancer. A more in depth discussion is provided in [6]. GISTIC currently uses two CNV exclusion lists. One is based on the literature describing copy number variation, and a second one comes from an analysis of significant variations among the blood normals in the TCGA data set.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Beroukhim et al, Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma, Proc Natl Acad Sci U S A. Vol. 104:50 (2007)
[2] GISTIC version 1
[3] Mermel et al, GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers, Genome Biology Vol. 12:4 (2011)
[4] GISTIC version 2
[5] Beroukhim et al., The landscape of somatic copy-number alteration across human cancers, Nature Vol. 463:7283 (2010)
[6] McCarroll, S. A. et al., Integrated detection and population-genetic analysis of SNPs and copy number variation, Nat Genet Vol. 40(10):1166-1174 (2008)
[7] The Sanger Institute: Cancer Gene Census
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