GSEA Report for Dataset input

Enrichment in phenotype: EAT (28 samples)

• 2222 / 4322 gene sets are upregulated in phenotype EAT
• 507 gene sets are significant at FDR < 25%
• 432 gene sets are significantly enriched at nominal pvalue < 1%
• 611 gene sets are significantly enriched at nominal pvalue < 5%
• Snapshot of enrichment results
• Detailed enrichment results in html format
• Detailed enrichment results in excel format (tab delimited text)
• Guide to interpret results

Enrichment in phenotype: SAT (27 samples)

• 2100 / 4322 gene sets are upregulated in phenotype SAT
• 96 gene sets are significantly enriched at FDR < 25%
• 223 gene sets are significantly enriched at nominal pvalue < 1%
• 343 gene sets are significantly enriched at nominal pvalue < 5%
• Snapshot of enrichment results
• Detailed enrichment results in html format
• Detailed enrichment results in excel format (tab delimited text)
• Guide to interpret results

Dataset details

• The dataset has 14324 features (genes)
• No probe set => gene symbol collapsing was requested, so all 14324 features were used

Gene set details

• Gene set size filters (min=15, max=500) resulted in filtering out 1595 / 5917 gene sets
• The remaining 4322 gene sets were used in the analysis
• List of gene sets used and their sizes (restricted to features in the specified dataset)

Gene markers for the EAT versus SAT comparison

• The dataset has 14324 features (genes)
• # of markers for phenotype EAT: 6116 (42.7% ) with correlation area 45.2%
• # of markers for phenotype SAT: 8208 (57.3% ) with correlation area 54.8%
• Detailed rank ordered gene list for all features in the dataset
• Heat map and gene list correlation profile for all features in the dataset

Global statistics and plots

• Plot of p-values vs. NES
• Global ES histogram

Other

• Parameters used for this analysis

Comments

• There were duplicate row identifiers in the specified dataset. One id was arbitarilly choosen. Details are below Generally, this is OK, but if you want to avoid this automagic, edit your dataset so that all row ids are unique # of row ids in original dataset: 14914 # of row UNIQUE ids in original dataset: 14324 # The duplicates were SLC25A37 FBXO9 ARID5A PPP2R3B ZNF277 TARP TTC6 C2 ERCC3 GK IDS KRT18 MICA NF1 PTEN TYR KRT17 KRT17 PECAM1 ATRX FCGR1A FCGR1A FCGR3A LTA LTA RPL9 AMY2A CACNA1C CHRNA7 DHFR DHFR DRD5 FKBP1A IGF1R NPR3 P4HB RPL5 RPL7 RPL12 RPL12 RPL13 RPL18A RPL21 RPL21 RPL23A RPL17 RPL24 RPL34 REEP3 TBC1D3B TBC1D3B TBC1D3B OR2W3 RPLP0 ANAPC11 FCGR2B KCTD11 SMAD2 RABL2B GTF2IRD2B OR2M7 OR4C46 OR4D10 OR4M2 OR2J3 OR2J3 DAZ4 OR8B3 OR4K15 OR4A47 SUMO2 SUMO2 RPS3A RPS3A RBMY1J RBMY1J RBMY1J RBMY1J LRRC37A2 LRRC37A2 LRRC37A2 CACYBP MOG PRAMEF4 PRAMEF4 B3GNTL1 RPS7 PCGF6 RPSA ROPN1B ANKRD20A3 ANKRD20A3 ANKRD20A3 LSP1 DDR2 FOLH1 BTBD11 HFM1 DKK3 FRMPD2 GOLGA8B RGPD1 RGPD1 RGPD1 RGPD1 RGPD1 HIST2H2BF HIST2H2BF SH3KBP1 CBWD5 CBWD5 CBWD5 RPS25 RPS26 RPS26 RPS26 RPS26 RPS27 RPS27 CPLX3 BOLA2 GLUL TOM1L2 RPL14 RPL41 RPL41 SDHC DYNLL1 NBPF9 NBPF9 NBPF9 MARVELD2 YIF1B NBPF10 LOC650293 LOC650293 ANXA8 ANXA8 BTNL8 ZXDC GAGE1 GAGE1 PTPN20 PTPN20 TPM3 UGT2B11 ZNF626 PGA3 PGA3 TMEM183B CASZ1 RASA4 RASA4 ZBTB38 SLC45A4 DYNC2H1 TSPAN11 KIR2DL4 PXN SPAG11A FAM86B1 FAM86B1 MORC4 MORC4 SFTPA1 ACR GPR89A POLR2J3 HLA-F HLA-F RAPGEF3 SFTPA2 ZBTB34 PTMA PTMA PTMA PTMA ALG13 PACS2 DGKZ CCHCR1 NBEAL1 SET CCR2 CFLAR AURKAIP1 VPS53 EEF1D ACAA1 FAM58A CDV3 ZDHHC3 RPS27A RPS27A AGER BTF3L4 SYT2 LRRFIP1 LRRFIP1 LRRFIP1 RGSL1 DAXX WEE1 DET1 ANKRD30B RASGRF1 SORBS2 BIVM NRG1 ZNF138 ARMC10 C6orf136 CSF2RA COL11A2 ANKRD36 PTCH2 SRGAP2 IQSEC3 IQSEC3 ABCC6 ARHGDIG SCN8A PIGT VDAC2 WNK1 DNAJC19 CLSPN UNKL DHRS4L2 DENND1B GABPA HLA-DQB2 SERINC2 AK2 RPL17 CNTNAP3B CNTNAP3B CNTNAP3B DDR1 ATP6V1G2 SRP19 ZNF587 RAB43 USMG5 LOC554223 HLA-DPA1 GFOD1 HLA-A TRIM26 HLA-C HLA-C FYB HIP1 GNG2 HDLBP HLA-DQB1 HLA-DQB1 HLA-DRB1 LCN1 RPL15 ANKRD11 MSTO1 RPL10 RNF165 DDX11 DDX11 CCDC74A PDPK1 CDSN FBXW10 RPS3A CTCFL RXRB RXRB WTAP HYDIN HYDIN HYDIN KIF27 KIF27 MEGF8 RAB13 AP1S2 GPSM3 SDHD IGSF9B AOC3 ALDH6A1 RAD17 ZNRD1 ABCB8 ABCB8 ABCB8 CSNK2B MAGEA2 CDRT1 TRA2A SERHL2 VKORC1L1 TPT1 CNOT6L CBWD5 CBWD5 CBWD5 D2HGDH DKC1 SDAD1 EFCAB2 KIR2DS2 KIR2DS2 KIR2DS2 TUBB TUBB DUX4 DUX4 DUX4 DUX4 DUX4 SDHA EEF1A1 EIF4B EIF4B GPR32 CKS1B EIF4A2 FGF7 FTH1 GAB1 GNA11 H3F3A H3F3A H3F3A HLA-DMB HLA-DOB HLA-DPB1 HLA-DPB1 HLA-DQA1 HLA-G HMGB1 HSPA6 KCNG1 MAFG MAFG MOG PBX2 PLCG2 POU5F1 PRSS2 PSMC6 RBMS1 RING1 RPS2 ST8SIA1 SNRPE SNRPG SRP9 SSRP1 TAPBP TAPBP TERF1 TPSAB1 TSPYL1 UBE2L3 HIST1H2AI HIST1H4K DOC2B DHX16 ADAM21 NRP2 GBP2 STK19 GCSH GCSH HERC2 HERC2 HERC2 CD8B HMGN1 KIF5A PRB1 GNG5 GNL1 GNL1 GRK5 RAPGEF1 PDIA3 HSPA1A HSPA1B RBPJ MAGEA3 TOM1L1 HLA-B HLA-E HMGN2 HMGN2 KRT6A RHEB MMP16 MT2A MT2A UQCRFS1 VARS ANP32A NPEPPS RAN TIMM23 RBM14 SEMA4D CDRT1 ARID3B AVIL MTHFD2 TCEA1 YWHAE TRIM10 IFNA13 RNF5 SLC5A3 TRIM31 TRIM31 TCF19 ZNF90 LYPLA2 LYPLA2 ACOT7 ELL2 ARL2BP FBXO25 RHOQ FBXO9 OR11A1 DEXI ARHGEF10 PLEKHM1 AAK1 FRYL TBC1D2B SMG1 SMG1 SMG1 SMG1 SMG1 BOP1 PRUNE2 MICAL3 SMCHD1 PSD3 AHCTF1 GPATCH4 C1QTNF5 PELO KLF13 FAHD2A RPL26L1 IER3IP1 SELT GLRX5 ZCCHC2 IMPAD1 MRPL20 RNF31 FAM90A1 PLCXD1 RRN3 RRN3 PXMP2 CLN8 FAM35A TNXB TNXB HLA-DRA PCNP CD177 CLK4 KIAA1328 MST1 MTMR3 TMSB4X TMSB4X TMSB4X PPIA LY6G5B GABBR1 PPP1R11 PGM5 PGM5 EIF4H TOR1AIP2 SUDS3 CSH2 ANAPC1 DGCR14 NUCKS1 HAPLN4 UGT2A3 FBXO17 C6orf25 C6orf25 LY6G5C SAA2 ITFG1 OR2J2 ISCA1 SCRT1 ING5 THOC3 PNMA6A ZNF479 CGB1 ZFHX2 TRERF1 RFT1 ADAMTSL1 RBM33 HIST1H2BK TREX2 ZNF618 KIAA2013 CYHR1 CDC26 TCP10L DNHD1 DNHD1 DNHD1 LSM14B LSM14B LSM12 ZNF75A KIR3DL3 KIR3DL3 DNAH17 DNAH17 FSIP2 ARHGAP27 TUBB8 LCN8 ZNF616 ZNF678 SLCO4C1 KRTAP10-4 PHLDB3 STMN1 ERICH1 DNAH10 RPL23AP7 RPL23AP7 TTTY14 OR7E37P OR7E37P OR7E37P OR7E37P OR7E37P OR7E37P OR7E37P MEIS3P1 WDR74 MALAT1 MGC72080 PMCHL1 FLJ25758 FAM99A KIAA0125 DBF4B LOC441081 LOC441081 FER1L4 ESR1 DUX4 CCNL2 UBQLN4 POLR2J VAC14 PPM1K CD99 PDPK1 EPHA10 PGM5 GPC2 TRIM74 VTI1A DNAJC9 PRAMEF4 HLA-A ALDH1A3 AQP7 AQP7 SLC6A8 RPL23AP7 LOC401357 CARD8
• Timestamp used as random seed: 1557974095973