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Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 17138 new columns ({'RP3-382I10.7', 'MIR3180-4', 'IL4I1', 'ARL14EP', 'CDX2', 'GNA11', 'PDDC1', 'BRD2', 'PIGN', 'KIF1C', 'LRRC41', 'RP11-336A10.4', 'RP11-727F15.14', 'GNA13', 'TNPO1', 'TANK', 'ZCCHC2', 'LDOC1', 'PGS1', 'LINGO1', 'CCNK', 'ENTPD6', 'HESX1', 'DOCK11', 'CWC25', 'GJC2', 'NNAT', 'NDUFA6', 'SEMA4A', 'C2CD3', 'RAPGEFL1', 'SHF', 'POLR2E', 'DHRS7', 'EFNA5', 'MBOAT7', 'TMEM88', 'GOLPH3', 'CHID1', 'PPP2R5E', 'CCNB1IP1', 'CH507-24F1.2', 'GLT1D1', 'CARD16', 'ACER1', 'HSPA6', 'HSCB', 'ZBTB7C', 'MAGEH1', 'SCARA3', 'RFX1', 'UAP1L1', 'TTC7A', 'STAT5B', 'RAN', 'PARP3', 'HPSE', 'ANAPC16', 'AC006116.20', 'STYX', 'CLEC2B', 'KLF4', 'HCG18', 'TNFAIP1', 'QSOX2', 'GALNT6', 'RP11-442H21.2', 'HOXD1', 'GABBR2', 'LINC01621', 'ELL', 'CD48', 'CCDC81', 'SAE1', 'HS3ST6', 'CCSER2', 'UBE2J2', 'FOXB1', 'GJA3', 'TRIM68', 'RING1', 'C8orf44', 'EFCAB2', 'APAF1', 'AIFM1', 'CCT4', 'KLHL31', 'RPL32', 'LY9', 'C5orf45', 'CA2', 'RP11-30J20.1', 'SPATC1L', 'DLX5', 'RP11-532F12.5', 'B4GALT1', 'SPRYD4', 'FYTTD1', 'HEATR5B', 'LINC00441', 'HIST1H2AE', 'PSMB7', 'WDR6', 'CUTC', 'ERCC2', 'C16orf86', 'FAM72A', 'CSPG5', 'MCU', 'FZD6', 'SYK', 'TPGS2', 'PPT1', 'NPPC', 'HIBADH', 'C1orf116', 'GCC1', 'ENO4', 'PCMT1', 'EXD3', 'RNF103', 'TDRD12', 'SYT15', 'GGTLC3', 'FAM228A', 'KLC2', 'FUT1', 'CBSL', 'NRROS', 'TMEM156', 'ZNF720', 'RAB14', 'COQ9', 'AC092580.4', 'SCOC', 'SRP72', 'PIAS2', 'CUTA', 'NBAS', 'BMX', 'SLFN5', 'TRAF2', 'YBX2', 'ASIC1', 'SASS6', 'PRELP', 'ERP27', 'FBXL22', 'FBXO39', 'LTK', 'PDE6D', 'NOSTRIN', 'SYCP2', 'ZNF333', 'CSF2', ' ... 7', 'NOP58', 'CKS1B', 'KDM7A', 'SOCS7', 'KATNAL2', 'RP11-66B24.2', 'CRACR2B', 'ABRACL', 'RPL31', 'TIMM10', 'CARMN', 'OR51E1', 'SPRYD3', 'GNB1L', 'NDC80', 'F2RL2', 'CDK20', 'PIK3C2B', 'HMG20A', 'CEACAM5', 'RAB32', 'METRNL', 'MYCBP2', 'INTS6-AS1', 'RGCC', 'IZUMO1', 'KEL', 'TM9SF1', 'PRR15', 'MMP25', 'PRR5', 'GLUD2', 'TMEM106A', 'VAMP1', 'DNAJC14', 'RNF122', 'NHSL1', 'RBCK1', 'EGLN1', 'CSRNP1', 'HSFX1', 'MED29', 'EPN3', 'MIEF1', 'GBA2', 'GZMM', 'NLRP2B', 'TIMM21', 'ATP11B', 'BBS2', 'PLPP7', 'PRKCQ', 'RP11-618L22.1', 'GSAP', 'STK38L', 'GS1-393G12.13', 'AC093388.3', 'B3GALT5', 'MEGF6', 'MUC15', 'CTD-2298J14.2', 'TRIM23', 'H2AFV', 'CA8', 'ATE1', 'FADD', 'BIN3', 'MPZ', 'MICAL2', 'FILIP1L', 'ZNF420', 'NME8', 'TPO', 'S100A12', 'TRIM37', 'AREG', 'WBSCR17', 'VSIG10L', 'ATG2B', 'MARCH9', 'PHEX', 'GTF2A2', 'RPS6KA5', 'IDI1', 'HSPA4', 'CDA', 'ASB12', 'STAU1', 'ZSCAN32', 'NDE1', 'C2CD2', 'ZNF83', 'INTS5', 'EMC7', 'DNAH2', 'EHD3', 'EMG1', 'TIPARP-AS1', 'VAMP7', 'CTC-260F20.3', 'MOSPD3', 'PELI2', 'FBXL17', 'UBR2', 'KCNN1', 'ANKRD54', 'PCGF3', 'ABR', 'ST3GAL1', 'CTB-12A17.3', 'ATP6AP2', 'RAB20', 'COX16', 'GTF2I', 'LMCD1', 'PANX1', 'ADAMDEC1', 'IKBIP', 'MYBPC3', 'TUBA1B', 'PPIAL4E', 'RGL4', 'NPIPB4', 'SERTAD1', 'FRYL', 'KCNK2', 'RAP1GAP', 'HOMER2', 'TMEM27', 'NME3', 'C15orf48', 'LPIN1', 'C1orf131', 'ARL6IP4', 'NDP', 'ZFAS1', 'TNC', 'H3F3B', 'ZNF205', 'C1QL1', 'SUSD4', 'FAM3A', 'LRRC66', 'C7orf55', 'C15orf41', 'CCDC78', 'IL6R', 'MAEA', 'COX6B1', 'EFCAB10', 'PHYHIP', 'KDM4C', 'PPP1R2P3', 'HELZ2'}) and 3 missing columns ({'xaxis', 'yaxis', 'r'}). This happened while the csv dataset builder was generating data using hf://datasets/jiawennnn/STimage-1K4M/ST/gene_exp/GSE144239_GSM4284316_count.csv (at revision eb59a849e82d5e0f3bdd2fd269891dffd63da998) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast Unnamed: 0: string MIR1302-2: double RP11-34P13.7: double RP11-34P13.14: double FO538757.1: double RP4-669L17.10: double RP11-206L10.9: double LINC00115: double RP11-54O7.1: double SAMD11: double NOC2L: double KLHL17: double PLEKHN1: double PERM1: double HES4: double ISG15: double AGRN: double RNF223: double C1orf159: double TTLL10: double TNFRSF18: double TNFRSF4: double SDF4: double B3GALT6: double FAM132A: double UBE2J2: double SCNN1D: double ACAP3: double PUSL1: double CPSF3L: double CPTP: double TAS1R3: double DVL1: double MXRA8: double AURKAIP1: double CCNL2: double MRPL20: double RP4-758J18.13: double ANKRD65: double VWA1: double ATAD3C: double ATAD3B: double ATAD3A: double TMEM240: double SSU72: double FNDC10: double MIB2: double MMP23B: double CDK11B: double SLC35E2B: double CDK11A: double SLC35E2: double NADK: double GNB1: double RP1-140A9.1: double CALML6: double TMEM52: double CFAP74: double GABRD: double PRKCZ: double FAAP20: double SKI: double MORN1: double RER1: double PEX10: double PLCH2: double PANK4: double HES5: double TNFRSF14: double MMEL1: double FAM213B: double TTC34: double PRDM16: double ARHGEF16: double MEGF6: double RP11-46F15.2: double TPRG1L: double WRAP73: double TP73: double SMIM1: double LRRC47: double CEP104: double DFFB: double C1orf174: double AJAP1: double NPHP4: double KCNAB2: double RP1-120G22.11: double RPL22: double RNF207: double ICMT: double GPR153: double ACOT7: double HES2: double ESPN: double TNFRSF25: double PLEKHG5: double NOL9: ... e NSDHL: double ZNF185: double PNMA3: double PNMA6A: double LL0XNC01-16G2.1: double ZNF275: double ZFP92: double TREX2: double HAUS7: double BGN: double FAM58A: double DUSP9: double SLC6A8: double BCAP31: double ABCD1: double SRPK3: double IDH3G: double SSR4: double PDZD4: double AVPR2: double L1CAM: double ARHGAP4: double NAA10: double RENBP: double HCFC1: double TMEM187: double IRAK1: double MECP2: double TKTL1: double FLNA: double EMD: double DNASE1L1: double RPL10: double TAZ: double ATP6AP1: double GDI1: double FAM50A: double PLXNA3: double LAGE3: double UBL4A: double SLC10A3: double FAM3A: double G6PD: double IKBKG: double CTAG1A: double CTAG1B: double CTAG2: double GAB3: double DKC1: double MPP1: double H2AFB1: double F8A1: double F8: double FUNDC2: double BRCC3: double MTCP1: double VBP1: double CLIC2: double H2AFB2: double F8A2: double F8A3: double H2AFB3: double TMLHE: double SPRY3: double VAMP7: double IL9R: double RPS4Y1: double ZFY: double LINC00278: double PCDH11Y: double TBL1Y: double USP9Y: double DDX3Y: double UTY: double TMSB4Y: double NLGN4Y: double FAM224B: double FAM224A: double HSFY1: double HSFY2: double TTTY14: double KDM5D: double EIF1AY: double RPS4Y2: double BPY2: double DAZ1: double DAZ2: double AC012005.2: double AC012005.1: double BPY2B: double DAZ3: double DAZ4: double BPY2C: double AC006386.1: double LINC00266-4P: double AC006328.1: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1929671 to {'Unnamed: 0': Value(dtype='string', id=None), 'yaxis': Value(dtype='float64', id=None), 'xaxis': Value(dtype='float64', id=None), 'r': Value(dtype='float64', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1524, in compute_config_parquet_and_info_response parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet( File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1884, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2015, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 17138 new columns ({'RP3-382I10.7', 'MIR3180-4', 'IL4I1', 'ARL14EP', 'CDX2', 'GNA11', 'PDDC1', 'BRD2', 'PIGN', 'KIF1C', 'LRRC41', 'RP11-336A10.4', 'RP11-727F15.14', 'GNA13', 'TNPO1', 'TANK', 'ZCCHC2', 'LDOC1', 'PGS1', 'LINGO1', 'CCNK', 'ENTPD6', 'HESX1', 'DOCK11', 'CWC25', 'GJC2', 'NNAT', 'NDUFA6', 'SEMA4A', 'C2CD3', 'RAPGEFL1', 'SHF', 'POLR2E', 'DHRS7', 'EFNA5', 'MBOAT7', 'TMEM88', 'GOLPH3', 'CHID1', 'PPP2R5E', 'CCNB1IP1', 'CH507-24F1.2', 'GLT1D1', 'CARD16', 'ACER1', 'HSPA6', 'HSCB', 'ZBTB7C', 'MAGEH1', 'SCARA3', 'RFX1', 'UAP1L1', 'TTC7A', 'STAT5B', 'RAN', 'PARP3', 'HPSE', 'ANAPC16', 'AC006116.20', 'STYX', 'CLEC2B', 'KLF4', 'HCG18', 'TNFAIP1', 'QSOX2', 'GALNT6', 'RP11-442H21.2', 'HOXD1', 'GABBR2', 'LINC01621', 'ELL', 'CD48', 'CCDC81', 'SAE1', 'HS3ST6', 'CCSER2', 'UBE2J2', 'FOXB1', 'GJA3', 'TRIM68', 'RING1', 'C8orf44', 'EFCAB2', 'APAF1', 'AIFM1', 'CCT4', 'KLHL31', 'RPL32', 'LY9', 'C5orf45', 'CA2', 'RP11-30J20.1', 'SPATC1L', 'DLX5', 'RP11-532F12.5', 'B4GALT1', 'SPRYD4', 'FYTTD1', 'HEATR5B', 'LINC00441', 'HIST1H2AE', 'PSMB7', 'WDR6', 'CUTC', 'ERCC2', 'C16orf86', 'FAM72A', 'CSPG5', 'MCU', 'FZD6', 'SYK', 'TPGS2', 'PPT1', 'NPPC', 'HIBADH', 'C1orf116', 'GCC1', 'ENO4', 'PCMT1', 'EXD3', 'RNF103', 'TDRD12', 'SYT15', 'GGTLC3', 'FAM228A', 'KLC2', 'FUT1', 'CBSL', 'NRROS', 'TMEM156', 'ZNF720', 'RAB14', 'COQ9', 'AC092580.4', 'SCOC', 'SRP72', 'PIAS2', 'CUTA', 'NBAS', 'BMX', 'SLFN5', 'TRAF2', 'YBX2', 'ASIC1', 'SASS6', 'PRELP', 'ERP27', 'FBXL22', 'FBXO39', 'LTK', 'PDE6D', 'NOSTRIN', 'SYCP2', 'ZNF333', 'CSF2', ' ... 7', 'NOP58', 'CKS1B', 'KDM7A', 'SOCS7', 'KATNAL2', 'RP11-66B24.2', 'CRACR2B', 'ABRACL', 'RPL31', 'TIMM10', 'CARMN', 'OR51E1', 'SPRYD3', 'GNB1L', 'NDC80', 'F2RL2', 'CDK20', 'PIK3C2B', 'HMG20A', 'CEACAM5', 'RAB32', 'METRNL', 'MYCBP2', 'INTS6-AS1', 'RGCC', 'IZUMO1', 'KEL', 'TM9SF1', 'PRR15', 'MMP25', 'PRR5', 'GLUD2', 'TMEM106A', 'VAMP1', 'DNAJC14', 'RNF122', 'NHSL1', 'RBCK1', 'EGLN1', 'CSRNP1', 'HSFX1', 'MED29', 'EPN3', 'MIEF1', 'GBA2', 'GZMM', 'NLRP2B', 'TIMM21', 'ATP11B', 'BBS2', 'PLPP7', 'PRKCQ', 'RP11-618L22.1', 'GSAP', 'STK38L', 'GS1-393G12.13', 'AC093388.3', 'B3GALT5', 'MEGF6', 'MUC15', 'CTD-2298J14.2', 'TRIM23', 'H2AFV', 'CA8', 'ATE1', 'FADD', 'BIN3', 'MPZ', 'MICAL2', 'FILIP1L', 'ZNF420', 'NME8', 'TPO', 'S100A12', 'TRIM37', 'AREG', 'WBSCR17', 'VSIG10L', 'ATG2B', 'MARCH9', 'PHEX', 'GTF2A2', 'RPS6KA5', 'IDI1', 'HSPA4', 'CDA', 'ASB12', 'STAU1', 'ZSCAN32', 'NDE1', 'C2CD2', 'ZNF83', 'INTS5', 'EMC7', 'DNAH2', 'EHD3', 'EMG1', 'TIPARP-AS1', 'VAMP7', 'CTC-260F20.3', 'MOSPD3', 'PELI2', 'FBXL17', 'UBR2', 'KCNN1', 'ANKRD54', 'PCGF3', 'ABR', 'ST3GAL1', 'CTB-12A17.3', 'ATP6AP2', 'RAB20', 'COX16', 'GTF2I', 'LMCD1', 'PANX1', 'ADAMDEC1', 'IKBIP', 'MYBPC3', 'TUBA1B', 'PPIAL4E', 'RGL4', 'NPIPB4', 'SERTAD1', 'FRYL', 'KCNK2', 'RAP1GAP', 'HOMER2', 'TMEM27', 'NME3', 'C15orf48', 'LPIN1', 'C1orf131', 'ARL6IP4', 'NDP', 'ZFAS1', 'TNC', 'H3F3B', 'ZNF205', 'C1QL1', 'SUSD4', 'FAM3A', 'LRRC66', 'C7orf55', 'C15orf41', 'CCDC78', 'IL6R', 'MAEA', 'COX6B1', 'EFCAB10', 'PHYHIP', 'KDM4C', 'PPP1R2P3', 'HELZ2'}) and 3 missing columns ({'xaxis', 'yaxis', 'r'}). This happened while the csv dataset builder was generating data using hf://datasets/jiawennnn/STimage-1K4M/ST/gene_exp/GSE144239_GSM4284316_count.csv (at revision eb59a849e82d5e0f3bdd2fd269891dffd63da998) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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Unnamed: 0
string | yaxis
float64 | xaxis
float64 | r
float64 |
---|---|---|---|
GSE144239_GSM4284316_10x26 | 5,741.5 | 3,845.3 | 45.125581 |
GSE144239_GSM4284316_10x28 | 6,142.9 | 3,841.4 | 45.125581 |
GSE144239_GSM4284316_10x30 | 6,549.5 | 3,834.4 | 45.125581 |
GSE144239_GSM4284316_10x32 | 6,951.6 | 3,839.6 | 45.125581 |
GSE144239_GSM4284316_10x34 | 7,355.5 | 3,839.4 | 45.125581 |
GSE144239_GSM4284316_10x36 | 7,756.1 | 3,839.3 | 45.125581 |
GSE144239_GSM4284316_10x38 | 8,144.4 | 3,838.8 | 45.125581 |
GSE144239_GSM4284316_10x40 | 8,554.1 | 3,833.4 | 45.125581 |
GSE144239_GSM4284316_10x44 | 9,356.4 | 3,830.9 | 45.125581 |
GSE144239_GSM4284316_10x46 | 9,758 | 3,828.8 | 45.125581 |
GSE144239_GSM4284316_10x48 | 10,156 | 3,830.9 | 45.125581 |
GSE144239_GSM4284316_11x25 | 5,551.5 | 4,022.2 | 45.125581 |
GSE144239_GSM4284316_11x27 | 5,940.9 | 4,020.2 | 45.125581 |
GSE144239_GSM4284316_11x29 | 6,353 | 4,009.4 | 45.125581 |
GSE144239_GSM4284316_11x31 | 6,757.6 | 4,014.4 | 45.125581 |
GSE144239_GSM4284316_11x33 | 7,155.4 | 4,013.1 | 45.125581 |
GSE144239_GSM4284316_11x35 | 7,557.4 | 4,014.1 | 45.125581 |
GSE144239_GSM4284316_11x37 | 7,947.4 | 4,004.7 | 45.125581 |
GSE144239_GSM4284316_11x39 | 8,337.8 | 4,010.5 | 45.125581 |
GSE144239_GSM4284316_11x41 | 8,760.5 | 4,011.8 | 45.125581 |
GSE144239_GSM4284316_11x43 | 9,164.1 | 4,015.6 | 45.125581 |
GSE144239_GSM4284316_11x45 | 9,564 | 4,006.9 | 45.125581 |
GSE144239_GSM4284316_11x47 | 9,959.5 | 4,018.4 | 45.125581 |
GSE144239_GSM4284316_11x49 | 10,355.8 | 4,014.1 | 45.125581 |
GSE144239_GSM4284316_12x22 | 4,940.1 | 4,194.9 | 45.125581 |
GSE144239_GSM4284316_12x24 | 5,340.2 | 4,194.8 | 45.125581 |
GSE144239_GSM4284316_12x26 | 5,747.8 | 4,194.1 | 45.125581 |
GSE144239_GSM4284316_12x28 | 6,143.3 | 4,195.9 | 45.125581 |
GSE144239_GSM4284316_12x30 | 6,554.3 | 4,190.9 | 45.125581 |
GSE144239_GSM4284316_12x32 | 6,951.6 | 4,195.8 | 45.125581 |
GSE144239_GSM4284316_12x34 | 7,354.3 | 4,197.5 | 45.125581 |
GSE144239_GSM4284316_12x36 | 7,750.3 | 4,200.9 | 45.125581 |
GSE144239_GSM4284316_12x38 | 8,142.6 | 4,186.9 | 45.125581 |
GSE144239_GSM4284316_12x40 | 8,553.2 | 4,187.2 | 45.125581 |
GSE144239_GSM4284316_12x42 | 8,954.5 | 4,190.6 | 45.125581 |
GSE144239_GSM4284316_12x44 | 9,357.6 | 4,191.9 | 45.125581 |
GSE144239_GSM4284316_12x46 | 9,757.8 | 4,194.4 | 45.125581 |
GSE144239_GSM4284316_12x48 | 10,154.5 | 4,193.3 | 45.125581 |
GSE144239_GSM4284316_13x21 | 4,734.1 | 4,378 | 45.125581 |
GSE144239_GSM4284316_13x23 | 5,143 | 4,373.2 | 45.125581 |
GSE144239_GSM4284316_13x25 | 5,539.8 | 4,382.1 | 45.125581 |
GSE144239_GSM4284316_13x27 | 5,933.8 | 4,384.9 | 45.125581 |
GSE144239_GSM4284316_13x29 | 6,348.2 | 4,374.1 | 45.125581 |
GSE144239_GSM4284316_13x31 | 6,745.5 | 4,377.5 | 45.125581 |
GSE144239_GSM4284316_13x33 | 7,148.5 | 4,380.3 | 45.125581 |
GSE144239_GSM4284316_13x35 | 7,555.3 | 4,379 | 45.125581 |
GSE144239_GSM4284316_13x37 | 7,949.6 | 4,375.2 | 45.125581 |
GSE144239_GSM4284316_13x39 | 8,347.3 | 4,372.9 | 45.125581 |
GSE144239_GSM4284316_13x41 | 8,752.6 | 4,376.6 | 45.125581 |
GSE144239_GSM4284316_13x43 | 9,160.5 | 4,375.2 | 45.125581 |
GSE144239_GSM4284316_13x45 | 9,558.7 | 4,368.6 | 45.125581 |
GSE144239_GSM4284316_13x47 | 9,955.3 | 4,374.2 | 45.125581 |
GSE144239_GSM4284316_13x49 | 10,358.7 | 4,382.5 | 45.125581 |
GSE144239_GSM4284316_14x18 | 4,130.1 | 4,567 | 45.125581 |
GSE144239_GSM4284316_14x20 | 4,522.4 | 4,558.1 | 45.125581 |
GSE144239_GSM4284316_14x22 | 4,925.8 | 4,555.8 | 45.125581 |
GSE144239_GSM4284316_14x24 | 5,326.6 | 4,555.5 | 45.125581 |
GSE144239_GSM4284316_14x26 | 5,727 | 4,560.2 | 45.125581 |
GSE144239_GSM4284316_14x28 | 6,132.8 | 4,554.1 | 45.125581 |
GSE144239_GSM4284316_14x30 | 6,524.2 | 4,550.7 | 45.125581 |
GSE144239_GSM4284316_14x32 | 6,928.3 | 4,554.7 | 45.125581 |
GSE144239_GSM4284316_14x34 | 7,329 | 4,559.4 | 45.125581 |
GSE144239_GSM4284316_14x36 | 7,729.1 | 4,558.3 | 45.125581 |
GSE144239_GSM4284316_14x38 | 8,128.4 | 4,552.6 | 45.125581 |
GSE144239_GSM4284316_14x40 | 8,527.1 | 4,555.9 | 45.125581 |
GSE144239_GSM4284316_14x42 | 8,929.7 | 4,557.5 | 45.125581 |
GSE144239_GSM4284316_14x44 | 9,328.8 | 4,559.7 | 45.125581 |
GSE144239_GSM4284316_14x46 | 9,731.5 | 4,549.9 | 45.125581 |
GSE144239_GSM4284316_14x48 | 10,129.5 | 4,554.9 | 45.125581 |
GSE144239_GSM4284316_14x50 | 10,531.1 | 4,556.3 | 45.125581 |
GSE144239_GSM4284316_15x17 | 3,939.2 | 4,743.3 | 45.125581 |
GSE144239_GSM4284316_15x19 | 4,327.9 | 4,745.6 | 45.125581 |
GSE144239_GSM4284316_15x21 | 4,726.3 | 4,734.8 | 45.125581 |
GSE144239_GSM4284316_15x23 | 5,128.5 | 4,735.4 | 45.125581 |
GSE144239_GSM4284316_15x25 | 5,536.5 | 4,736.6 | 45.125581 |
GSE144239_GSM4284316_15x27 | 5,931.5 | 4,741.7 | 45.125581 |
GSE144239_GSM4284316_15x29 | 6,329.8 | 4,730 | 45.125581 |
GSE144239_GSM4284316_15x31 | 6,729.5 | 4,734.1 | 45.125581 |
GSE144239_GSM4284316_15x33 | 7,130.9 | 4,738.7 | 45.125581 |
GSE144239_GSM4284316_15x35 | 7,532.7 | 4,739.5 | 45.125581 |
GSE144239_GSM4284316_15x37 | 7,931.4 | 4,729.9 | 45.125581 |
GSE144239_GSM4284316_15x39 | 8,322 | 4,738.1 | 45.125581 |
GSE144239_GSM4284316_15x41 | 8,731 | 4,736.8 | 45.125581 |
GSE144239_GSM4284316_15x43 | 9,131.5 | 4,740 | 45.125581 |
GSE144239_GSM4284316_15x45 | 9,533.9 | 4,733.1 | 45.125581 |
GSE144239_GSM4284316_15x47 | 9,933.6 | 4,733.6 | 45.125581 |
GSE144239_GSM4284316_15x49 | 10,329.9 | 4,735.9 | 45.125581 |
GSE144239_GSM4284316_15x51 | 10,734.1 | 4,738.6 | 45.125581 |
GSE144239_GSM4284316_16x16 | 3,732.4 | 4,919.1 | 45.125581 |
GSE144239_GSM4284316_16x18 | 4,132.2 | 4,926.6 | 45.125581 |
GSE144239_GSM4284316_16x20 | 4,527.4 | 4,922.8 | 45.125581 |
GSE144239_GSM4284316_16x22 | 4,925.8 | 4,917.7 | 45.125581 |
GSE144239_GSM4284316_16x24 | 5,333.2 | 4,915.9 | 45.125581 |
GSE144239_GSM4284316_16x26 | 5,724.5 | 4,925.1 | 45.125581 |
GSE144239_GSM4284316_16x28 | 6,132.7 | 4,914 | 45.125581 |
GSE144239_GSM4284316_16x30 | 6,527.9 | 4,915.3 | 45.125581 |
GSE144239_GSM4284316_16x32 | 6,930.5 | 4,918.4 | 45.125581 |
GSE144239_GSM4284316_16x34 | 7,330 | 4,917.3 | 45.125581 |
GSE144239_GSM4284316_16x36 | 7,733 | 4,916.8 | 45.125581 |
GSE144239_GSM4284316_16x38 | 8,127.2 | 4,913 | 45.125581 |
STimage-1K4M Dataset
Welcome to the STimage-1K4M Dataset repository. This dataset is designed to foster research in the field of spatial transcriptomics, combining high-resolution histopathology images with detailed gene expression data.
Dataset Description
STimage-1K4M consists of 1,149 spatial transcriptomics slides, totaling over 4 million spots with paired gene expression data. This dataset includes:
- Images.
- Gene expression profiles matched with high-resolution histopathology images.
- Spatial coordinates for each spot.
Data structure
The data structure is organized as follows:
βββ annotation # Pathologist annotation
βββ meta # Test files (alternatively `spec` or `tests`)
β βββ bib.txt # the bibtex for all studies with pmid included in the dataset
β βββ meta_all_gene.csv # The meta information
βββ ST # Include all data for tech: Spatial Transcriptomics
β βββ coord # Include the spot coordinates & spot radius of each slide
β βββ gene_exp # Include the gene expression of each slide
β βββ image # Include the image each slide
βββ Visium # Include all data for tech: Visium, same structure as ST
βββ VisiumHD # Include all data for tech: VisiumHD, same structure as ST
Repository structure
The code for data processing and reproducing evaluation result in the paper are in Document.
Acknowledgement
The fine-tuning and evaluation codes borrows heavily from CLIP and PLIP.
Citation
@misc{chen2024stimage1k4m,
title={STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics},
author={Jiawen Chen and Muqing Zhou and Wenrong Wu and Jinwei Zhang and Yun Li and Didong Li},
year={2024},
eprint={2406.06393},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
License
All code is licensed under the MIT License - see the LICENSE.md file for details.
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