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pmid:33361643

Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis.

Zhen Sun · Chen Liu · Steven Y Cheng

Journal of biomedical research · 2020 doi:10.7555/JBR.34.20200021

Paper

complete

Experiment

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Data

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Analysis

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pmid:33361643
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title
Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis.
doi
10.7555/JBR.34.20200021
pmid
33361643
authors array · 3 items
[0]
Zhen Sun
[1]
Chen Liu
[2]
Steven Y Cheng
journal
Journal of biomedical research
year
2020
abstract
Colorectal cancer (CRC) is one of the most deadly cancers in the world with few reliable biomarkers that have been selected into clinical guidelines for prognosis of CRC patients. In this study, mRNA microarray datasets GSE113513, GSE21510, GSE44076, and GSE32323 were obtained from the Gene Expression Omnibus (GEO) and analyzed with bioinformatics to identify hub genes in CRC development. Differentially expressed genes (DEGs) were analyzed using the GEO2R tool. Gene ontology (GO) and KEGG analyses were performed through the DAVID database. STRING database and Cytoscape software were used to construct a protein-protein interaction (PPI) network and identify key modules and hub genes. Survival analyses of the DEGs were performed on GEPIA database. The Connectivity Map database was used to screen potential drugs. A total of 865 DEGs were identified, including 374 upregulated and 491 downregulated genes. These DEGs were mainly associated with metabolic pathways, pathways in cancer, cell cycle and so on. The PPI network was identified with 863 nodes and 5817 edges. Survival analysis revealed that HMMR, PAICS, ETFDH, and SCG2 were significantly associated with overall survival of CRC patients. And blebbistatin and sulconazole were identified as candidate drugs. In conclusion, our study found four hub genes involved in CRC, which may provide novel potential biomarkers for CRC prognosis, and two potential candidate drugs for CRC.
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To identify the DEGs, we used the NCBI-GEO2R online tool to analyze these datasets. Subsequently, adjusted P-value <0.05 and |log 2(fold change)| >1 were set as the cutoff criteria to screen the significant DEGs of each dataset. Finally, Venn diagrams were performed to get the overlap significant DEGs of the 4 datasets.
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sections[4] "Identification of DEGs and data preprocessing" paragraph 2
quote
To identify the DEGs, we used the NCBI-GEO2R online tool to analyze these datasets. Subsequently, adjusted P-value <0.05 and |log 2(fold change)| >1 were set as the cutoff criteria to screen the significant DEGs of each dataset. Finally, Venn diagrams were performed to get the overlap significant DEGs of the 4 datasets.
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A total of 4 GEO datasets were selected, including GSE113513, GSE21510, GSE44076, and GSE32323.
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sections[3] "Data resources" paragraph 2
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A total of 4 GEO datasets were selected, including GSE113513, GSE21510, GSE44076, and GSE32323.
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GSM1077783
[186]
GSM1077784
[187]
GSM1077785
[188]
GSM1077786
[189]
GSM1077787
[190]
GSM1077788
[191]
GSM1077789
[192]
GSM1077790
[193]
GSM1077791
[194]
GSM1077792
[195]
GSM1077793
[196]
GSM1077794
[197]
GSM1077795
[198]
GSM1077796
[199]
GSM1077797
[200]
GSM1077798
[201]
GSM1077799
[202]
GSM1077800
[203]
GSM1077801
[204]
GSM1077802
[205]
GSM1077803
[206]
GSM1077804
[207]
GSM1077805
[208]
GSM1077806
[209]
GSM1077807
[210]
GSM1077808
[211]
GSM1077809
[212]
GSM1077810
[213]
GSM1077811
[214]
GSM1077812
[215]
GSM1077813
[216]
GSM1077814
[217]
GSM1077815
[218]
GSM1077816
[219]
GSM1077817
[220]
GSM1077818
[221]
GSM1077819
[222]
GSM1077820
[223]
GSM1077821
[224]
GSM1077822
[225]
GSM1077823
[226]
GSM1077824
[227]
GSM1077825
[228]
GSM1077826
[229]
GSM1077827
[230]
GSM1077828
[231]
GSM1077829
[232]
GSM1077830
[233]
GSM1077831
[234]
GSM1077832
[235]
GSM1077833
[236]
GSM1077834
[237]
GSM1077835
[238]
GSM1077836
[239]
GSM1077837
[240]
GSM1077838
[241]
GSM1077839
[242]
GSM1077840
[243]
GSM1077841
[244]
GSM1077842
[245]
GSM1077843
sample_count
246
group_sizes
null
group_sizes_basis
null
platform
13667
taxon
Homo sapiens
title
Gene expression data from healthy, adjacent normal and tumor colon cells
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 16 fields
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asset:table:pmid:33361643:1
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:6a0a01a37989eb850007918295baf201d1b156e8f7fdc488dbe31803ee70487c
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Gene summaries of the four hub genes
structure object · 5 fields
pmcid
PMC7874272
section_index
7
section_title
Analysis and validation of hub genes
row_count
6
column_count
6
table object · 8 fields
label
1
caption
Gene summaries of the four hub genes
rows array · 6 items
[0] array · 3 items
[0]
Gene
[1]
Summary
[2]
Microarray datasets [P-value, log2(fold change)]
[1] array · 4 items
[0]
GSE113513
[1]
GSE21510
[2]
GSE44076
[3]
GSE32323
[2] array · 6 items
[0]
HMMR
[1]
The protein encoded by this gene is involved in cell motility. It is expressed in breast tissue and together with other proteins, it forms a complex with BRCA1 and BRCA2, thus is potentially associated with higher risk of breast cancer. Alternatively spliced transcript variants encoding different isoforms have been noted for this gene.
[2]
6.82e−04, 1.11
[3]
3.84e−35, 3.22
[4]
5.32e−22, 1.20
[5]
2.63e−04, 1.63
[3] array · 6 items
[0]
PAICS
[1]
This gene encodes a bifunctional enzyme containing phosphoribosylaminoimidazole carboxylase activity in its N-terminal region and phosphoribosylaminoimidazole succinocarboxamide synthetase in its C-terminal region. It catalyzes steps 6 and 7 of purine biosynthesis. The gene is closely linked and divergently transcribed with a locus that encodes an enzyme in the same pathway, and transcription of the two genes is coordinately regulated. The human genome contains several pseudogenes of this gene. Multiple transcript variants encoding different isoforms have been found for this gene.
[2]
4.77e−08, 1.31
[3]
5.71e−47, 2.48
[4]
2.14e−55, 1.49
[5]
1.38e−06, 1.73
[4] array · 6 items
[0]
ETFDH
[1]
This gene encodes a component of the electron-transfer system in mitochondria and is essential for electron transfer from a number of mitochondrial flavin-containing dehydrogenases to the main respiratory chain. Mutations in this gene are associated with glutaric acidemia. Alternatively spliced transcript variants that encode distinct isoforms have been observed.
[2]
1.78e−08, −1.47
[3]
1.67e−27, −1.92
[4]
1.80e−71, −1.85
[5]
3.14e−08, −1.78
[5] array · 6 items
[0]
SCG2
[1]
The protein encoded by this gene is a member of the chromogranin/secretogranin family of neuroendocrine secretory proteins. Studies in rodents suggest that the full-length protein, secretogranin II, is involved in the packaging or sorting of peptide hormones and neuropeptides into secretory vesicles. The full-length protein is cleaved to produce the active peptide secretoneurin, which exerts chemotaxic effects on specific cell types, and EM66, whose function is unknown.
[2]
2.37e−07, −2.50
[3]
1.13e−17, −1.86
[4]
4.83e−25, −1.90
[5]
2.91e−07, −2.28
locator
section[13]/table-wrap[1]#Table1
[6] object · 16 fields
id
asset:table:pmid:33361643:2
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:6a0a01a37989eb850007918295baf201d1b156e8f7fdc488dbe31803ee70487c
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section[13]/table-wrap[1]#Table1
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Gene summaries of the four hub genes
structure object · 5 fields
pmcid
PMC7874272
section_index
13
section_title
Analysis and validation of hub genes
row_count
6
column_count
6
table object · 8 fields
label
1
caption
Gene summaries of the four hub genes
rows array · 6 items
[0] array · 3 items
[0]
Gene
[1]
Summary
[2]
Microarray datasets [P-value, log2(fold change)]
[1] array · 4 items
[0]
GSE113513
[1]
GSE21510
[2]
GSE44076
[3]
GSE32323
[2] array · 6 items
[0]
HMMR
[1]
The protein encoded by this gene is involved in cell motility. It is expressed in breast tissue and together with other proteins, it forms a complex with BRCA1 and BRCA2, thus is potentially associated with higher risk of breast cancer. Alternatively spliced transcript variants encoding different isoforms have been noted for this gene.
[2]
6.82e−04, 1.11
[3]
3.84e−35, 3.22
[4]
5.32e−22, 1.20
[5]
2.63e−04, 1.63
[3] array · 6 items
[0]
PAICS
[1]
This gene encodes a bifunctional enzyme containing phosphoribosylaminoimidazole carboxylase activity in its N-terminal region and phosphoribosylaminoimidazole succinocarboxamide synthetase in its C-terminal region. It catalyzes steps 6 and 7 of purine biosynthesis. The gene is closely linked and divergently transcribed with a locus that encodes an enzyme in the same pathway, and transcription of the two genes is coordinately regulated. The human genome contains several pseudogenes of this gene. Multiple transcript variants encoding different isoforms have been found for this gene.
[2]
4.77e−08, 1.31
[3]
5.71e−47, 2.48
[4]
2.14e−55, 1.49
[5]
1.38e−06, 1.73
[4] array · 6 items
[0]
ETFDH
[1]
This gene encodes a component of the electron-transfer system in mitochondria and is essential for electron transfer from a number of mitochondrial flavin-containing dehydrogenases to the main respiratory chain. Mutations in this gene are associated with glutaric acidemia. Alternatively spliced transcript variants that encode distinct isoforms have been observed.
[2]
1.78e−08, −1.47
[3]
1.67e−27, −1.92
[4]
1.80e−71, −1.85
[5]
3.14e−08, −1.78
[5] array · 6 items
[0]
SCG2
[1]
The protein encoded by this gene is a member of the chromogranin/secretogranin family of neuroendocrine secretory proteins. Studies in rodents suggest that the full-length protein, secretogranin II, is involved in the packaging or sorting of peptide hormones and neuropeptides into secretory vesicles. The full-length protein is cleaved to produce the active peptide secretoneurin, which exerts chemotaxic effects on specific cell types, and EM66, whose function is unknown.
[2]
2.37e−07, −2.50
[3]
1.13e−17, −1.86
[4]
4.83e−25, −1.90
[5]
2.91e−07, −2.28
locator
section[13]/table-wrap[1]#Table1
[7] object · 16 fields
id
asset:table:pmid:33361643:3
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:65f342a24095ef3ebc102405b7580262a6116cff7d926a2c0d6ebc27c0d7c787
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verified
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read_table
reader_status
available
identifier
section[14]/table-wrap[1]#Table2
version
null
note
The significant small active molecules that may reverse the DEGs of CRC predicted by CMap
structure object · 5 fields
pmcid
PMC7874272
section_index
14
section_title
Identification of related active small molecules
row_count
39
column_count
9
table object · 8 fields
label
2
caption
The significant small active molecules that may reverse the DEGs of CRC predicted by CMap
rows array · 39 items
[0] array · 9 items
[0]
CMap name
[1]
Count
[2]
Enrichment
[3]
P-value
[4]
[5]
CMap name
[6]
Count
[7]
Enrichment
[8]
P-value
[1] array · 9 items
[0]
DL-thiorphan
[1]
2
[2]
−0.976
[3]
0.001 27
[4]
[5]
8-azaguanine
[6]
4
[7]
−0.644
[8]
0.038 11
[2] array · 9 items
[0]
Quinostatin
[1]
2
[2]
−0.878
[3]
0.029 90
[4]
[5]
Acepromazine
[6]
4
[7]
−0.640
[8]
0.040 08
[3] array · 9 items
[0]
1,4-chrysenequinone
[1]
2
[2]
−0.866
[3]
0.035 75
[4]
[5]
Doxazosin
[6]
4
[7]
−0.639
[8]
0.040 48
[4] array · 9 items
[0]
Menadione
[1]
2
[2]
−0.852
[3]
0.043 24
[4]
[5]
Mefloquine
[6]
5
[7]
−0.637
[8]
0.016 28
[5] array · 9 items
[0]
Blebbistatin
[1]
2
[2]
−0.844
[3]
0.048 59
[4]
[5]
Trifluridine
[6]
4
[7]
−0.637
[8]
0.041 87
[6] array · 9 items
[0]
trazodone
[1]
3
[2]
−0.813
[3]
0.013 20
[4]
[5]
Clomipramine
[6]
4
[7]
−0.636
[8]
0.042 51
[7] array · 9 items
[0]
Thioguanosine
[1]
4
[2]
−0.809
[3]
0.002 59
[4]
[5]
Trioxysalen
[6]
4
[7]
−0.633
[8]
0.044 24
[8] array · 9 items
[0]
Sulconazole
[1]
4
[2]
−0.805
[3]
0.002 82
[4]
[5]
Corbadrine
[6]
4
[7]
−0.629
[8]
0.046 73
[9] array · 9 items
[0]
0297417-0002B
[1]
3
[2]
−0.792
[3]
0.018 27
[4]
[5]
Etofenamate
[6]
4
[7]
−0.624
[8]
0.049 27
[10] array · 9 items
[0]
Etacrynic acid
[1]
3
[2]
−0.776
[3]
0.022 99
[4]
[5]
Phthalylsulfathiazole
[6]
5
[7]
−0.616
[8]
0.022 71
[11] array · 9 items
[0]
Latamoxef
[1]
3
[2]
−0.759
[3]
0.028 76
[4]
[5]
Oxetacaine
[6]
5
[7]
−0.610
[8]
0.025 23
[12] array · 9 items
[0]
GW-8510
[1]
4
[2]
−0.757
[3]
0.007 12
[4]
[5]
Amiodarone
[6]
5
[7]
−0.601
[8]
0.029 00
[13] array · 9 items
[0]
Triflusal
[1]
3
[2]
−0.755
[3]
0.030 11
[4]
[5]
Meticrane
[6]
5
[7]
−0.599
[8]
0.029 62
[14] array · 9 items
[0]
Piperidolate
[1]
3
[2]
−0.743
[3]
0.034 63
[4]
[5]
Vorinostat
[6]
12
[7]
−0.596
[8]
0.000 18
[15] array · 9 items
[0]
Daunorubicin
[1]
4
[2]
−0.733
[3]
0.010 19
[4]
[5]
Tranylcypromine
[6]
5
[7]
−0.592
[8]
0.032 64
[16] array · 9 items
[0]
Repaglinide
[1]
4
[2]
−0.727
[3]
0.011 42
[4]
[5]
Bromocriptine
[6]
5
[7]
−0.573
[8]
0.042 46
[17] array · 9 items
[0]
Camptothecin
[1]
3
[2]
−0.725
[3]
0.042 85
[4]
[5]
Zimeldine
[6]
5
[7]
−0.572
[8]
0.043 38
[18] array · 9 items
[0]
Norcyclobenzaprine
[1]
4
[2]
−0.723
[3]
0.012 02
[4]
[5]
Clemizole
[6]
5
[7]
−0.568
[8]
0.045 48
[19] array · 9 items
[0]
Ronidazole
[1]
3
[2]
−0.711
[3]
0.049 19
[4]
[5]
Astemizole
[6]
5
[7]
−0.567
[8]
0.046 14
[20] array · 9 items
[0]
Ellipticine
[1]
4
[2]
−0.708
[3]
0.015 14
[4]
[5]
Meclozine
[6]
5
[7]
−0.565
[8]
0.047 08
[21] array · 9 items
[0]
Gliclazide
[1]
4
[2]
−0.707
[3]
0.015 28
[4]
[5]
Procaine
[6]
5
[7]
−0.565
[8]
0.047 46
[22] array · 9 items
[0]
Phenoxybenzamine
[1]
4
[2]
−0.704
[3]
0.015 76
[4]
[5]
Cloperastine
[6]
6
[7]
−0.551
[8]
0.031 56
[23] array · 9 items
[0]
0175029-0000
[1]
6
[2]
−0.701
[3]
0.001 63
[4]
[5]
Famprofazone
[6]
6
[7]
−0.543
[8]
0.036 21
[24] array · 9 items
[0]
Tyloxapol
[1]
4
[2]
−0.694
[3]
0.018 52
[4]
[5]
Dipyridamole
[6]
6
[7]
−0.537
[8]
0.039 63
[25] array · 9 items
[0]
Skimmianine
[1]
4
[2]
−0.690
[3]
0.020 01
[4]
[5]
Promazine
[6]
6
[7]
−0.523
[8]
0.047 85
[26] array · 9 items
[0]
Bisacodyl
[1]
4
[2]
−0.690
[3]
0.020 03
[4]
[5]
Trifluoperazine
[6]
16
[7]
−0.504
[8]
0.000 20
[27] array · 9 items
[0]
Resveratrol
[1]
9
[2]
−0.684
[3]
0.000 04
[4]
[5]
Prochlorperazine
[6]
16
[7]
−0.434
[8]
0.002 99
[28] array · 9 items
[0]
Medrysone
[1]
6
[2]
−0.680
[3]
0.002 92
[4]
[5]
LY-294002
[6]
61
[7]
−0.428
[8]
0.000 00
[29] array · 9 items
[0]
Bepridil
[1]
4
[2]
−0.674
[3]
0.025 22
[4]
[5]
Trichostatin A
[6]
182
[7]
−0.425
[8]
0.000 00
[30] array · 9 items
[0]
Pyrvinium
[1]
6
[2]
−0.672
[3]
0.003 34
[4]
[5]
Fluphenazine
[6]
18
[7]
−0.406
[8]
0.003 80
[31] array · 9 items
[0]
Nortriptyline
[1]
4
[2]
−0.669
[3]
0.027 07
[4]
[5]
Thioridazine
[6]
20
[7]
−0.388
[8]
0.003 27
[32] array · 9 items
[0]
Apigenin
[1]
4
[2]
−0.667
[3]
0.027 65
[4]
[5]
Alpha-estradiol
[6]
16
[7]
−0.357
[8]
0.025 35
[33] array · 9 items
[0]
Methylergometrine
[1]
4
[2]
−0.664
[3]
0.028 71
[4]
[5]
Geldanamycin
[6]
15
[7]
−0.349
[8]
0.039 26
[34] array · 9 items
[0]
Bufexamac
[1]
4
[2]
−0.660
[3]
0.030 10
[4]
[5]
Sirolimus
[6]
44
[7]
−0.335
[8]
0.000 08
[35] array · 9 items
[0]
Prestwick-1084
[1]
4
[2]
−0.656
[3]
0.032 41
[4]
[5]
Chlorpromazine
[6]
19
[7]
−0.329
[8]
0.024 17
[36] array · 9 items
[0]
Deptropine
[1]
4
[2]
−0.651
[3]
0.034 95
[4]
[5]
Wortmannin
[6]
18
[7]
−0.314
[8]
0.046 91
[37] array · 9 items
[0]
Dextromethorphan
[1]
4
[2]
−0.647
[3]
0.036 86
[4]
[5]
Tanespimycin
[6]
62
[7]
−0.311
[8]
0.000 00
[38] array · 9 items
[0]
Protriptyline
[1]
4
[2]
−0.646
[3]
0.037 36
[4]
[5]
Fulvestrant
[6]
40
[7]
−0.225
[8]
0.029 99
locator
section[14]/table-wrap[1]#Table2
gaps array · 8 items
[0]
asset:data:geo:GSE113513 not downloaded
[1]
asset:data:geo:GSE113513 licence not read
[2]
asset:data:geo:GSE21510 not downloaded
[3]
asset:data:geo:GSE21510 licence not read
[4]
asset:data:geo:GSE32323 not downloaded
[5]
asset:data:geo:GSE32323 licence not read
[6]
asset:data:geo:GSE44076 not downloaded
[7]
asset:data:geo:GSE44076 licence not read
analysis object · 4 fields
state
partial
methods array · 2 items
[0] object · 10 fields
id
method-1
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
[1] object · 10 fields
id
method-2
family
null
specific
null
label
NCBI-GEO2R online tool
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
To identify the DEGs, we used the NCBI-GEO2R online tool to analyze these datasets. Subsequently, adjusted P-value <0.05 and |log 2(fold change)| >1 were set as the cutoff criteria to screen the significant DEGs of each dataset. Finally, Venn diagrams were performed to get the overlap significant DEGs of the 4 datasets.
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 4 items
[0]
GSE113513
[1]
GSE21510
[2]
GSE44076
[3]
GSE32323
resolved_accessions array · 4 items
[0]
GSE113513
[1]
GSE21510
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GSE44076
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GSE32323
statements array · 1 item
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A total of 4 GEO datasets were selected, including GSE113513, GSE21510, GSE44076, and GSE32323.
basis
The paper names GSE113513, GSE21510, GSE44076, GSE32323 in NCBI Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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GEO GSE113513
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asset:data:geo:GSE113513 licence not read
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asset:data:geo:GSE32323 licence not read
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ognosis of CRC patients. In this study, mRNA microarray datasets GSE113513, GSE21510, GSE44076, and
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Complete file
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In this study, mRNA microarray datasets GSE113513, GSE21510, GSE44076, and GSE32323 were obtained from the Gene Expression Omnibus (GEO) and analyzed with bioinformatics to identify hub genes in CRC development. Differentially expressed genes (DEGs) were analyzed using the GEO2R tool. Gene ontology (GO) and KEGG analyses were performed through the DAVID database. STRING database and Cytoscape software were used to construct a protein-protein interaction (PPI) network and identify key modules and hub genes. Survival analyses of the DEGs were performed on GEPIA database. The Connectivity Map database was used to screen potential drugs. A total of 865 DEGs were identified, including 374 upregulated and 491 downregulated genes. These DEGs were mainly associated with metabolic pathways, pathways in cancer, cell cycle and so on. The PPI network was identified with 863 nodes and 5817 edges. Survival analysis revealed that HMMR, PAICS, ETFDH, and SCG2 were significantly associated with overall survival of CRC patients. And blebbistatin and sulconazole were identified as candidate drugs. In conclusion, our study found four hub genes involved in CRC, which may provide novel potential biomarkers for CRC prognosis, and two potential candidate drugs for CRC.", "claims": [{"id": "claim-method", "statement": "To identify the DEGs, we used the NCBI-GEO2R online tool to analyze these datasets. Subsequently, adjusted P-value <0.05 and |log 2(fold change)| >1 were set as the cutoff criteria to screen the significant DEGs of each dataset. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE113513"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE113513"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33361643", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7555/JBR.34.20200021", "sha256": 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