← All .science files
pmid:40672380
Disulfidptosis-related gene in acute myocardial infarction and its diagnostic value and functions based on bioinformatics analysis and machine learning.
Liwen Chen · Jinru Wei · Guoxiong Deng · Guien Xu
Frontiers in cardiovascular medicine · 2025 doi:10.3389/fcvm.2025.1513342
Paper
complete
Experiment
complete
Data
partial
Analysis
complete
Execution
absent
Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
paper object · 10 fields
authors array · 4 items
claims array · 3 items
[0] object · 6 fields
[1] object · 6 fields
[2] object · 6 fields
evidence array · 2 items
[0] object · 3 fields
[1] object · 3 fields
gaps array · 0 items
experiment object · 8 fields
steps array · 3 items
[0] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
assets array · 4 items
[0] object · 15 fields
structure object · 4 fields
[1] object · 15 fields
structure object · 15 fields
sample_accessions array · 5 items
[2] object · 15 fields
structure object · 15 fields
sample_accessions array · 33 items
[3] object · 15 fields
structure object · 15 fields
sample_accessions array · 24 items
gaps array · 6 items
analysis object · 4 fields
methods array · 5 items
[0] object · 10 fields
dsl_operations array · 3 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[1] object · 10 fields
dsl_operations array · 0 items
missing_operations array · 1 item
parameters object · 0 fields
data_shapes array · 1 item
[2] object · 10 fields
dsl_operations array · 3 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[3] object · 10 fields
dsl_operations array · 3 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[4] object · 10 fields
dsl_operations array · 1 item
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
requirements array · 1 item
[0] object · 6 fields
assay_families array · 9 items
gaps array · 0 items
readiness object · 8 fields
axes object · 3 fields
method object · 5 fields
required_operations array · 3 items
missing_operations array · 0 items
capability object · 4 fields
data object · 6 fields
accessions array · 3 items
resolved_accessions array · 3 items
statements array · 1 item
can_run object · 3 fields
dsl_operations array · 3 items
assets array · 2 items
steps array · 1 item
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
gaps array · 0 items
review object · 5 fields
machine_critique object · 5 fields
reader object · 5 fields
evidence_check object · 2 fields
usage object · 3 fields
stages array · 1 item
[0] object · 4 fields
gaps array · 3 items
provenance object · 7 fields
entities array · 3 items
activities array · 3 items
[0] object · 4 fields
used array · 3 items
[0] object · 3 fields
[1] object · 3 fields
[2] object · 3 fields
[1] object · 4 fields
agents array · 2 items
lineage object · 4 fields
gaps array · 10 items
assays array · 3 items
[0] object · 11 fields
required_operations array · 0 items
source_hashes object · 1 field
evidence array · 1 item
[1] object · 11 fields
required_operations array · 0 items
source_hashes object · 1 field
evidence array · 1 item
[2] object · 11 fields
required_operations array · 3 items
source_hashes object · 1 field
evidence array · 1 item
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40672380", "kind": "science-record", "revision": 4, "content_hash": "sha256:166616183b15259555724395f3569dbf48613f27b38b2e5563bace3f9a51021d", "created_at": "2026-11-01T20:30:46Z", "updated_at": "2026-11-01T22:56:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Disulfidptosis-related gene in acute myocardial infarction and its diagnostic value and functions based on bioinformatics analysis and machine learning.", "doi": "10.3389/fcvm.2025.1513342", "pmid": "40672380", "authors": ["Liwen Chen", "Jinru Wei", "Guoxiong Deng", "Guien Xu"], "journal": "Frontiers in cardiovascular medicine", "year": 2025, "abstract": "Background: Acute myocardial infarction (AMI) is a major cause of morbidity and mortality. Disulfidptosis, a novel form of programmed cell death, has been largely unexplored in AMI. This study aims to identify disulfidptosis-related genes in AMI and assess their diagnostic potential using bioinformatics and machine learning.\nMethods: The microarray datasets GSE60993 and GSE61144, associated with Acute Myocardial Infarction (AMI), were obtained from the Gene Expression Omnibus (GEO) database. Differential disulfidptosis-associated genes were identified via differential expression analysis. The disulfidptosis related genes were collected from FerrDb V2 and the differentially expressed disulfidptosis related genes were utilized to construct a Protein-Protein Interaction (PPI) network. Key genes were identified utilizing a Protein-Protein Interaction (PPI) network and plugins available in Cytoscape. The key genes were used to detect potential biomarkers by receiver operating characteristic (ROC) analysis.Next, GO and KEGG analyses, as well as correlation analysis were performed on the key genes, and potential drug molecules targeting these genes were also analyzed. At the same time, key genes further screened by Support Vector Machine (SVM), Lasso regression, as well as random forest. By intersecting the results of the three, we ended up with hub genes for AMI. The expression of these key genes was verified using external dataset GSE61144.\nResults: A total of 16 differentially expressed disulfidptosis related genes were identified and these genes were mainly enriched in the pathways of \"regulation of actin cytoskeleton organization\", \"regulation of actin filament-based process\", \"regulation of actin filament organization\", \"cell cortex\", \"cell leading edge\", \"cadherin binding\", \"actin filament bindin, and \"D-glucose transmembrane transporter activity\". The top 10 hub genes ACTB, RAC1, IQGAP1, FLNB, MYL6, ABI2, DBN1, PRDX1, SLC2A1 and SLC2A3 were identified from the PPI network. Further screening using Support Vector Machine (SVM), Lasso regression and random forest, and intersecting the results of these analyses, led to the identification of DBN1, RAC1, and SLC2A3 as final hub genes in AMI. While the final key genes DBN1 and SLC2A3 were significantly differentially expressed in external dataset GSE61144 with AUC ≥ 0.7.\nConclusion: In this study, we identified differentially expressed disulfidptosis related genes in blood samples from AMI patients using existing datasets. The research delved into the expression patterns and molecular mechanisms of differentially expressed disulfidptosis related genes in AMI, offering a foundation for precise AMI diagnosis and the identification of novel therapeutic targets.", "claims": [{"id": "claim-method", "statement": "Differential gene analysis was conducted utilizing the R package “limma” (37).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40672380", "locator": "sections[4] \"Identification of genes with differential expression related to acute myocardial infarction and disulfidptosis\" paragraph 2", "quote": "Differential gene analysis was conducted utilizing the R package “limma” (37)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40672380", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified DBN1 and SLC2A3 as final disulfidptosis-associated hub genes for acute myocardial infarction, with the two-gene nomogram achieving AUC values of 0.916 in GSE60993 and 0.864 in GSE61144.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40672380", "locator": "sections[15] \"Machine learning-based identification of a disulfidptosis signature\" paragraph 2", "quote": "This analysis led to the identification of 2 disulfidptosis-associated feature genes as hub genes: DBN1 and SLC2A3."}, {"asset": "source:pmid:40672380", "locator": "sections[15] \"Machine learning-based identification of a disulfidptosis signature\" paragraph 2", "quote": "The AUC values of the ROC curves for the diagnostic performance of this nomogram in the GSE60993 and GSE61144 datasets were 0.916 and 0.864, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified DBN1 and SLC2A3 as final disulfidptosis-associated hub genes for acute myocardial infarction, with the two-gene nomogram achieving AUC values of 0.916 in GSE60993 and 0.864 in GSE61144.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40672380"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE163956"], "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:GSE163956"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40672380", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcvm.2025.1513342", "sha256": "sha256:f30c6b5ac8ae9a2e8cf3260a3e625212e18e8d06ba97260cecb82ab03b6450aa", "bytes": 60134, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcvm.2025.1513342", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12263613", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE163956", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163956", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE163956", "version": null, "note": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4991229", "GSM4991230", "GSM4991231", "GSM4991232", "GSM5795879"], "sample_count": 5, "group_sizes": null, "group_sizes_basis": null, "platform": "21103", "taxon": "Mus musculus", "title": "Single-cell RNA sequencing analysis of mouse cardiac tissues with myocardial infarction", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE60993", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60993", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE60993", "version": null, "note": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1495313", "GSM1495314", "GSM1495315", "GSM1495316", "GSM1495317", "GSM1495318", "GSM1495319", "GSM1495320", "GSM1495321", "GSM1495322", "GSM1495323", "GSM1495324", "GSM1495325", "GSM1495326", "GSM1495327", "GSM1495328", "GSM1495329", "GSM1495330", "GSM1495331", "GSM1495332", "GSM1495333", "GSM1495334", "GSM1495335", "GSM1495336", "GSM1495337", "GSM1495338", "GSM1495339", "GSM1495340", "GSM1495341", "GSM1495342", "GSM1495343", "GSM1495344", "GSM1495345"], "sample_count": 33, "group_sizes": null, "group_sizes_basis": null, "platform": "6884", "taxon": "Homo sapiens", "title": "Assessment and Diagnostic Relevance of Novel Serum Biomarkers for Early Decision of ST-elevation Myocardial Infarction", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE61144", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61144", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE61144", "version": null, "note": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1498369", "GSM1498370", "GSM1498371", "GSM1498372", "GSM1498373", "GSM1498374", "GSM1498375", "GSM1498376", "GSM1498377", "GSM1498378", "GSM1498379", "GSM1498380", "GSM1498381", "GSM1498382", "GSM1498383", "GSM1498384", "GSM1498385", "GSM1498386", "GSM1498387", "GSM1498388", "GSM1498389", "GSM1498390", "GSM1498391", "GSM1498392"], "sample_count": 24, "group_sizes": null, "group_sizes_basis": null, "platform": "6106", "taxon": "Homo sapiens", "title": "Expression data from blood samples of STEMI and Same STEMI patients after PIC", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE163956 not downloaded", "asset:data:geo:GSE163956 licence not read", "asset:data:geo:GSE60993 not downloaded", "asset:data:geo:GSE60993 licence not read", "asset:data:geo:GSE61144 not downloaded", "asset:data:geo:GSE61144 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Differential gene analysis was conducted utilizing the R package “limma” (37)."}}, {"id": "method-2", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-3", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "Support Vector Machine"}}, {"id": "method-4", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "Protein-Protein Interaction"}}, {"id": "method-5", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "pathway enrichment"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"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": {"tier": "R1", "reachable": true, "accessions": ["GSE60993", "GSE61144", "GSE163956"], "resolved_accessions": ["GSE60993", "GSE61144", "GSE163956"], "statements": ["Our study utilized the following publicly available datasets from the Gene Expression Omnibus (GEO) database related to acute myocardial infarction: GSE60993, GSE61144, GSE163956."], "basis": "The paper names GSE60993, GSE61144, GSE163956 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:40672380", "data:geo:GSE163956"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE163956"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:57:05Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 16149, "completion_tokens": 1304, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:40672380", "type": "paper", "label": "pmid:40672380"}, {"id": "source:pmid:40672380", "type": "manuscript", "label": "PMID 40672380 full text"}, {"id": "data:geo:GSE163956", "type": "dataset", "label": "GEO GSE163956"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:40672380", "type": "paper", "label": "pmid:40672380"}, {"id": "source:pmid:40672380", "type": "manuscript", "label": "PMID 40672380 full text"}, {"id": "data:geo:GSE163956", "type": "dataset", "label": "GEO GSE163956"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-40672380", "type": "extraction", "used": ["source:pmid:40672380"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE163956", "type": "accession_resolution", "used": ["data:geo:GSE163956"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:40672380", "parent_hash": "sha256:d679492720d66c5acc1ef347de5bd87e7a37471dc2d504eaaabd13869786f9bf", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE163956 licence not read", "asset:data:geo:GSE163956 not downloaded", "asset:data:geo:GSE60993 licence not read", "asset:data:geo:GSE60993 not downloaded", "asset:data:geo:GSE61144 licence not read", "asset:data:geo:GSE61144 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["formatics and machine learning. Methods: The microarray datasets GSE60993 and GSE61144, associated w"], "order_basis": "paper_text_order:448", "id": "assay:1"}, {"role": "data_generation", "definition_id": "clinical_cohort", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["ly expressed disulfidptosis related genes in blood samples from AMI patients using existing datasets. The re"], "order_basis": "paper_text_order:2563", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Differential gene analysis was conducted utilizing the R package “limma” (37)."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}