Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38137330", "kind": "science-record", "revision": 4, "content_hash": "sha256:bde417344ea29d28d3fa26bcf1b85bb1b8d1eafe8f623495f499df67eb961180", "created_at": "2026-11-01T19:20:04Z", "updated_at": "2026-11-01T22:53:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis.", "doi": "10.3390/biomedicines11123109", "pmid": "38137330", "authors": ["Muttanagouda Giriyappagoudar", "Basavaraj Vastrad", "Rajeshwari Horakeri", "Chanabasayya Vastrad"], "journal": "Biomedicines", "year": 2023, "abstract": "Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.", "claims": [{"id": "claim-method", "statement": "The DESeq2 package [36] of R language was utilized to screen DEGs. The false discovery rate (FDR) of the Benjamini–Hochberg (BH) method was applied to adjust p-values for multiple comparisons [37].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38137330", "locator": "sections[4] \"2.2. Identification of DEGs\" paragraph 2", "quote": "The DESeq2 package [36] of R language was utilized to screen DEGs. The false discovery rate (FDR) of the Benjamini–Hochberg (BH) method was applied to adjust p-values for multiple comparisons [37]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets supporting the conclusions of this article are available in the GEO (Gene Expression Omnibus) (https://www.ncbi.nlm.nih.gov/geo/, accessed on 1 November 2023) repository. [(GSE213001) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE213001, accessed on 1 November 2023].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38137330", "locator": "sections[24] \"Data Availability Statement\" paragraph 2", "quote": "The datasets supporting the conclusions of this article are available in the GEO (Gene Expression Omnibus) (https://www.ncbi.nlm.nih.gov/geo/, accessed on 1 November 2023) repository. [(GSE213001) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE213001, accessed on 1 November 2023]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 958 differentially expressed genes between IPF and normal control samples, including 479 upregulated and 479 downregulated genes.", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "The NGS dataset GSE213001 was downloaded from the GEO database, and total of 958 DEGs were screened between IPF and normal control groups with |logFC| > 0.512 for up regulated genes, |logFC| < −0.831 for down regulated genes and adjusted p < 0.05, including 479 up regulated DEGs and 479 down regulated DEGs (Supplementary Table S1 and Figure 2)."}, "evidence": [{"asset": "source:pmid:38137330", "locator": "sections[12] \"3.1. Identification of DEGs\" paragraph 2", "quote": "The NGS dataset GSE213001 was downloaded from the GEO database, and total of 958 DEGs were screened between IPF and normal control groups with |logFC| > 0.512 for up regulated genes, |logFC| < −0.831 for down regulated genes and adjusted p < 0.05, including 479 up regulated DEGs and 479 down regulated DEGs (Supplementary Table S1 and Figure 2)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 958 differentially expressed genes between IPF and normal control samples, including 479 upregulated and 479 downregulated genes.", "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:38137330"], "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:GSE213001"], "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": {"fdr_threshold": "with Benjamini–Hochberg false discovery rate adjustment"}, "inputs": ["data:geo:GSE213001"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38137330", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/biomedicines11123109", "sha256": "sha256:6942ee3ad5bc7563cc3a1b5aee58587fe56ad11837a4e802b9eeca88e1a3818e", "bytes": 276380, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3390/biomedicines11123109", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10740779", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE213001", "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=GSE213001", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE213001", "version": null, "note": "The datasets supporting the conclusions of this article are available in the GEO (Gene Expression Omnibus) (https://www.ncbi.nlm.nih.gov/geo/, accessed on 1 November 2023) repository. [(GSE213001) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE213001, accessed on 1 November 2023].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets supporting the conclusions of this article are available in the GEO (Gene Expression Omnibus) (https://www.ncbi.nlm.nih.gov/geo/, accessed on 1 November 2023) repository. [(GSE213001) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE213001, accessed on 1 November 2023].", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM6568317", "GSM6568318", "GSM6568319", "GSM6568320", "GSM6568321", "GSM6568322", "GSM6568323", "GSM6568324", "GSM6568325", "GSM6568326", "GSM6568327", "GSM6568328", "GSM6568329", "GSM6568330", "GSM6568331", "GSM6568332", "GSM6568333", "GSM6568334", "GSM6568335", "GSM6568336", "GSM6568337", "GSM6568338", "GSM6568339", "GSM6568340", "GSM6568341", "GSM6568342", "GSM6568343", "GSM6568344", "GSM6568345", "GSM6568346", "GSM6568347", "GSM6568348", "GSM6568349", "GSM6568350", "GSM6568351", "GSM6568352", "GSM6568353", "GSM6568354", "GSM6568355", "GSM6568356", "GSM6568357", "GSM6568358", "GSM6568359", "GSM6568360", "GSM6568361", "GSM6568362", "GSM6568363", "GSM6568364", "GSM6568365", "GSM6568366", "GSM6568367", "GSM6568368", "GSM6568369", "GSM6568370", "GSM6568371", "GSM6568372", "GSM6568373", "GSM6568374", "GSM6568375", "GSM6568376", "GSM6568377", "GSM6568378", "GSM6568379", "GSM6568380", "GSM6568381", "GSM6568382", "GSM6568383", "GSM6568384", "GSM6568385", "GSM6568386", "GSM6568387", "GSM6568388", "GSM6568389", "GSM6568390", "GSM6568391", "GSM6568392", "GSM6568393", "GSM6568394", "GSM6568395", "GSM6568396", "GSM6568397", "GSM6568398", "GSM6568399", "GSM6568400", "GSM6568401", "GSM6568402", "GSM6568403", "GSM6568404", "GSM6568405", "GSM6568406", "GSM6568407", "GSM6568408", "GSM6568409", "GSM6568410", "GSM6568411", "GSM6568412", "GSM6568413", "GSM6568414", "GSM6568415", "GSM6568416", "GSM6568417", "GSM6568418", "GSM6568419", "GSM6568420", "GSM6568421", "GSM6568422", "GSM6568423", "GSM6568424", "GSM6568425", "GSM6568426", "GSM6568427", "GSM6568428", "GSM6568429", "GSM6568430", "GSM6568431", "GSM6568432", "GSM6568433", "GSM6568434", "GSM6568435", "GSM6568436", "GSM6568437", "GSM6568438", "GSM6568439", "GSM6568440", "GSM6568441", "GSM6568442", "GSM6568443", "GSM6568444", "GSM6568445", "GSM6568446", "GSM6568447", "GSM6568448", "GSM6568449", "GSM6568450", "GSM6568451", "GSM6568452", "GSM6568453", "GSM6568454", "GSM6568455"], "sample_count": 139, "group_sizes": null, "group_sizes_basis": null, "platform": "21290", "taxon": "Homo sapiens", "title": "Bulk tissue RNA sequencing from human donors with and without lung fibrosis", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE213001 not downloaded", "asset:data:geo:GSE213001 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "deseq2", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {"fdr_threshold": "with Benjamini–Hochberg false discovery rate adjustment"}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The DESeq2 package [36] of R language was utilized to screen DEGs. The false discovery rate (FDR) of the Benjamini–Hochberg (BH) method was applied to adjust p-values for multiple comparisons [37]."}}, {"id": "method-2", "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-3", "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": 0.7, "band": "medium", "quote": "pathway enrichment"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 0.05, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold."}], "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: deseq2."}, "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": ["GSE213001"], "resolved_accessions": ["GSE213001"], "statements": ["The datasets supporting the conclusions of this article are available in the GEO (Gene Expression Omnibus) (https://www.ncbi.nlm.nih.gov/geo/, accessed on 1 November 2023) repository. [(GSE213001) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE213001, accessed on 1 November 2023]."], "basis": "The paper names GSE213001 in GEO (Gene Expression Omnibus) 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:38137330", "data:geo:GSE213001"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE213001"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:03:30Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 91597, "completion_tokens": 1952, "cached_tokens": 264}}, "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:38137330", "type": "paper", "label": "pmid:38137330"}, {"id": "source:pmid:38137330", "type": "manuscript", "label": "PMID 38137330 full text"}, {"id": "data:geo:GSE213001", "type": "dataset", "label": "GEO GSE213001"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38137330", "type": "paper", "label": "pmid:38137330"}, {"id": "source:pmid:38137330", "type": "manuscript", "label": "PMID 38137330 full text"}, {"id": "data:geo:GSE213001", "type": "dataset", "label": "GEO GSE213001"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38137330", "type": "extraction", "used": ["source:pmid:38137330"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE213001", "type": "accession_resolution", "used": ["data:geo:GSE213001"], "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:38137330", "parent_hash": "sha256:840b8440a546423d6b1f514428a26063e3d5ee3db4b41bc4d90e00905b822c97", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE213001 licence not read", "asset:data:geo:GSE213001 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "amplicon_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["hic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis.", "and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Exp"], "order_basis": "paper_text_order:60", "id": "assay:1"}, {"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": ["The DESeq2 package [36] of R language was utilized to screen DEGs. The false discovery rate (FDR) of the Benjamini–Hochberg (BH) method was applied to adjust p-values for multiple comparisons [37]."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}