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315 results for “regulons”
Dataset supporting the paper "Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities"
<p>Datasets involved in the construction and benchmarking of the CollecTRI-derived regulons as presented in the paper "Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities".</p>
Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs
<p>This repository contains the raw and processed files used in Minaeva et al. 2024.</p> <p>In this version, we have revised the regulon construction pipeline and expanded the dataset to cover 40 common cell lines.</p> <p>The code used to generate these files is available at <a href="https://github.com/LappalainenLab/chip_seq_regulons" target="_new" rel="noreferrer">GitHub - LappalainenLab/chip_seq_regulons</a>.</p> <p>The descriptions of the files contained within each subdirectory are as follows:</p> <h3>1-dataset_stats</h3> <ul> <li><code>per_gene_stats_{approach}_{cell_line}.tsv</code>: Number of TFs regulating a gene according to the respective approach (S2Mb, M2Kb, or S2Kb) in a given cell line.</li> <li><code>per_tf_stats_{approach}_{cell_line}.tsv</code>: Number of target genes regulated by a TF according to the respective approach (S2Mb, M2Kb, or S2Kb) in a given cell line.</li> </ul> <h3>1-network_enrichment</h3> <ul> <li><code>enrich_scores_remap_all_tfs_K562.tsv</code>: Results of fitting logistic regression for testing the enrichment of the K562 regulon in other biological networks (PPI, coexpression, experimental trans-networks).</li> </ul> <h3>2-plot_decoupler_comparison_benchmark_across_cells</h3> <ul> <li><code>{cell_line}_comparison_benchmark.tsv</code>: Results of benchmarking S2Mb, M2Kb, CollecTri, Dorothea, ChIP-Atlas, RegNet, and TRRUST regulons using the decoupler package and the KnockTF database. Cell lines considered are K562, HepG2, and MCF7 (see Methods for benchmarking pipeline details).</li> </ul> <h3>2-plot_decoupler_filter_benchmark_across_methods</h3> <ul> <li><code>{cell_line}_filtering_benchmark.tsv</code>: Results of benchmarking S2Mb, M2Kb, and S2Kb regulons with different filters applied using the decoupler package and the KnockTF database. Cell lines considered are K562, HepG2, and MCF7 (see Methods for benchmarking pipeline details).</li> </ul> <h3>3-tf_activity</h3> <ul> <li><code>aml_k562_activity_{regulon}_sc.tsv</code>: Results of TF activity analysis based on a respective regulon between healthy hematopoietic stem cells (HSCs) and abnormal AML progenitor cells following the decoupler pipeline. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>aml_activity_estimates_hsc_sc.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between healthy HSCs and abnormal AML progenitor cells across regulons.</li> <li><code>aml_dhsc_ahsc_activity_{regulon}_sc.tsv</code>: Results of TF activity analysis based on a respective regulon between leukemic activated and dormant HSCs following the decoupler pipeline. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>aml_activity_estimates_dhsc_ahsc_sc.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between leukemic activated and dormant HSCs across regulons.</li> <li><code>bc_bas_activity_{regulon}.tsv</code>: Results of TF activity analysis based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from basal breast cancer following the decoupler pipeline. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_activity_estimates_bas.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between healthy epithelial breast cells and malignant epithelial cells from basal breast cancer across regulons.</li> <li><code>bc_lum_activity_{regulon}.tsv</code>: Results of TF activity analysis based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from luminal type A breast cancer following the decoupler pipeline. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_activity_estimates_lum.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between healthy epithelial breast cells and malignant epithelial cells from luminal type A breast cancer across regulons.</li> <li><code>hep_activity_{regulon}.tsv</code>: Results of TF activity analysis based on a respective regulon between neoplastic and healthy liver cells following the decoupler pipeline. Regulons considered are HepG2-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>hep_activity_estimates.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between neoplastic and healthy liver cells across regulons.</li> </ul> <h3>3-tf_disease_enrichment</h3> <ul> <li><code>aml_{database}_enrich_{regulon}_hsc_sc.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between healthy HSCs and abnormal AML progenitor cells following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, OMIM, and KEGG. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>aml_{database}_enrich_{regulon}_dhsc_ahsc_sc.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between leukemic activated and dormant HSCs following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, OMIM, and KEGG. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_{database}_enrich_{regulon}_bas.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from basal breast cancer following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, and OMIM. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_{database}_enrich_{regulon}_lum.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from luminal type A breast cancer following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, and OMIM. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>hep_{database}_enrich_{regulon}.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between neoplastic and healthy liver cells following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, OMIM, and KEGG. Regulons considered are HepG2-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> </ul> <h3>regulons</h3> <ul> <li><code>{cell_line}_regulon.tsv</code>: S2Mb, M2Kb, and S2Kb regulons generated in this study with all acquired annotations (see Methods for details).</li> </ul> <p>External regulons used for comparison. Cell lines considered are K562, HepG2, MCF7, and GM12878:</p> <ul> <li><code>ChIP-Atlas_target_genes_{cell_line}.tsv</code>: Customized ChIP-Atlas regulons (see Methods for details).</li> <li><code>Revised_Supplemental_Table_S3_Normal.csv</code>: Dorothea regulon collected from supplementary materials of Garcia-Alonso et al. (2019).</li> </ul> <h3>s3-network_enrichment</h3> <ul> <li><code>enrich_scores_remap_all_tfs_{cell_line}.tsv</code>: Results of fitting logistic regression for testing the enrichment of cell-line-specific regulons in PPI networks (see Methods and corresponding GitHub repository for details). Cell lines considered are K562, HepG2, MCF7, and GM12878.</li> </ul> <p> </p>
Supplemental Dataset Excel files and Source Data Excel file for "START domains generate paralog-specific regulons from a single network architecture"
<p>Supplemental Dataset Excel files and Source Data Excel file for "START domains generate paralog-specific regulons from a single network architecture" in Nat Comms</p>
Underlying data of DoRothEA's regulons
<p>This repository contains the raw data that were used to construct DoRothEA's regulons. Details of the raw data are described in <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6673718/">Garcia-Alonso et al. 2019</a>.</p>
Comparative Genomic Analysis of PhoP Regulon in S. Typhi and S. Typhimurium
GEO Series GSE17670. Salmonella enterica subsp. enterica serovar Typhimurium str. LT2; Salmonella enterica subsp. enterica serovar Typhi str. CT18; Salmonella enterica subsp. enterica serovar Typhi str. Ty2. 12 samples. Type: Expression profiling by array.
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280344. Zea mays. 57 samples. Type: Expression profiling by high throughput sequencing.
RNA-Seq analysis reveals a six-gene SoxR regulon in Streptomyces coelicolor
GEO Series GSE57268. Streptomyces coelicolor. 6 samples. Type: Expression profiling by high throughput sequencing.
Analysis of ChIP-Seq data identifies BfmR and CzcR regulons
GEO Series GSE154293. Pseudomonas aeruginosa. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Undomesticated Bacillus subtilis RemA regulon
GEO Series GSE47409. Bacillus subtilis. 3 samples. Type: Expression profiling by array.
Analysis of the iron stimulon and fur regulon of Geobacter sulfurreducens
GEO Series GSE54306. Geobacter sulfurreducens PCA. 16 samples. Type: Expression profiling by genome tiling array; Genome binding/occupancy profiling by genome tiling array.
Tailoring a global iron regulon to a uropathogen
GEO Series GSE145424. Escherichia coli CFT073. 19 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
PhyK, PhyR, σT and σU regulons
GEO Series GSE26977. Caulobacter vibrioides NA1000; Caulobacter vibrioides CB15. 15 samples. Type: Expression profiling by array.
The QstR regulon of Vibrio cholerae
GEO Series GSE114592. Vibrio cholerae. 24 samples. Type: Expression profiling by high throughput sequencing.
The histone-like protein AlgP regulon is distinct in nonmucoid and mucoid Pseudomonas aeruginosa and does not include alginate biosynthesis genes
GEO Series GSE148593. Pseudomonas aeruginosa. 8 samples. Type: Expression profiling by high throughput sequencing.
Determination of the VanS regulon in Clostridioides difficile
GEO Series GSE212197. Clostridioides difficile 630. 6 samples. Type: Expression profiling by high throughput sequencing.
The MisR regulon in Neisseria gonorrhoeae strain FA19
GEO Series GSE50184. Neisseria gonorrhoeae. 6 samples. Type: Expression profiling by high throughput sequencing.
The androgen receptor regulates a druggable translational regulon in advanced prostate cancer [ribosome profiling]
GEO Series GSE116082. Mus musculus. 10 samples. Type: Other.
SigB modulates expression of novel SigB regulon members via Bc1009 in non-stressed and heat-stressed cells revealing its alternative roles in Bacillus cereus
GEO Series GSE213958. Bacillus cereus ATCC 14579. 16 samples. Type: Expression profiling by array.
PqsE expands and differentially modulates the RhlR quorum sensing regulon in Pseudomonas aeruginosa
GEO Series GSE200835. Pseudomonas aeruginosa. 12 samples. Type: Expression profiling by high throughput sequencing.
The PerA regulon in Enterococcus faecalis
GEO Series GSE31538. Escherichia coli CFT073; Enterococcus faecalis V583; Escherichia coli O157:H7 str. Sakai; Enterococcus faecalis; Bacillus anthracis; Escherichia coli str. K-12 substr. MG1655; Escherichia coli O157:H7 str. EDL933; Bacteroides thetaiotaomicron VPI-5482; Salmonella enterica subsp. enterica serovar Typhimurium str. LT2. 12 samples. Type: Expression profiling by array.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.