hEGCLC paper

Html versions of scripts available in the GitHub repository EGCLC_paper_release.

00_ExplorationQC_DimRed_Clustering.ipynb

First exploration, quality check, dimensionality reduction and clustering of the scRNA-Seq data.

01a_CellsAnnotationMarkers.ipynb

Exploration of known markers across clusters of the scRNA-Seq data and cell types annotation.

01b_FunctionalEnrichment_Clusters.ipynb

Functional enrichment of the markers of the Leiden clusters.

01c_CellCycle.ipynb

Analysis of cell cycle phases of the cells in the scRNA-Seq data.

02a_PseudoBulk_PCA.ipynb

Generation of pseudobulk from annotated scRNA-Seq and PCA analysis.

02b_Pseudobulk_edgeR_topGO_hEGCLC_hPGCLC.ipynb

Differential expression analysis and functional enrichment of DEGs from pseudobulks of hPGCLC and hEGCLC.

02b_Pseudobulk_edgeR_topGO_hiPSC_hEGCLC.ipynb

Differential expression analysis and functional enrichment of DEGs from pseudobulks of hiPSC and hEGCLC.

02b_Pseudobulk_edgeR_topGO_hiPSC_hPGCLC.ipynb

Differential expression analysis and functional enrichment of DEGs from pseudobulks of hPGCLC and hiPSC.

02c_Comparisons_between_DEGs.ipynb

Comparison of DEGs of comparisons hPGCLC-hEGCLC, hiPSC-hEGCLC and hPGCLC-hiPSC.

03a_Chen_Processing_and_Annotation.ipynb

Processing of dataset from Chen et al. (Cell Reports, 2019) and annotation of the cell types.

03b_Ingest_Chen.ipynb

Ingestion of in-house dataset onto Chen dataset.

03c_Fetal_Processing_and_Annotation.ipynb

Processing of dataset from Chen et al. (Cell Reports, 2019) and annotation of the cell types.

03d_Ingest_FetalData.ipynb

Processing of dataset from Guo et al. (Cell Reports, 2019) and annotation of the cell types.

04a_DEGs_patterns_AggClustering.ipynb

Clustering of genes based on the logFC patterns along the hiPSC-iMeLC-hPGCLC-hEGCLC axis.

05_TF_activity_inference.ipynb

Inference of TF activity from scRNA-Seq data using Multivariate Linear Model.

FuncEnrich_LeidenCluster_0

Functional enrichment of Leiden cluster 0 from clustering in notebook 01

FuncEnrich_LeidenCluster_1

Functional enrichment of Leiden cluster 1 from clustering in notebook 01

FuncEnrich_LeidenCluster_2

Functional enrichment of Leiden cluster 2 from clustering in notebook 01

FuncEnrich_LeidenCluster_3

Functional enrichment of Leiden cluster 3 from clustering in notebook 01

FuncEnrich_LeidenCluster_4

Functional enrichment of Leiden cluster 4 from clustering in notebook 01

FuncEnrich_LeidenCluster_5

Functional enrichment of Leiden cluster 5 from clustering in notebook 01

FuncEnrich_LeidenCluster_6

Functional enrichment of Leiden cluster 6 from clustering in notebook 01

FuncEnrich_LeidenCluster_7

Functional enrichment of Leiden cluster 7 from clustering in notebook 01

FuncEnrich_LeidenCluster_8

Functional enrichment of Leiden cluster 8 from clustering in notebook 01

FuncEnrich_LeidenCluster_9

Functional enrichment of Leiden cluster 9 from clustering in notebook 01

FuncEnrich_LeidenCluster_10

Functional enrichment of Leiden cluster 10 from clustering in notebook 01

FuncEnrich_LeidenCluster_11

Functional enrichment of Leiden cluster 11 from clustering in notebook 01

FuncEnrich_LeidenCluster_12

Functional enrichment of Leiden cluster 12 from clustering in notebook 01

FuncEnrich_GenesCluster_0

Functional enrichment of genes in cluster 0 from clustering in notebook 04a

FuncEnrich_GenesCluster_1

Functional enrichment of genes in cluster 1 from clustering in notebook 04a

FuncEnrich_GenesCluster_2

Functional enrichment of genes in cluster 2 from clustering in notebook 04a

FuncEnrich_GenesCluster_3

Functional enrichment of genes in cluster 3 from clustering in notebook 04a

FuncEnrich_GenesCluster_4

Functional enrichment of genes in cluster 4 from clustering in notebook 04a

FuncEnrich_GenesCluster_5

Functional enrichment of genes in cluster 5 from clustering in notebook 04a

FuncEnrich_GenesCluster_6

Functional enrichment of genes in cluster 6 from clustering in notebook 04a

FuncEnrich_GenesCluster_7

Functional enrichment of genes in cluster 7 from clustering in notebook 04a

FuncEnrich_GenesCluster_8

Functional enrichment of genes in cluster 8 from clustering in notebook 04a

FuncEnrich_GenesCluster_9

Functional enrichment of genes in cluster 9 from clustering in notebook 04a

FuncEnrich_GenesCluster_10

Functional enrichment of genes in cluster 10 from clustering in notebook 04a

FuncEnrich_GenesCluster_11

Functional enrichment of genes in cluster 11 from clustering in notebook 04a

FuncEnrich_GenesCluster_12

Functional enrichment of genes in cluster 12 from clustering in notebook 04a

FuncEnrich_GenesCluster_13

Functional enrichment of genes in cluster 13 from clustering in notebook 04a

FuncEnrich_GenesCluster_14

Functional enrichment of genes in cluster 14 from clustering in notebook 04a

06.1_CellOracle.ipynb

06.2_CellOracle.ipynb

06.3_CellOracle.ipynb

06_GRN_DMDE.ipynb

06_GRN_hEGCLC.ipynb

06_GRN_hPGCLC.ipynb

06_GRN_hiPSC.ipynb

06_GRN_iMeLC.ipynb

PreliminaryExploration

Preliminary exploration of DNA methylation profiles.

DMRCalling

Differentially methylated regions (DMRs) identification.

TwistBedAnnotation

Functional and genomic annotation of targeted Twist regions.

DMRAnnotation

Functional and genomic annotation of identified DMRs.

DMRplots

Visualization of DMR methylation patterns across samples.

TopGO_hiPSCs_vs_hPGCLCs_all

GO enrichment analysis for DMR-associated genes in hiPSCs vs hPGCLCs.

TopGO_iMeLCs_vs_hPGCLCs_all

GO enrichment analysis for DMR-associated genes in iMeLCs vs hPGCLCs.

TopGO_hEGCLCs_vs_hiPSCs_all

GO enrichment analysis for DMR-associated genes in hEGCLCs vs hiPSCs.

TopGO_hEGCLCs_vs_hPGCLCs_all

GO enrichment analysis for DMR-associated genes in hEGCLCs vs hPGCLCs.

Heatmaps_imprinted_regions

Heatmap visualization of methylation in imprinted regions.

DMRplots_imprinted_regions

Visualization of methylation patterns in imprinted genomic regions.

1.EscapeeBsseqGeneration_Tang

Generation of bsseq object with measured CpGs within Tang escapee regions.

2.EscapeeAnnotationAndFunctional_Tang

Functional annotation Tang escapee regions and GO of associated genes.

3.EscapeeHeatmaps_Tang

Heatmap visualization of Tang escapee methylation profiles across samples.

4.EscapeesvsNonEscapees_Tang

Comparative analysis between Tang escapee and non-escapee regions methylation profiles.

1.EscapeeBsseqGeneration_Mitinori

Generation of bsseq object with measured CpGs within Mitinori escapee regions.

2.EscapeeAnnotationAndFunctional_Mitinori

Functional annotation Mitinori escapee regions and GO of associated genes.

3.EscapeeHeatmaps_Mitinori

Heatmap visualization of Mitinori escapee methylation profiles across samples.

4.EscapeesvsNonEscapees_Mitinori

Comparative analysis between Mitinori escapee and non-escapee regions methylation profiles.

1.HsuExploration_WGBS

Exploration of Whole-genome bisulfite sequencing (WGBS) data from Hsu datasets.

2.HsuExploration_bACEseq

Exploration of bACE-seq data from Hsu datasets.

3.HsuExploration_WGBSandbACEseq

Generation of bsseq object with WGBS and bACE-seq data from Hsu datasets.

1.EscapeeBsseqGeneration_Hsu_Tang

Generation of bsseq object with Hsu CpGs within Tang escapee regions.

2.EscapeeAnnotationAndFunctional_Hsu_Tang

Functional annotation Tang escapee regions in Hsu dataset and GO of associated genes.

3.EscapeeHeatmaps_Hsu_Tang

Heatmap visualization of methylation patterns in Hsu–Tang escapee regions.

4.EscapeesvsNonEscapees_Hsu_Tang

Comparative analysis between escapee and non-escapee regions in combined Hsu–Tang dataset.

EGCLC_p10_PreliminaryExploration

Preliminary methylation data exploration adding EGCLC passage 10 samples.

EGCLC_p10_DMRCalling

Differentially methylated regions (DMRs) identification adding EGCLC passage 10 samples.

EGCLC_p10_DMRAnnotation

Functional and genomic annotation of identified DMRs adding EGCLC passage 10 samples.

EGCLC_p10_DMRplots

Visualization of DMR methylation patterns across samples including EGCLC passage 10 ones.

EGCLC_p10_Heatmaps_imprinted_regions

Heatmap visualization of methylation in imprinted regions adding EGCLC passage 10 samples.

EGCLC_p10_DMRplots_imprinted_regions

Visualization of methylation patterns in imprinted genomic regions adding EGCLC passage 10 samples.

EGCLC_p10_1.EscapeeBsseqGeneration

Generation of bsseq object with measured CpGs within Tang escapee regions including EGCLC passage 10 samples.

EGCLC_p10_2.EscapeeAnnotationAndFunctional

Functional annotation Tang escapee regions and GO of associated genes (from bsseq object including EGCLC passage 10 samples).

EGCLC_p10_3.EscapeeHeatmaps

Heatmap visualization of Mitinori escapee methylation profiles across samples including EGCLC passage 10 ones.

EGCLC_p10_4.EscapeesvsNonEscapees

Comparative analysis between Tang escapee and non-escapee regions methylation profiles across samples including EGCLC passage 10 ones.