cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26994490.v1
title: Additional file 2 of Unprecedented variation pattern of plastid genomes and the potential role in adaptive evolution in Poales

description: Additional file 2: Figs. S1–S9. Fig. S1. The plastomic configuration of Poales. Numbers represent possible configurations based on the results of assembly software GetOrganelle. Fig. S2. Plastome gene maps of Poales. Genes on the inside and outside of the map are transcribed clockwise and transcribed counterclockwise, respectively. Different color genes represent different function. Fig. S3. Variation of GC content in each family of Poales. The graph displays the trends in GC content, wherein the purple dots indicate the mean value and the black lines connecting them represent GC content variation. Fig. S4. Verification of four species (Anarthria humilis, Isolepis setacea, Xyris capensis and X. capensis var. schoenoides plastomes) by PCR and corresponding readmapping graphs. The IR regions are indicated by black squares and the direction is indicated by a red arrow. The corresponding sequences of validation are denoted with blue border and the names are listed in blue text. Fig. S5. Heatmap of gene and intron content of 93 plastomes in Poales. Different colors represent gene deletions, gene copy number, the number of intron deletions and pseudogenes. The color box on the left represents the in formation of each family and clade of Poales, and the species with red text are incomplete plastomes. The yellow color bar at the bottom of the heatmap represents that these genes are all present in all plastomes of Poales, which have no mutation. Fig. S6. Scatter plot of repeat length for each family of Poales. Fig. S7. The Poales phylogram is based on 80PG-half matrix. Fig. S8. Correlation analysis of repeat number and plastomic size. The shaded area indicates 95% confidence intervals. Fig. S9. A Correlation analysis of repeat number and inversion number. B Correlation analysis of inversion number and arrangement distance. The shaded area indicates 95% confidence intervals.
DOI: 10.6084/m9.figshare.26994493
title: Additional file 3 of Unprecedented variation pattern of plastid genomes and the potential role in adaptive evolution in Poales

description: Additional file 3: 80PG-half matrix.
DOI: 10.6084/m9.figshare.26994493.v1
title: Additional file 3 of Unprecedented variation pattern of plastid genomes and the potential role in adaptive evolution in Poales

description: Additional file 3: 80PG-half matrix.
DOI: 10.6084/m9.figshare.26994496
title: Additional file 4 of Unprecedented variation pattern of plastid genomes and the potential role in adaptive evolution in Poales

description: Additional file 4: 63 single-gene matrices used in select pressure analysis.
DOI: 10.6084/m9.figshare.26994496.v1
title: Additional file 4 of Unprecedented variation pattern of plastid genomes and the potential role in adaptive evolution in Poales

description: Additional file 4: 63 single-gene matrices used in select pressure analysis.
DOI: 10.6084/m9.figshare.26994499
title: Additional file 1 of Inclusion of the severe and enduring anorexia nervosa phenotype in genetics research: a scoping review

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26994499.v1
title: Additional file 1 of Inclusion of the severe and enduring anorexia nervosa phenotype in genetics research: a scoping review

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26994502
title: Additional file 2 of Inclusion of the severe and enduring anorexia nervosa phenotype in genetics research: a scoping review

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26994502.v1
title: Additional file 2 of Inclusion of the severe and enduring anorexia nervosa phenotype in genetics research: a scoping review

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26994535
title: Additional file 4 of Type 2 diabetic mellitus related osteoporosis: focusing on ferroptosis

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26994535.v1
title: Additional file 4 of Type 2 diabetic mellitus related osteoporosis: focusing on ferroptosis

description: Supplementary Material 4
DOI: 10.34740/kaggle/dsv/9367806
title: Top Spotify Songs in 73 Countries (Daily Updated)
DOI: 10.6084/m9.figshare.26994565.v1
title: Additional file 1 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26994565
title: Additional file 1 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26994568
title: Additional file 2 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26994568.v1
title: Additional file 2 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26994571
title: Additional file 3 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26994571.v1
title: Additional file 3 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26994574
title: Additional file 4 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26994574.v1
title: Additional file 4 of Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26994580
title: Additional file 2 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 2: Table S1. Characterization of donors in the study.
DOI: 10.6084/m9.figshare.26994580.v1
title: Additional file 2 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 2: Table S1. Characterization of donors in the study.
DOI: 10.6084/m9.figshare.26994583
title: Additional file 3 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 3: Table S2. Single cell annotation.
DOI: 10.6084/m9.figshare.26994583.v1
title: Additional file 3 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 3: Table S2. Single cell annotation.
DOI: 10.6084/m9.figshare.26994586
title: Additional file 4 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 4: Table S3. Statistical details for trophoblast CytoTRACE analysis.
DOI: 10.6084/m9.figshare.26994589
title: Additional file 5 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 5: Table S4. Differential peaks in bulk ATAC assay.
DOI: 10.6084/m9.figshare.26994589.v1
title: Additional file 5 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 5: Table S4. Differential peaks in bulk ATAC assay.
DOI: 10.6084/m9.figshare.26994586.v1
title: Additional file 4 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 4: Table S3. Statistical details for trophoblast CytoTRACE analysis.
DOI: 10.6084/m9.figshare.26994592
title: Additional file 6 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 6: Table S5. PE specific differential methylation regions.
DOI: 10.6084/m9.figshare.26994595
title: Additional file 7 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 7: Table S6. Differentially expressed genes in trophoblast.
DOI: 10.6084/m9.figshare.26994595.v1
title: Additional file 7 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 7: Table S6. Differentially expressed genes in trophoblast.
DOI: 10.6084/m9.figshare.26994592.v1
title: Additional file 6 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 6: Table S5. PE specific differential methylation regions.
DOI: 10.6084/m9.figshare.26994598
title: Additional file 8 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 8: Table S7. List of cargo genes.
DOI: 10.6084/m9.figshare.26994598.v1
title: Additional file 8 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 8: Table S7. List of cargo genes.
DOI: 10.6084/m9.figshare.26994601
title: Additional file 9 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 9. Table S8. QC metrics for sequencing assays in the study.
DOI: 10.6084/m9.figshare.26994601.v1
title: Additional file 9 of Disruption of maternal vascular remodeling by a fetal endoretrovirus-derived gene in preeclampsia

description: Additional file 9. Table S8. QC metrics for sequencing assays in the study.
DOI: 10.6084/m9.figshare.26994652
title: Additional file 1 of An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis

description: Additional file 1. Marker genes list for each stage 7, 8.1 and 9.1, and for non-integrated and rPCA integrated clusterings.
DOI: 10.6084/m9.figshare.26994652.v1
title: Additional file 1 of An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis

description: Additional file 1. Marker genes list for each stage 7, 8.1 and 9.1, and for non-integrated and rPCA integrated clusterings.
DOI: 10.6084/m9.figshare.26994655
title: Additional file 2 of An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis

description: Additional file 2. FASTA file of predicted cell cycle genes in Parasteatoda tepidariorum.
DOI: 10.6084/m9.figshare.26994655.v1
title: Additional file 2 of An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis

description: Additional file 2. FASTA file of predicted cell cycle genes in Parasteatoda tepidariorum.
DOI: 10.6084/m9.figshare.26994697
title: Additional file 10 of A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus fossil record

description: Additional file 10: Table S2. Minimum ages of EVEs.
DOI: 10.6084/m9.figshare.26994697.v1
title: Additional file 10 of A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus fossil record

description: Additional file 10: Table S2. Minimum ages of EVEs.
DOI: 10.6084/m9.figshare.26994754
title: Additional file 12 of Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

description: Additional file 12. Table S5. Differential biological pathways and functions between DTBC and LumA. (A) Genes and proteins that are significantly differentially expressed and share overlapping agreement in their upregulation (green) and downregulation (orange) between DTBC and LumA. (B) Genes that are significantly differentially expressed between DTBC and LumA and are linked to the IPA cell proliferation regulator network. The table concludes with the listing of 7 recognized IPA regulators, which are highlighted in yellow. (C) Proteins that are significantly differentially expressed between DTBC and LumA and are associated with the FOXC1 regulator network. (D) Predicted molecular functions by IPA for the differentially expressed phosphopeptides between DTBC and LumA.
DOI: 10.6084/m9.figshare.26994745
title: Additional file 9 of Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

description: Additional file 9. Table S2. Differential mutations and SCNA between DTBC and LumA tumors. (A) Significantly (p-value &lt; 0.1) differentially mutated genes with non-synonymous somatic short variants (SNV and INDEL) in DTBC versus LumA tumors. Odds ratio and p-value of the Firth logistic regression are reported. (B) Somatic copy number alterations (SCNAs) at the chromosome arm level that show significant differences (p &lt; 0.05) between DTBC and LumA tumors. Samples with a value of &gt;  = 0.1 were classified as amplified, and those with &lt;  = − 0.1 were categorized as deleted. The table’s order corresponds to the clustering arrangement of Fig. 2D. (C) Genes linked with focal SCNA peaks displaying significant differences (FDR &lt; 0.05) between DTBC and LumA tumors. Cases with a relative SCNA of &gt;  = 0.1 are categorized as amplified, while those with &lt;  = − 0.1 are classified as deleted. The table provides Wilcoxon test p-values, adjusted p-values, and Pearson’s correlation coefficient (r) for gene’s SCNA and RNA expression. The table is arranged by cytoband, start coordinate, and FDR-adjusted p-values. Genes associated with cell proliferation are indicated in the table.
DOI: 10.6084/m9.figshare.26994745.v1
title: Additional file 9 of Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

description: Additional file 9. Table S2. Differential mutations and SCNA between DTBC and LumA tumors. (A) Significantly (p-value &lt; 0.1) differentially mutated genes with non-synonymous somatic short variants (SNV and INDEL) in DTBC versus LumA tumors. Odds ratio and p-value of the Firth logistic regression are reported. (B) Somatic copy number alterations (SCNAs) at the chromosome arm level that show significant differences (p &lt; 0.05) between DTBC and LumA tumors. Samples with a value of &gt;  = 0.1 were classified as amplified, and those with &lt;  = − 0.1 were categorized as deleted. The table’s order corresponds to the clustering arrangement of Fig. 2D. (C) Genes linked with focal SCNA peaks displaying significant differences (FDR &lt; 0.05) between DTBC and LumA tumors. Cases with a relative SCNA of &gt;  = 0.1 are categorized as amplified, while those with &lt;  = − 0.1 are classified as deleted. The table provides Wilcoxon test p-values, adjusted p-values, and Pearson’s correlation coefficient (r) for gene’s SCNA and RNA expression. The table is arranged by cytoband, start coordinate, and FDR-adjusted p-values. Genes associated with cell proliferation are indicated in the table.
DOI: 10.6084/m9.figshare.26994754.v1
title: Additional file 12 of Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

description: Additional file 12. Table S5. Differential biological pathways and functions between DTBC and LumA. (A) Genes and proteins that are significantly differentially expressed and share overlapping agreement in their upregulation (green) and downregulation (orange) between DTBC and LumA. (B) Genes that are significantly differentially expressed between DTBC and LumA and are linked to the IPA cell proliferation regulator network. The table concludes with the listing of 7 recognized IPA regulators, which are highlighted in yellow. (C) Proteins that are significantly differentially expressed between DTBC and LumA and are associated with the FOXC1 regulator network. (D) Predicted molecular functions by IPA for the differentially expressed phosphopeptides between DTBC and LumA.
DOI: 10.6084/m9.figshare.26994742
title: Additional file 8 of Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

description: Additional file 8. Table S1. Subtypes and Gene set enrichment analysis. (A) Contingency table comparing PCA-PAM50 and IHC subtypes. (B) Annotation of the differentially expressed genes between LMD and TCGA LumA samples. (C) Gene Set Enrichment Analyses highlight sets of immune-related pathways significantly down-regulated in LMD LumA tumors.
DOI: 10.6084/m9.figshare.26994742.v1
title: Additional file 8 of Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

description: Additional file 8. Table S1. Subtypes and Gene set enrichment analysis. (A) Contingency table comparing PCA-PAM50 and IHC subtypes. (B) Annotation of the differentially expressed genes between LMD and TCGA LumA samples. (C) Gene Set Enrichment Analyses highlight sets of immune-related pathways significantly down-regulated in LMD LumA tumors.
DOI: 10.6084/m9.figshare.26994769
title: Additional file 2 of Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting

description: Additional file 2. Simulation datasets used to generate the plots in Fig. 4.
DOI: 10.6084/m9.figshare.26994769.v1
title: Additional file 2 of Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting

description: Additional file 2. Simulation datasets used to generate the plots in Fig. 4.
DOI: 10.6084/m9.figshare.26994787
title: Additional file 1 of Integrated proteomic, phosphoproteomic, and N-glycoproteomic analyses of small extracellular vesicles from C2C12 myoblasts identify specific PTM patterns in ligand-receptor interactions

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.26994787.v1
title: Additional file 1 of Integrated proteomic, phosphoproteomic, and N-glycoproteomic analyses of small extracellular vesicles from C2C12 myoblasts identify specific PTM patterns in ligand-receptor interactions

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.26994790
title: Additional file 1 of Increasing the diagnostic yield of childhood glaucoma cases recruited into the 100,000 Genomes Project

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26994790.v1
title: Additional file 1 of Increasing the diagnostic yield of childhood glaucoma cases recruited into the 100,000 Genomes Project

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26994811.v1
title: Additional file 3 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 3: Table S2. Number of filtered variants per sample.
DOI: 10.6084/m9.figshare.26994808
title: Additional file 2 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 2: Table S1. Number of individuals, sex, and age groups aggregated by disease entities.
DOI: 10.6084/m9.figshare.26994811
title: Additional file 3 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 3: Table S2. Number of filtered variants per sample.
DOI: 10.6084/m9.figshare.26994814
title: Additional file 4 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 4: Table S3. Number of filtered variants aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994814.v1
title: Additional file 4 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 4: Table S3. Number of filtered variants aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994817
title: Additional file 5 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 5: Table S4. Number of filtered variants aggregated by disease entities, genes and VEP consequences.
DOI: 10.6084/m9.figshare.26994817.v1
title: Additional file 5 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 5: Table S4. Number of filtered variants aggregated by disease entities, genes and VEP consequences.
DOI: 10.6084/m9.figshare.26994820
title: Additional file 6 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 6: Table S5. Number of underexpression outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994823
title: Additional file 7 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 7: Table S6. Number of overexpression outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994826
title: Additional file 8 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 8: Table S7. Number of activation outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994829
title: Additional file 9 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 9: Table S8. Number of splicing outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994829.v1
title: Additional file 9 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 9: Table S8. Number of splicing outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994808.v1
title: Additional file 2 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 2: Table S1. Number of individuals, sex, and age groups aggregated by disease entities.
DOI: 10.6084/m9.figshare.26994820.v1
title: Additional file 6 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 6: Table S5. Number of underexpression outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994823.v1
title: Additional file 7 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 7: Table S6. Number of overexpression outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994826.v1
title: Additional file 8 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 8: Table S7. Number of activation outliers aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994832
title: Additional file 10 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 10: Table S9. Number of splice-affecting variants aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994832.v1
title: Additional file 10 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 10: Table S9. Number of splice-affecting variants aggregated by disease entities and genes.
DOI: 10.6084/m9.figshare.26994835
title: Additional file 11 of Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

description: Additional file 11: Table S10. Fraction of splice-affecting variants within filtered variants aggregated by disease entities and genes.