Supplementary table

Research Data for Psychological factors and oral health during initial outbreak of COVID-19 in China: A cross-sectional study by Qiang Sun, Honglin Ren, Yueran Bian, Yesi Xie, Hui Shi: The International Headache Genetics Consortium (IHGC) in Journal of International Medical Research

Supplemental material, sj-xlt-5-cll-10.1177_09636897231165874 for circSOBP Inhibits Bladder Cancer Proliferation and Metastasis by Regulating the miR-200a-3p/PTEN Axis and Participating in the Immune Response by Yinglang Zhang, Zhi Li, Yu Zhang, Chong Shen, Zhe Zhang, Xiaolei Ren, Changgang Guo, Shaobo Yang, Zejin Wang and Hailong Hu in Cell Transplantation

Additional file 1: Table S1. The basic compression performance comparison between GBC and alternative tools. Table S2. The comparison of GBC’s compression and decompression speed under multiple threads in the 1000GP3 dataset. Table S3. The data query performance comparison between GBC and alternative tools. Table S4. The comparison of LD calculation speed between GBC and alternative tools in the 1000GP3 and SG10K datasets. Table S5. The file management performance comparison between GBC and alternative tools....

To investigate the prognostic value of N6-methyladenosine (m6A)-, 5-methylcytosine (m5C)-, and N1-methyladenosine (m1A)-related genes in cervical cancer (CESC) and predicting immunotherapy response. We downloaded cervical cancer mRNA expression profiles, clinical data, and m6A, m5C, m1A-related genes from public databases, and subjected them to serial bioinformatics analysis and clinical sample validation. Differential analysis revealed 106 methylation-related differential genes (MEDs), including 44 differentially downregulated and 62 upregulated genes. We then obtained methylation models containing 10 genes by...

Additional file 3: Table S3. Proteins interacting with LAC proteins in Arabidopsis and C. sinensis.

Additional file 10: Table 8. Mapping of aging DMRs to the promoter regions (TSS7k3k) of regenerative DEGs in both synchronous (hyper-DMRs to down-DEGs; hypo-DMRs to up-DEGs) and inverse (hyper-DMRs to up-DEGs or hypo-DMRs to down-DEGs) patterns.

Additional file 6. The immune scores of each tumor sample were calculated.

Additional file 7. Total 10 KEGG pathways were predicted to be related with high and low TIME.

Additional file 1.

Additional file 6: Table S6. (A) KEGG analysis results in sMPLC. (B) KEGG analysis results in SPLC.

Additional file 1: Table S1. Primers used in this study. Table S2. COG annotation results. Table S3. Annotation results of mitochondria metabolism.

Additional file 5: Table S1. The specific primers for qRT-PCR.

Additional file 2:Table S1. The basic informations and sequencing data of NK-AML (M4/M5) patients and healthy donors.

Additional file 2: Table S2. Primers developed for six CsLAC genes for qRT‒PCR and CsLAC3 for subcellular localization.

Additional file 2: Table S2. Association results for the multi-ancestry index SNPs with the gene prioritization.

Additional file 2. Differentially expressed mRNAs between the EMP and the sham group.

Additional file 10: Table S7. DESE phenotype-tissue association results using both GTEx gene-level and transcript-level selective expression.

Additional file 22: Table S14. Test for difference in effects for index variants from sex-stratified meta-analysis.

Additional file 23: Table S15. Comparison of the sex-specific effects.

Additional file 23: Table S15. Comparison of the sex-specific effects.

Additional file 25: Table S16. Comparison of effect size estimates for sex-stratified analysis in the replication cohorts.

Additional file 17: Table S9. PheWAS UKB-MVP meta-analysis results for each index lipid variant at Bonferroni threshold for multiple testing p<=3.5e-8)

Additional file 3. Mass spectrometry identification data for the interactomics of SMYD3 (the protein score equal to or higher than two).

Additional file 8. Correlation analysis between PD-L1 expression and DEMGs expression.