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Dataset results
32 results for “LCL”
High density SNP genotypes (Infinium Human CytoSNP-850K v1.2 BeadChip) of ERAP2-WT and ERAP2-KO Birdshot LCL
<p>SNP genotype data was performed on DNA isolated from WT and CRISPR-Cas9 edited LCLs (ERAP2-KO) according to standard procedures using the Infinium Human CytoSNP-850K v1.2 BeadChip (Illumina, San Diego, CA, USA). SNP-array results and data analysis were carried out using NxClinical software v5.1 (BioDiscovery, Los Angeles, CA, USA). Human genome build Feb. 2009 GRCh37/hg19 was used. </p>
Significant sQTLs and splicing TWAS reference panels (AMP-AD brain and EADB Belgian LCL cohorts)
<p>This dataset is part of the manuscript "<em><strong>New insights into the genetic etiology of Alzheimer’s disease and related dementias</strong></em>" by Bellenguez, Küçükali, et al. Nature Genetics 2022.</p> <p>Publication link: <a href="https://www.nature.com/articles/s41588-022-01024-z">https://www.nature.com/articles/s41588-022-01024-z</a></p> <p>GitHub repository of all QTL/TWAS data shared for this study: <a href="https://github.com/SleegersLab-VIBCMN/EADB_GWAS_NatureGenetics_QTL_TWAS">https://github.com/SleegersLab-VIBCMN/EADB_GWAS_NatureGenetics_QTL_TWAS</a></p> <p>For details, please see the publication. For any questions, please contact Fahri Küçükali (<a href="mailto:fahri.kucukali@uantwerpen.vib.be">fahri.kucukali@uantwerpen.vib.be</a>) and Kristel Sleegers (<a href="mailto:Kristel.Sleegers@uantwerpen.vib.be">Kristel.Sleegers@uantwerpen.vib.be</a>).</p> <p>Significant sQTL catalogues are compressed with <em>gzip </em>and tar achieve of splicing TWAS reference panels are compressed with <em>bzip2</em>.</p> <p><strong>sQTL catalogues</strong></p> <p>The files show significant sQTL - splice junction pairs mapped in AMP-AD brain and EADB Belgian LCL cohorts. The catalogues are in hg38/GRCh38 human genome build. Most of the columns in the files are based on FastQTL output (<a href="http://fastqtl.sourceforge.net/">http://fastqtl.sourceforge.net/</a>).</p> <p><em>sQTL file columns:</em></p> <ol> <li>variant_id - ID of the significant sQTL variant based on the dbSNPv151 rsID annotation or hg38/GRCh38 CHR_POS_REF_ALT ID if rsID not available.</li> <li>junc_id - sJunction ID assigned by Regtools/Leafcutter pipeline. For stranded datasets (ROSMAP and EADB Belgian) strand info is provided with "+" or "-" symbols, and if not stranded, "?" symbol is used.</li> <li>junc_distance - Genomic distance between sQTL variant and splice junction start</li> <li>ma_samples - Number of samples carrying the minor allele</li> <li>ma_count - Total count of minor alleles</li> <li>maf - Minor allele frequency</li> <li>pval_nominal - Nominal P-value of the association</li> <li>slope - Slope of the association with respect to alternative (ALT) allele indicated on column 14</li> <li>slope_se - Standard error of the slope</li> <li>pval_nominal_threshold - Nominal <em>P</em>-value significant threshold for thissJunction</li> <li>min_pval_nominal - Most significant <em>P</em>-value observed for this sJunction</li> <li>pval_beta - permutation <em>P</em>-value obtained via beta approximation and later used to calculate Storey q-values</li> <li>junction - sJunction in chr:start-end splice junction format</li> <li>cluster - The splice cluster of this sJunction</li> <li>genes - Genes overlapping with this sJunction (if any), based on GENCODEv24 (AMP-AD) and GENCODEv32 (EADB Belgian)</li> <li>GRCh38_chr_pos - Genomic position of the variant, separated by underscore</li> <li>ref_alt - Reference (REF) and alternative (ALT) allele of the variant, separated by ">" sign. ALT is the tested (A1) allele</li> </ol> <p>Of note, we also mapped the significant eQTLs in the same datasets (please see the data availability section of the manuscript or the GitHub repository).</p> <p><strong>Splicing TWAS reference panels</strong></p> <p>Custom splicing TWAS reference panels prepared using FUSION pipeline (<a href="http://gusevlab.org/projects/fusion/">http://gusevlab.org/projects/fusion/</a>) in AMP-AD brain and EADB Belgian LCL cohorts. All data in hg38/GRCh38 genome build. In each directory, you will find ".pos", ."profile", and ".profile.err" files. These are explained in the FUSION website as well, but briefly these are:</p> <ol> <li><strong>.pos:</strong> This is a position file that describes the 1Mb extended splice junction start and end coordinates for each calculated weight file for splice junction phenotype. Used for scanning the variants in those coordinates for TWAS.</li> <li><strong>.profile: </strong>This informs about all prediction weights calculated, in terms of number of variants in the model, heritability information, and R2 info for each prediction model used (top1, blup, enet, bslmm, lasso; bslmm was not used therefore has NA values).</li> <li><strong>.profile.err: </strong>This summarizes the reference panel in terms of average hsq (with SD), and which model is the best performing.</li> </ol> <p>Each TWAS weight is provided in a .RDat file under <strong>All_Splicing_Weights</strong>, and in this data we included all calculated functional weights independent of the fact that they are heritable features or not. In our TWAS analyses, we included the heritable functional weights at a hsq <em>P</em>-value ≤ 0.05 level.</p> <p>Please also see the expression TWAS reference panels we prepared in the same datasets (see the data availability section of the manuscript or the GitHub repository). If you need an LD reference data in hg38/GRCh38 genome build based on 1000 Genomes NFE samples (whose variant ID annotation are matching to these functional weights), suitable for running the TWAS/FUSION pipeline, please contact us.</p>
R-CHOP + GM-CSF for Previously Untreated LCL in Elderly
ClinicalTrials.gov study NCT00582725. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Significant eQTLs and expression TWAS reference panels (AMP-AD brain and EADB Belgian LCL cohorts)
<p>This dataset is part of the manuscript "<em><strong>New insights into the genetic etiology of Alzheimer’s disease and related dementias</strong></em>" by Bellenguez, Küçükali, et al. Nature Genetics 2022.</p> <p>Publication link: <a href="https://www.nature.com/articles/s41588-022-01024-z">https://www.nature.com/articles/s41588-022-01024-z</a></p> <p>GitHub repository of all QTL/TWAS data shared for this study: <a href="https://github.com/SleegersLab-VIBCMN/EADB_GWAS_NatureGenetics_QTL_TWAS">https://github.com/SleegersLab-VIBCMN/EADB_GWAS_NatureGenetics_QTL_TWAS</a></p> <p>For details, please see the publication. For any questions, please contact Fahri Küçükali (<a href="mailto:fahri.kucukali@uantwerpen.vib.be">fahri.kucukali@uantwerpen.vib.be</a>) and Kristel Sleegers (<a href="mailto:Kristel.Sleegers@uantwerpen.vib.be">Kristel.Sleegers@uantwerpen.vib.be</a>).</p> <p>Significant eQTL catalogues are compressed with <em>gzip </em>and tar achieve of expression TWAS reference panels are compressed with <em>bzip2</em>.</p> <p><strong>eQTL catalogues</strong></p> <p>The files show significant eQTL - gene pairs mapped in AMP-AD brain and EADB Belgian LCL cohorts. The catalogues are in hg38/GRCh38 human genome build. Most of the columns in the files are based on FastQTL output (<a href="http://fastqtl.sourceforge.net/">http://fastqtl.sourceforge.net/</a>).</p> <p><em>eQTL file columns:</em></p> <ol> <li>variant_id - ID of the significant eQTL variant based on the dbSNPv151 rsID annotation or hg38/GRCh38 CHR_POS_REF_ALT ID if rsID not available.</li> <li>gene_id - eGene ENSG gene ID based on GENCODEv24 (AMP-AD) or GENCODEv32 (EADB Belgian)</li> <li>tss_distance - Genomic distance between eQTL variant and eGene</li> <li>ma_samples - Number of samples carrying the minor allele</li> <li>ma_count - Total count of minor alleles</li> <li>maf - Minor allele frequency</li> <li>pval_nominal - Nominal <em>P</em>-value of the association</li> <li>slope - Slope of the association with respect to alternative (ALT) allele indicated on column 14</li> <li>slope_se - Standard error of the slope</li> <li>pval_nominal_threshold - Nominal <em>P</em>-value significant threshold for this eGene</li> <li>min_pval_nominal - Most significant <em>P</em>-value observed for this eGene</li> <li>pval_beta - permutation <em>P</em>-value obtained via beta approximation and later used to calculate Storey q-values</li> <li>gene_name - eGene name based on GENCODEv24 (AMP-AD) and GENCODEv32 (EADB Belgian)</li> <li>GRCh38_chr_pos - Genomic position of the variant, separated by underscore</li> <li>ref_alt - Reference (REF) and alternative (ALT) allele of the variant, separated by ">" sign. ALT is the tested (A1) allele</li> </ol> <p>Of note, we also mapped the significant sQTLs in the same datasets (please see the data availability section of the manuscript or the GitHub repository).</p> <p><strong>Expression TWAS reference panels</strong></p> <p>Custom expression TWAS reference panels prepared using FUSION pipeline (<a href="http://gusevlab.org/projects/fusion/">http://gusevlab.org/projects/fusion/</a>) in AMP-AD brain and EADB Belgian LCL cohorts. All data in hg38/GRCh38 genome build. In each directory, you will find ".pos", ."profile", and ".profile.err" files. These are explained in the FUSION website as well, but briefly these are:</p> <ol> <li><strong>.pos:</strong> This is a position file that describes the 1Mb extended gene start and end coordinates for each calculated weight file for each gene expression phenotype. Used for scanning the variants in those coordinates for TWAS.</li> <li><strong>.profile: </strong>This informs about all prediction weights calculated, in terms of number of variants in the model, heritability information, and R2 info for each prediction model used (top1, blup, enet, bslmm, lasso; bslmm was not used therefore has NA values).</li> <li><strong>.profile.err: </strong>This summarizes the reference panel in terms of average hsq (with SD), and which model is the best performing.</li> </ol> <p>Each TWAS weight is provided in a .RDat file under <strong>All_Expression_Weights</strong>, and in this data we included all calculated functional weights independent of the fact that they are heritable features or not. In our TWAS analyses, we included the heritable functional weights at a hsq <em>P</em>-value ≤ 0.05 level.</p> <p>Please also see the splicing TWAS reference panels we prepared in the same datasets (see the data availability section of the manuscript or the GitHub repository). If you need an LD reference data in hg38/GRCh38 genome build based on 1000 Genomes NFE samples (whose variant ID annotation are matching to these functional weights), suitable for running the TWAS/FUSION pipeline, please contact us.</p>
ET-01 in Subjects With Lateral Canthal Lines, LCL-207
ClinicalTrials.gov study NCT03655691. IPD Sharing: NO. Countries: 1. Publications: 0.
ET-01 in Subjects With Lateral Canthal Lines, LCL-209
ClinicalTrials.gov study NCT03912805. IPD Sharing: NO. Countries: 1. Publications: 0.
ET-01 in Subjects With Lateral Canthal Lines, LCL-208
ClinicalTrials.gov study NCT03839693. IPD Sharing: NO. Countries: 1. Publications: 0.
MT10109L in the Long-term, Open-label Treatment of Glabellar Lines (GL) and Lateral Canthal Lines (LCL)
ClinicalTrials.gov study NCT04157686. IPD Sharing: NO. Countries: 6. Publications: 0.
MT10109L in the Treatment of Glabellar Lines (GL) With or Without Concurrent Treatment of Lateral Canthal Lines (LCL)
ClinicalTrials.gov study NCT03721016. IPD Sharing: NO. Countries: 4. Publications: 0.
Gene expression profile of PMM2_CDG (Congenital Disorder of Glycosylation) B lymphoblastoid cell lines (B-LCL)
GEO Series GSE145082. Homo sapiens. 14 samples. Type: Expression profiling by array.
Impact of regulatory variation across human iPSCs and differentiated cells [ATAC-seq LCL]
GEO Series GSE108460. Homo sapiens. 20 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
LCL ATAC-seq
GEO Series GSE193312. Homo sapiens. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Transcriptome analysis for LMP1 depletion in GM12878 Lymphoblastoid cell line (LCL)
GEO Series GSE228167. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
LCL Bio-CAP-seq
GEO Series GSE193315. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Transcriptome analysis for LMP1 depletion rescue with Wildtype LMP1 or individual TES mutant LMP1 in GM12878 Lymphoblastoid cell line (LCL)
GEO Series GSE240732. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
ET-01 in Subjects With Lateral Canthal Lines, LCL-210
ClinicalTrials.gov study NCT04985916. IPD Sharing: NO. Countries: 1. Publications: 0.
Radiological Outcomes of Modified Extra-articular LCL
ClinicalTrials.gov study NCT06562062. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Two steps cross-linking LCL ChIP-seq
GEO Series GSE193310. Homo sapiens. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
LCL Capture-C
GEO Series GSE193314. Homo sapiens. 6 samples. Type: Other.
Improved LCL to iPSC reprogramming: RNA Analysis of LCLs, reprogrammed iPSCs, and differentiated NSCs reveal potential regulatory and functional processes involved in these cellular transitions.
GEO Series GSE74289. Homo sapiens. 36 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
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