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• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW4_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW4_F

  Dataset EGAD00001001833

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW49_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW49_F

  Dataset EGAD00001001830

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW32_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_F

  Dataset EGAD00001001815

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB51_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_C

  Dataset EGAD00001001760

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB50_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB50_M

  Dataset EGAD00001001759

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB50_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB50_F

  Dataset EGAD00001001758

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB50_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB50_C

  Dataset EGAD00001001757

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB4_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_M

  Dataset EGAD00001001756

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB4_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_F

  Dataset EGAD00001001755

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB4_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB4_C

  Dataset EGAD00001001754

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB44_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB44_M

  Dataset EGAD00001001753

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB44_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB44_F

  Dataset EGAD00001001752

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB44_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB44_C

  Dataset EGAD00001001751

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB43_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB43_M

  Dataset EGAD00001001750

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB43_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB43_F

  Dataset EGAD00001001749

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB43_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB43_C

  Dataset EGAD00001001748

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB42_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_M

  Dataset EGAD00001001747

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB42_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_F

  Dataset EGAD00001001746

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB42_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB42_C

  Dataset EGAD00001001745

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB41_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB41_M

  Dataset EGAD00001001744

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB41_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB41_F

  Dataset EGAD00001001743

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB41_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB41_C

  Dataset EGAD00001001742

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB40_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB40_M

  Dataset EGAD00001001741

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB40_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB40_F

  Dataset EGAD00001001740

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB40_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB40_C

  Dataset EGAD00001001739

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB38_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB38_F

  Dataset EGAD00001001737

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB38_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB38_C

  Dataset EGAD00001001736

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB35_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB35_M

  Dataset EGAD00001001735

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB35_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB35_F

  Dataset EGAD00001001734

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB35_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB35_C

  Dataset EGAD00001001733

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB33_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_M

  Dataset EGAD00001001732

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB33_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB33_C

  Dataset EGAD00001001730

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB31_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB31_M

  Dataset EGAD00001001729

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB31_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB31_C

  Dataset EGAD00001001727

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB30_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB30_M

  Dataset EGAD00001001726

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB30_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB30_F

  Dataset EGAD00001001725

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB30_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB30_C

  Dataset EGAD00001001724

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB28_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB28_M

  Dataset EGAD00001001723

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB28_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB28_F

  Dataset EGAD00001001722

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB27_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_M

  Dataset EGAD00001001720

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB27_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_F

  Dataset EGAD00001001719

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB27_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB27_C

  Dataset EGAD00001001718

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB25_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB25_M

  Dataset EGAD00001001717

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB25_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB25_F

  Dataset EGAD00001001716

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB25_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB25_C

  Dataset EGAD00001001715

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB24_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB24_M

  Dataset EGAD00001001714

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB24_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB24_C

  Dataset EGAD00001001712

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB23_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB23_M

  Dataset EGAD00001001711

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB51_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_M

  Dataset EGAD00001001762

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB52_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_F

  Dataset EGAD00001001764

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB55_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_C

  Dataset EGAD00001001766

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB55_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_M

  Dataset EGAD00001001768

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB58_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_F

  Dataset EGAD00001001773

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB58_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_M

  Dataset EGAD00001001774

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB8_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_C

  Dataset EGAD00001001781

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB8_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_M

  Dataset EGAD00001001783

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW14_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_F

  Dataset EGAD00001001788

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW20_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW20_C

  Dataset EGAD00001001796

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW22_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW22_C

  Dataset EGAD00001001799

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW2_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW2_M

  Dataset EGAD00001001813

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW32_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_C

  Dataset EGAD00001001814

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days LPS, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days LPS sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002337

• Transcriptome/Exome for glioblastoma intra-tumoral heterogeneity

  Total of 49 tumor specimens from 20 patients were subjected for whole-exome and/or whole-transcriptome sequencing including matched normal/blood. Tumor samples are acquired based on 4 categories; 1) locally adjacent tumors, 2) multifocal/multicentric tumors, 3) 5-ALA (+/-) tumors and 4) Longitudinal tumors.

  Dataset EGAD00001002248

• Sequencing Data for Sample 51_Hf01_BlCM_Ct

  Sequencing Data for DEEP Paper: "reChIP-seq reveals widespread bivalency of H3K4me3 and H3K27me3 in CD4+ memory T-Cells" Sample: 51_Hf01_BlCM_Ct (human, female, Blood, CD4+ central memory cell, normal control) Sequencing types are: total RNA, Whole Genome Bisulfite, ChipSeq (H3K27ac, H3K9me3, H3k36me3, H3K4me1, H3k27me3, H3K4me3, Input), reChipSeq (H3K27me3, H3K4me3)

  Dataset EGAD00001002255

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq EAC expression data - Publication Secrier & Li et al., 2016, Nature Genetics

  Dataset EGAD00001002260

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days B-glucan, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002522

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days untreated, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days untreated sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002457

• BLUEPRINT release August 2016, DNase-Hypersensitivity for alternatively activated macrophage, on genome GRCh38

  DNase-Hypersensitivity data for 2 alternatively activated macrophage sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002481

• WES of oral-mucosa-derived organoids

  Tumor and matching normal tissues were collected from 8 patients and organoids were derived from each tissue. Whole exome libraries were prepared for tumor tissue, normal tissue, tumor organoids and normal organoids, and paired-end sequencing was performed using Illumina Novaseq 6000 system. Only tumor and matching normal tissues were sequenced for the patients without available organoids.

  Dataset EGAD00001005063

• IBD Whole Genome Sequencing (2019-08-14)

  Whole genome sequences at 15X depth of patients with Inflammatory Bowel Disease. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005254

• The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer

  The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer includes 538 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001005339

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• Validation data for the SV analysis package: GRIDSS, PURPLE, LINX

  Validation data containing sequencing data of 13 samples. An hybrid capture approach was used to validate findings of both Manta and GRIDSS for the samples in the validation set. The dataset also contains the reference sequences used.

  Dataset EGAD00001005525

• DESIGN II HNSCC RNA-Seq

  RNA-Seq data of 28 HPV-negative HNSCC specimens from patients treated at the Netherlands Cancer Institute (Amsterdam), VU Medical Centre (Amsterdam) or MAASTRO Clinic (Maastricht) in The Netherlands. HNSCC biopsy samples were obtained prior to treatment (chemo-radiotherapy) for the prospective study within the DESIGN project and used for polyA mRNA sequencing.

  Dataset EGAD00001005722

• aCGH CNV detection by CNsolidate for 6,827 DDD probands

  aCGH CNV detection by CNsolidate for 6,827 DDD probands

  Dataset EGAD00001005728

• RNA-sequencing

  RNA-sequencing for a cohort of B-ALL samples : 5 Down Syndrome (DS), 16 Hyperdiploid (HeH), 6 iAMP21, 9 other. RNA-sequencing for B-cell progenitors from 3 healthy. It also contains RNA-sequencing datasets of Patient-Derived Xenografts (X) developed from the B-ALL samples : 4 Down Syndrome (DS), 4 Hyperdiploid (HeH), 1 iAMP21, 3 other.

  Dataset EGAD00001005426

• Human tumour ChIP-seq.

  We profiled 16 patient tumour samples by ChIP-seq. H3K27ac and Input are provided for 16 samples and H3K27me3 is provided for 14 samples. Among the 16 samples, 9 are G34WT and 7 are G34R/V. The raw fastq or bam files are provided.

  Dataset EGAD00001006100

• H3Africa CAfGEN Exome

  Whole Exome Sequencing data from a retrospective paediatric HIV-disease progression cohort defined on the World Health Organization's criteria for paediatric HIV progression. Data comprises of BAM and VCF files for 314 participants from 2 countries: Botswana and Uganda. DNA and RNA samples are linked in bio-repository.

  Dataset EGAD00001006224

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• single-cell RNAseq FASTq files for three muscle-invasive bladder tumors

  single-cell RNAseq FASTq files for three muscle-invasive bladder tumors

  Dataset EGAD00001008001

• RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  Dataset EGAD00001008656

• FACS sorting of ploidy populations in an undifferentiated soft tissue sarcoma for RRBS

  Groups of cells belonging to different ploidy populations (based on PI staining) were collected from an undifferentiated soft tissue sarcoma. The different ploidy populations underwent RRBS, after which copy number signatures for the ploidy-sorted populations and the bulk population were extracted.

  Dataset EGAD00001008667

• Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

  Advamced Visium Spatial Gene Expression assay for FFPE tissues with human and SARS-CoV-2 whole transcriptome (WT) information at a 55 µm resolution. The dataset consists of 13 tissue sections from 5 patient lung tissue samples, 3 from COVID-19 patients and 2 from control patients.

  Dataset EGAD00001008701

• CHROMATIN ACTIVATION PROFILING OF STEREOTYPED CHRONIC LYMPHOCYTIC LEUKEMIAS

  We used chromatin-immunoprecipitation followed by sequencing (ChIP-Seq) with an antibody for the H3K27ac (a bona fide histone mark for regulatory element activation) in sorted CLL cells from 15 CLL, including cases from stereotyped subsets #1, #2, #4, and #8. The samples were sequenced by Illumina HiSeq 2500.

  Dataset EGAD00001009082

• Bulk ATAC data

  Bulk ATAC libraries were generated for patient samples A.1, A.3, A.5, A.6, A.7, A.11, A.12, A.13 and A.15. For each patient a library of CD3- cells (myeloid cells, considered tumor cells) and CD3+ cells (T cells, considered healthy) were generated.

  Dataset EGAD00001010188

• Sequencing data for oesophageal and related samples - Ganguli et al (RNA)

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization across Pediatric Brain Tumors and Other Solid and Hematologic Malignancies for Research, Diagnostic, and Precision Medicine

  This study contains tumor and germline WGS, RNA-Seq, Clinical Panel Sequencing, and other omics and molecular data for patients with pediatric brain tumors and other solid and hematologic malignancies. This data has been collected from multiple organizations including the multi-institute Children's Brain Tumor Network (CBTN), the Pacific Pediatric Neuro-Oncology Consortium (PNOC), and the Children's Hospital of Philadelphia Division for Genomic Diagnostics (CHOP DGD). In addition to being available pre-publication and without embargo via dbGaP and the NCI Cancer Research Data Commons, this data is made available via Cavatica, PedcBioPortal and the Kids First Data Resource Portal. Collectively, this availability strives to accelerate the research process and enable members of the scientific and patient communities to partner and make discoveries faster than ever before.In 2019, the CBTN launched the Pediatric Brain Tumor Atlas, which now comprises the largest collection of childhood brain tumor data in the world. This resource is helping accelerate not only brain tumor research, but is also empowering discovery for other rare childhood conditions. Brain tumors are the most common form of cancer in children aged 0-19 in the United States, and are the largest cause of cancer-related deaths. The estimated number of new cases in 2019 is nearly 3,800, and thus brain tumors are a rare disease. Despite their relative rarity, the years of potential life lost due to brain tumors in 2009 was estimated at 47,631 years for children and adolescents aged 0-19 in the United States; this is a disproportionate amount of life lost compared to adult cancers and represents an unrecognized societal threat. There is an urgent need to improve therapies for these children. This sequencing cohort defines the largest, clinically annotated pediatric brain tumor cohort study to date and seeks to define the intersection of germline and somatic underpinnings of pediatric brain tumors across a shared developmental context of cancer and structural birth defects.

  Study phs002517

• Genome-Wide Association Study of Genetic Susceptibility for Graft-vs-Host Disease Cohort 1

  Allogeneic hematopoietic stem cell transplantation (Allo-HSCT) is the only curative therapy for many advanced hematologic malignancies. Allo-HSCT is associated with significant morbidities and mortality, mainly because of the graft-versus-host disease (GVHD) caused by donor T cells recognizing antigens present in recipient tissues, and initiating an alloimmune response resulting in damage to many organs including the skin, gastrointestinal (GI) tract, and liver in recipient. More than half of all Allo-HSCT recipients develop different degrees of GVHD (grades I-IV). About 20% of recipients develop severe GVHD (grades III-IV) that is associated with a very high morbidity and mortality. The most important factor determining the severity of GVHD is the genetic disparities between donors and recipients, as is reflected in human leukocyte antigen (HLA) haplotypes that are routinely checked for donor selection. Even when donors and recipients are HLA-identical, many recipients develop severe GVHD. As a result, non-HLA antigens are important determinants of acute GVHD. An interesting and unique aspect of GVHD is that it is the consequence of an interaction between antigens present in one individual with the immune system of another individual. As a result, genotypes of both donor and recipient, and their interactions affect the pathogenesis of GVHD. To determine the genetic risk factors for GVHD, in the first aim (discovery phase), we will conduct Genome-Wide Association Studies (GWAS) in 3,000 patients who underwent Allo-HSCT and in their respective donors (6000 DNA samples) that are provided to us by the Center for International Blood and Marrow Transplant Research (CIBMTR), a research collaboration between the NMDP and Medical College of Wisconsin. In the second aim, we will validate the association between high risk genotypes detected in the first aim and severe GVHD in 1,750 donors and 1,750 recipients of Allo-HSCT, and perform the joint analysis with the discovery samples. In the third aim, we will investigate the functional effect of SNPs detected and validated to be significantly correlated with the severity of acute GVHD in mixed lymphocyte reaction (MLR), as an ex vivo surrogate for an alloimmune response.

  Study phs002185

• Personalized Medicine Strategy for MPNSTs: Using Precision Oncology on PDOX Models to Inform Tumor Boards

  Background: Malignant peripheral nerve sheath tumors (MPNSTs) are a heterogeneous group of aggressive soft tissue sarcomas with poor prognosis. Currently there is a lack of effective treatments for MPNSTs. Here, we propose a personalized medicine approach that integrates a precision oncology strategy guided by MPNST genomic analysis, with a functional validation of treatment response in an orthotopic xenograft model (PDOX) derived from the same MPNST. Methods: Comprehensive whole genome sequencing analysis was performed in primary MPNSTs, relapses and (in one case) metastases, following disease progression in two independent individuals. Matched MPNST PDOX models were generated by orthotopically implanting tumor fragments near the sciatic nerve of immunodeficient mice. Candidate targeted combination therapies were prioritized based on genomic alterations and tested in vivo in the PDOX models. Results: The feasibility of the developed strategy is illustrated for two MPNST patients, one Neurofibromatosis type 1 (NF1) individual that developed two independent MPNSTs and another sporadic MPNST case with multiple metastatic relapses. Genomic analysis revealed a remarkable degree of genomic stability across primary MPNSTs and their successive relapses in each patient, and even metastases in one individual. While based on a small number of cases requiringing additional analyses, this finding aligns with previous evidence suggesting a fair genomic conservation throughout tumor evolution. This stability supports the identification of consistent therapeutic vulnerabilities throughout disease progression. Among the therapies tested, co-treatment of MEK inhibitor (MEKi) plus bromodomain inhibitor (BETi) elicited the highest antitumor activity, resulting in approximately 60% tumor volume reduction in the sporadic MPNST PDOX model, whose patient has been receiving this therapy for eight months with sustained remission. Conclusions: This study demonstrates the feasibility and clinical utility of integrating genomic-driven precision oncology with PDOX-based functional testing for MPNSTs. This strategy may support molecular tumor boards (MTBs) in their treatment decisions. The observed genomic stability supports the use of longitudinal tumor profiling to guide treatment, and the success of MEKi+BETi highlights its potential as a combination therapy for MPNSTs.

  Study EGAS50000001502

• Genetic Studies of Chronic Kidney Disease (CKD)

  The Genetic Studies of Chronic Kidney Disease (CKD) is an ongoing genetic research and biobanking protocol which aims to elucidate the genetic basis CKD. The study recruits patients seen at the Columbia University Medical Center (CUMC) Nephrology Division for the evaluation and care of CKD. All patients clinically diagnosed with CKD are eligible to participate; there are no inclusion or exclusion criteria related to age, sex/gender, and/or race/ethnicity. In addition to office visits, patients are recruited in contexts including perinatal care and nonprofit events for patients with various forms of CKD; recruitment tools include bilingual informational brochures, flyers, and consent forms. All individuals provide informed consent; for minors, signature of the parent/guardian is required. Consent includes: use of biosamples given for genetic studies, and the request to be re-contacted if medically actionable genetic findings are identified. In the case of the latter, such research-level findings are first validated in a clinically certified (CLIA) laboratory environment, using a second sample given by the individual at the time of re-contact; following CLIA validation, the individual is once again re-contacted, and, assuming he or she still desires return of these results, they can then be returned. Following the above consent process to participate in the study, individuals provide a single biosample (generally, a venous blood sample), from which DNA is extracted using standard protocols and used for genetic studies, such as exome sequencing. Basic clinical and demographic data, including sex/gender, age, and race/ethnicity are also collected. All data collected is stored in a secure computerized database, with patient samples anonymized using numerical identifiers; the relation of this identifier to patients' names is kept in a locked computer file in a centralized database. Electronic data complies with all HIPAA and other privacy and security regulations, and resides on a firewall server maintained by the CUMC IT department.

  Study phs001828

• Women's Health Study Accelerometry Dataset

  Background The Women's Health Study (WHS) was a randomized trial testing low-dose aspirin and vitamin E for preventing cancer and CVD among 39,876 women aged ≥45 years throughout the US from 1992-2004. When the trial ended as planned, women who were willing to participate continued in an observational follow-up study. Participants in Accelerometer Study From 2011-2015, an ancillary study collected data on physical activity and sedentary behavior using accelerometers. Women were mailed a triaxial accelerometer (ActiGraph GT3X+, ActiGraph Corp) with a wear log, and asked to wear this on their hip for seven consecutive days, removing it only during sleep and water-based activities. Further details have previously been published (PMID: 30666321). A total of 17,708 women wore and returned their devices, and data were downloaded from the devices of 17,466 women; no data were available from the other 242 (device failure). By convention, a "valid day" of wear has data on at least 10 hours (PMID: 22698174). Among these 17,466 women, 17,062 had at least one valid day of wear. The data are provided for all 17,062 women. Additionally, "compliant wear" is conventionally defined for participants wearing the device for at least 10 hours, on at least 4 days (PMID: 22698174). Of the 17,062 women, 16,741 had compliant wear (PMID: 29109088). Self-reported Physical Activity and Sedentary Behavior After we received the accelerometer from a WHS participant, she was sent a questionnaire asking her to report the time she spent in different physical activities during the week that the accelerometer was worn (see questionnaire below). A total of 15,514 women (91% of participants in the Accelerometer Study) returned their physical activity questionnaires. In addition, beginning in October 2012, we included questions on sedentary behavior; a total of 9,430 women returned questionnaires that included questions on both physical activity and sedentary behavior.

  Study phs001964

• Wistar PDX Development and Trial Center

  Overall the outcomes of patients with metastatic melanoma have improved dramatically over the last decade due to an improved understanding of the molecular drivers of this disease. In particular, multiple targeted therapy regimens have been approved for patients with a BRAFV600E/K mutation, which are present in ~50% of cutaneous melanomas. These treatments achieve clinical responses in ~80% of patients with a BRAFV600E/K mutation, thus providing proof-of-concept of the therapeutic potential for personalized therapeutic strategies. However, most of the patients will progress within 2 years of starting those therapies. Further, currently there are no targeted therapies that have been shown to be effective in patients with a wild-type BRAF. Thus, there are unmet clinical needs to develop treatments that prevent or overcome resistance to existing therapies for patients with a BRAFV600E/K mutation, and that are effective in patients without a BRAF mutation. In order to facilitate the development of new therapeutic strategies, over the last 5 years we have led a major effort to develop a broad collection of PDX models to reflect the clinical, histological, and genetic heterogeneity of this disease. Our collection of PDX models represents one of the largest collections for any human malignancy, and our initial testing demonstrates that the collection accurately recapitulates the oncogenic drivers and molecular heterogeneity that is observed in patients. This collection also includes a subset of PDX established from patients with acquired resistance to targeted therapies that have been maintained on those agents in vivo to sustain their resistant phenotype. Together these efforts have generated a robust resource to develop, refine, and prioritize new personalized combinatorial therapies for patients. Thus, we propose to establish a multi-disciplinary and multi-institutional PDTC Program focused on the use and continued expansion of our robust melanoma PDX collection to identify new therapeutic approaches that fill important clinical gaps in this disease.

  Study phs002432

• Polycystic Ovary Syndrome (PCOS) Genetics

  PCOS is a complex genetic disease reflecting the interplay of susceptibility genes and environmental factors. The cardinal reproductive feature of the syndrome, hyperandrogenemia, appears to play a direct role in the pathogenesis of the associated metabolic abnormalities. Male as well as female first-degree relatives have reproductive and metabolic phenotypes including increased prevalence rates of type 2 diabetes (T2D), metabolic syndrome (MBS) and other risk factors for cardiovascular disease (CVD). Northwestern University (NU) investigators lead a team that has extensive experience in phenotyping PCOS and in the genetic analysis of complex diseases including genome-wide association study (GWAS). Together with an expert group of collaborators from the Hershey Medical Center, and The University of Chicago, we have conducted a GWAS to identify PCOS susceptibility alleles using a large cohort of extensively and consistently phenotyped PCOS cases. Population controls for this study come from the NUgene project described below. NUgene project: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators.

  Study phs000368

• Bone Microarchitecture

  Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.    

  Study phs002102

• Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

  The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

  Study phs001179

• Small RNA Contents of Extracellular Vesicles from Patients with Cognitive Decline

  In this proposal, we examined samples from living neurologically normal individuals (n=72), cognitively normal Parkinson's disease (PD; n=21), PD with mild cognitive impairment (PD-MCI; n=18), PD with dementia (PDD; n=23), and dementia with Lewy-bodies (DLB; n=18), Alzheimer’s disease (AD; n=33) and mild cognitive impairment (MCI, n=38). The main goal for this study was to assess the diagnostic utility of small RNA contents from extracellular vesicles (EVs) for the prediction of cognitive decline. Plasma samples were collected and the RNA from extracellular vesicles (EVs) was isolated using the Qiagen exoRNeasy kit, and the small RNA contents were sequenced using the PerkinElmer NextFlex kit (v2). While PD is typically thought of as a motor disorder, there are significant non-motor symptoms that can be devastating. One of the most common non-motor symptoms of PD is dementia (PDD). While PD subjects that develop dementia all have Lewy bodies, there is often co-pathology with tau and β-amyloid found at autopsy or by PET amyloid imaging; thus, subjects diagnosed with AD were also included in the study. The development of the category, mild cognitive impairment (MCI) in AD, and in PD, provides an opportunity to identify and examine a transitional state between normal aging and dementia; this is a patient population ideally suited for therapeutic intervention. Progress in the detection, validation, and standardization of molecular biomarkers from biofluids, such as extracellular RNAs (exRNAs), would be efficient and cost-effective aids in the assessment of disease progression, cognitive decline, and response to therapeutics. We have provided the raw fastq files for the sequencing data from each sample. We are also providing demographic information, as complete as we have for each person; including age, diagnosis, sex, and cognitive assessments.

  Study phs003300

• Childhood Cancer Data Initiative (CCDI): Genomic Analysis in Pediatric Malignancies

  Pediatric solid tumors are highly heterogeneous, encompassing a large number of histotypes. The genomic landscape of these diseases is characterized by few single-nucleotide variants (SNVs) compared to adult cancers. In contrast, many exhibit a high prevalence of structural or epigenetic changes that alter gene expression, underlining the need for comprehensive genomic approaches such as whole-genome sequencing (WGS). Several studies have specifically addressed the clinical utility of genomic analysis in the pediatric and AYA cancer setting. Review of these studies point to key challenges that must be addressed in order to advance the routine use of genomics in this population. We have established a large collection of solid tumor tissue samples through our biobanking efforts. Where possible, we obtain longitudinal samples from the same patient. These primary patient samples and their corresponding germline have been analyzed using whole genome and whole transcriptome sequencing methods and have been linked to clinical metadata using both manual curation and robust methods for automatic extraction from the electronic health record (EHR). Importantly, research-grade genomic analysis is performed in parallel to our CLIA-grade sequencing (“UCSF500”) efforts for some of the patients in this study cohort and have been submitted as part of the American Association for Cancer Research's project GENIE and/or the National Childhood Cancer Registry. For our sequenced tumor samples, we have retrospective clinical data and ongoing efforts to prospectively record key events throughout the patient's cancer journey. In our solid tumor program, we have developed many patient-derived xenograft models and a number of PDX-derived cell lines. These unique models have been evaluated using genomic and functional approaches including (in some cases) treatment with conventional chemotherapy or investigational agents. Lastly, these samples were collected from a population that is among the most diverse in the nation and includes significant numbers of Asian, Latino, Indigenous and African-American patients, groups that are traditionally underrepresented in many banking efforts.

  Study phs002430

• Gene expression signatures associated with chronic endometritis revealed by RNA sequencing

  Chronic endometritis (CE) is a persistent inflammatory condition of the endometrium characterized by the infiltration of plasma cells. CD138 immunohistochemistry is considered to improve the CE diagnosis rate. Using the number of CD138-positive cells equal or greater than five as a diagnostic criterion for CE, we identified 24 CE and 33 non-CE cases among women with infertility. We conducted RNA-sequencing analysis for these 57 cases in total as an attempt to elucidate the molecular pathogenesis of CE and to search for new biomarkers for CE. By comparing CE and non-CE groups, we identified 20 genes upregulated in the endometria of CE patients, including 12 immunoglobulin-related genes and eight non-immunoglobulin genes as differentially expressed genes. The eight genes were MUC5AC, LTF, CAPN9, MESP1, ACSM1, TVP23A, ALOX15, and MZB1. By analyzing samples in the proliferative and secretory phases of the menstrual cycle separately, we also identified four additional non-immunoglobulin genes upregulated in CE endometria: CCDC13 by comparing the samples in the proliferative phase, and OVGP1, MTUS2, and CLIC6 by comparing the samples in the secretory phase. Although the genes upregulated in CE may serve as novel diagnostic markers of CE, many of them were upregulated only in a limited number of CE cases showing an extremely high number of CD138-positive cells near or over one hundred. Exceptionally, TVP23A was upregulated in the majority of CE cases regardless of the number of CD138-positive cells. The upregulation of TVP23A in the endometria of CE cases may reflect the pathophysiology of a cell-type or cell-types intrinsic to the endometrium rather than the accumulation of plasma cells. Our data, consisting of clinical and transcriptomic information for CE and non-CE cases, helped us identify gene expression signatures associated with CE.

  Study JGAS000621

• Single-Gene vs. Panel Sequencing in Advanced HR+/HER2− Breast Cancer

  Background: Hormone receptor-positive (HR+)/HER2-negative (HER2−) breast cancer is the most common subtype of breast cancer, with biomarker-driven therapies improving outcomes. Liquid biopsies, which analyze circulating tumor DNA (ctDNA), are increasingly essential in clinical management, offering a minimally invasive approach to assess somatic alterations and guide therapy decisions. However, the choice of assay directly affects clinical utility and global access to validated testing platforms remains inconsistent. To address these challenges, this study aimed to compare the performance of single-gene and panel-based sequencing for detecting PIK3CA mutations in HR+/HER2− breast cancer and evaluate the added value of broader genomic profiling in guiding treatment decisions. Patients and methods: We conducted a prospective, multicenter study comparing our previously established SiMSen-Seq (SSS) assay, a single-gene method targeting PIK3CA hotspot mutations, with the AVENIO ctDNA Expanded assay, enriching for 77 clinically relevant cancer genes. Additionally, tumor fractions were estimated with mFAST-SeqS by assessing chromosomal aneuploidy. We analyzed 161 plasma samples collected from 146 patients with HR+/HER2− advanced breast cancer before starting a new line of palliative therapy. Results: High concordance (92.6%) was observed between SSS and AVENIO for PIK3CA mutation detection, with accurate variant allele frequency (VAF) quantification confirmed by Bland-Altman analysis and linear mixed-effects modeling. AVENIO identified additional PIK3CA mutations in 19% of samples as well as other actionable alterations, including ESR1 mutations (17.5%) and PI3K pathway alterations (40.6%). Panel sequencing improved the interpretation of negative liquid biopsy results by integrating tumor fraction and VAF metrics. Conclusions: Panel sequencing assays such as AVENIO provide broader genomic coverage, enhance the detection of actionable mutations and refine the interpretation of negative liquid biopsy findings. These findings support the integration of comprehensive ctDNA profiling into routine clinical practice for HR+/HER2− advanced breast cancer while highlighting the need for improved assay accessibility and expanded genomic targets.

  Study EGAS00001008200

• In this study, blood-brain barrier (BBB)-forming brain endothelial-like cells were generated from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). Cells were subsequently exposed to focused ultrasound and microbubbles (FUS+MB) to induce BBB opening and their transcriptome analysed. RNA sequencing (RNA-seq) results demonstrated minimal changes in the gene expression following FUS+MB suggesting safety of FUS+MB application in the clinical setting.

  The blood-brain barrier (BBB) is a major impediment to therapeutic intracranial drug delivery for the treatment of neurodegenerative diseases, including Alzheimer’s disease (AD). Focused ultrasound applied together with microbubbles (FUS+MB) is a novel technique to transiently open the BBB and increase drug delivery. Evidence suggests that FUS+MB is safe, however the effects of FUS+MB on human BBB cells, especially in relation to AD, remain sparsely investigated. Here we developed a human sporadic AD BBB cell platform to investigate the effects of FUS+MB on BBB cells and screen for the delivery of two potentially therapeutic AD antibodies. We generated BBB cells from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). We utilized this robust and reproducible platform to demonstrate increased delivery of potentially therapeutic antibodies across the BBB, including an analogue of Aducanumab (AduhelmTM) following FUS+MB treatment. Our results also demonstrate the safety of FUS+MB indicated by minimal changes in the cell transcriptome as well as little or no changes in cell viability and inflammatory responses within first 24 h post FUS+MB, with potentially important implications in a clinical setting. Finally, we report a more physiologically relevant hydrogel-based 2.5D BBB model as a key development for FUS+MB-mediated drug delivery screening, with potentially higher translational utility. Our results provide an important advancement for identifying FUS+MB-deliverable drugs and screening for cell- and patient-specific effects of FUS+MB, accelerating its use as a therapy in AD.

  Study EGAS00001005944