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• 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: 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: 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: BvB1_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: BvB1_F

  Dataset EGAD00001001701

• 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: 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: 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: 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: 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: 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: 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: 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: BvB10_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: BvB10_M

  Dataset EGAD00001001696

• 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: 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: MW52_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: MW52_M

  Dataset EGAD00001001843

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB10_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: BvB10_C

  Dataset EGAD00001001694

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_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: BvB22_F

  Dataset EGAD00001001707

• 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: 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: 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: BvB10_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: BvB10_F

  Dataset EGAD00001001695

• 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: 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: BvB15_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: BvB15_C

  Dataset EGAD00001001697

• 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: MW50_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: MW50_M

  Dataset EGAD00001001837

• 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: MW51_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: MW51_C

  Dataset EGAD00001001838

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW52_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: MW52_F

  Dataset EGAD00001001842

• 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: BvB15_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: BvB15_F

  Dataset EGAD00001001698

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB21_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: BvB21_M

  Dataset EGAD00001001705

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB1_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: BvB1_M

  Dataset EGAD00001001702

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB21_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: BvB21_C

  Dataset EGAD00001001703

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB21_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: BvB21_F

  Dataset EGAD00001001704

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB1_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: BvB1_C

  Dataset EGAD00001001700

• 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: 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: 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: 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: 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: 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: 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: MW51_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: MW51_M

  Dataset EGAD00001001840

• 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: 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: MW50_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: MW50_F

  Dataset EGAD00001001836

• 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: 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: 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: 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: 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: 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

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW51_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: MW51_F

  Dataset EGAD00001001839

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW52_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: MW52_C

  Dataset EGAD00001001841

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_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: BvB22_C

  Dataset EGAD00001001706

• 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: 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: 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: 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: MW50_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: MW50_C

  Dataset EGAD00001001835

• Targeted DNA sequence

  Targeted DNA sequencing files that were used in our study. The cohort was composed of 36 cases of tumor-only targeted DNA sequencing data. All files are UMI processed. The panel is designed with Agilent Sure Select and the sequence was performed using DNBSEQ sequencer.

  Dataset EGAD50000000972

• Characterization and clinical relevance of the genomic alterations defining invasive lobular breast cancer

  Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications.Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates.Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively.Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment.

  Dataset EGAD00001001395

• Somatic mutations in endometriosis and normal uterine endometrium

  To characterize the genomic features of endometriosis, we performed whole-exome sequencing for ovarian endometriotic epithelium samples obtained from subjects without concurrent gynecological cancers. Additionally, we analyzed histologically normal uterine endometrial epithelium samples obtained from subjects with benign gynecologic diseases. All the epithelium samples were isolated by laser microdissection from frozen sections.

  Study EGAS00001003095

• National Human Genome Research Institute (NHGRI) Clinical Sequencing Exploratory Research (CSER) The MedSeq Project: Integration of Whole Genome Sequencing into Clinical Medicine (HG006500)

  Whole genome sequencing (WGS) and whole exome sequencing (WES) services are currently available to and being utilized by physicians and their patients in both research and clinical settings, and recently to anyone in the general public via direct-to-consumer companies. But the widespread availability and use of WGS and WES in the practice of clinical medicine is imminent. In the very near future, sequencing of individual genomes will be inexpensive and ubiquitous, and patients will be looking to the medical establishment for interpretations, insight and advice to improve their health. Developing standards and procedures for the use of WGS information in clinical medicine is an urgent need, but there are numerous obstacles related to integrity and storage of WGS data, interpretation and responsible clinical integration. The MedSeq Project is an exploratory trial of WGS in clinical medicine. At the conclusion of this study, we will have helped create innovative protocols and novel outcome measures that can be applied safely in future large-scale multi-site randomized clinical trials with larger numbers of physicians from broad specialties and with more economically and ethnically diverse patients. Together with our colleagues from across the nation through the U01 consortium formed as a result of this funding from the NIH, we will have invented a process of implementation and evaluation whereby the fruits of the Human Genome Project can be applied for the first time to the daily practice of medicine for the betterment of human health. The objectives of the MedSeq Project are to: Recruit, consent and enroll 2 study groups: 10 primary care physicians and 100 of their healthy middle-aged patients 10 cardiologists and 100 of their patients with cardiomyopathy. Randomize each study group to receive standard of care versus standard of care plus WGS. Monitor the entire protocol for subject safety. Only half the enrolled patients were selected for sequencing. Fifty subjects were selected from the primary care cohort and fifty were selected from the cardiomyopathy cohort. Whole genome sequencing was performed at 30x coverage in Illumina's CLIA-certified laboratory on these 100 individuals. Generate and optimize an algorithm for interpreting WGS data covering the spectrum of human genetic variation, in terms of both previously reported and novel variants likely to influence the health of patients. Create patient reports and provide an interface for communicating clinically relevant genomic information to practicing physicians. Describe physicians' and patients' attitudes toward, and preferences for, the disclosure of WGS results at the start of the study. Evaluate physicians' experiences with receiving and interpreting patients' genetic test results and how they communicate these results to their patients. Explore how patients respond to and use WGS results by administering validated scales of psychological impact, personal utility, and behavioral responses, as well as economic and health outcomes. Although we do not have a large enough sample size for statistical comparisons of outcomes, we will conduct exploratory comparisons: Exploratory Hypotheses: Patients who receive WGS results will show equivalent levels of distress compared to patients who receive family history only. Patients with higher genetic literacy and better understanding will report greater satisfaction and less decisional regret. Patients who receive WGS will (a) be more likely to change health behaviors and (b) utilize more health care resources than those who do not receive WGS.

  Study phs000958

• Genomic sequencing of Ewing's Sarcoma

  The Ewing sarcoma family of tumors (EFT) is a group of malignant small round blue cell tumors that arise in bone or soft tissue. Ewing sarcoma (ES) is the second most common type of primary bone tumor to affect children and adolescents and accounts for 2.9% of all childhood cancers. This data set reports whole-genome sequencing of 6 primary Ewing's Sarcoma samples and matching germline samples.

  Study phs000768

• Clinical and Genetic Analysis of Retinopathy of Prematurity (ROP)

  Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide and is treated based on the presence of symptoms of "plus disease", a dilation and tortuosity of retinal vessels. This project aims to identify the genetic and clinical underpinnings of the disease by comparing the germline variants of ~1,400 premature babies. 100 samples have been selected for WES and all have been genotyped.

  Study phs002047

• Heart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of Dyspnea (HFN ROSE-BioLINCC)

  ObjectivesTo test the two independent hypotheses that when compared to placebo, addition of: (1) low dose dopamine; or (2) low dose nesiritide to diuretic therapy will enhance decongestion and preserve renal function in patients with acute heart failure and renal dysfunction.Background A primary treatment goal in acute heart failure is to achieve adequate decongestion while avoiding renal dysfunction and other side effects. Patients with acute heart failure and moderate or severe renal dysfunction are at risk for inadequate decongestion and worsening renal function - both of which are associated with worse outcomes. Renal adjuvant therapies that enhance decongestion and preserve renal function during treatment of acute heart failure are needed. Dopamine is an endogenous catecholamine which, at low doses, may selectively activate dopamine receptors and promote renal vasodilatation. Previous studies have suggested that the addition of low dose dopamine to diuretic therapy enhances decongestion and preserves renal function during diuretic therapy in acute heart failure; however, these studies were small with variable study designs and dopamine doses. B-type natriuretic peptide (BNP) is a cardiac peptide with vasodilating, renin and aldosterone inhibiting, natriuretic and diuretic properties. Nesiritide is human recombinant BNP approved for management of acute heart failure. The recommended dose lowers blood pressure and atrial pressures and produces modest improvement in dyspnea, but does not favorably impact clinical outcomes or renal function, potentially due to its hypotensive effects. Small studies using low dose nesiritide in acute heart failure and cardiac surgery patients have demonstrated favorable effects on urine output and renal function. Therefore, the Renal Optimization Strategies Evaluation (ROSE) trial was initiated to determine the benefits and safety of intravenous administration of low dose nesiritide or low dose dopamine in patients with congestive heart failure and kidney dysfunction. ParticipantsA total of 360 participants were enrolled. Design Participants were enrolled within 24 hours of hospital admission and randomized in a 1:1 ratio to the nesiritide or dopamine strategies. Participants randomized to the dopamine strategy were randomized in a double-blind 2:1 ratio to low dose dopamine (2 µg/kg/min for 72 hours infused via local guideline stipulated vascular access) or placebo. Participants randomized to the nesiritide strategy were randomized in a double-blind 2:1 ratio to low dose nesiritide (0.005 μg/kg/min for 72 hours infused via peripheral intravenous access without initial bolus) or placebo. All participants received open-label, intravenous loop diuretic treatment with a recommended total daily dose equal to 2.5x the total daily oral outpatient furosemide (or equivalent) dose at 7 days prior to admission up to a maximum of 600 mg/day. Participants naive to outpatient loop diuretics received 80 mg/day of intravenous furosemide. One-half of the total daily diuretic dose was administered as a bolus twice daily for at least 24 hours. Use of other medications and diuretic dosing after 24 hours were at the discretion of the clinician. All participants were placed on a 2000 mg sodium diet and 2000 cc fluid restriction. After the primary endpoint assessment at 72 hours, study drug was discontinued and subsequent treatment was at the clinician's discretion. The two co-primary endpoints were the 72-hour cumulative urinary volume as an index of decongestion efficacy and the change in cystatin-C from randomization to 72 hours as a measure of renal function preservation. Conclusions In participants with acute heart failure and renal dysfunction, neither low-dose dopamine nor low-dose nesiritide enhanced decongestion or improved renal function when added to diuretic therapy.

  Study phs003589

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson?s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000142

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson���s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000318

• NHLBI TOPMed: Pathways to Immunologically Mediated Asthma (PIMA)

  Study designed to further our understanding of the pathogenesis of asthma exacerbations in children. Children enrolled in the study (n=217) were all asthmatic and primarily Hispanic white. The children were followed for 18 months until they experienced an asthma exacerbation or completed the follow-up without an exacerbation. The time to the first asthma exacerbation was considered the outcome. The acute and convalescent immune phenotype of each asthma exacerbation was documented.

  Study phs001727

• Timing chromosomal amplification events using patterns of somatic mutations in high hyperdiploid acute lymphoblastic leukemia

  This dataset included 19 paired diagnostic and remission samples with high hyperdiploid acute lymphoblastic leukemia (ALL) that were collected from four different cohorts: the Division of Clinical Genetics, Lund University, Sweden. All samples were subjected to whole genome sequencing using the Illumina HiSeqX platform. Paired-end sequencing (2x150bp) was done to ~60x coverage for diagnostic samples and ~30x coverage for remission samples. The paired-end reads were aligned to the human reference genome GRCh37 (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/vertebrate_mammalian/Homo_sapiens/all_assembly_versions/GCF_000001405.25_GRCh37.p13/GCF_000001405.25_GRCh37.p13_genomic.fna.gz) by the Burrows-Wheeler Aligner tool (version 0.7.17). Duplicate reads marking and local realignment were performed by GATK (version 4.0.11.0).

  Dataset EGAD00001010103

• Assessing the impact of low frequency coding variants on disease risk using the Exomechip

  Following several rounds of Genome Wide Association (GWA) scans and subsequent meta-analyses of results multiple risk loci have been identified for many common diseases. However, in most instances the implicated common variants identified so far explain only a modest fraction of the genetic risk. In parallel to our efforts to identify the causative variants in the known loci it is necessary to assess the full spectrum of sequence variants for disease risk and in particular low frequency and rare variants that have not been tested in a comprehensive way so far. To this end an international effort by investigators who have performed whole exome sequencing in circa 12,000 individuals have assembled a set of ~250,000 exonic variants of low frequency – defined as seen in at least two studies and a minimum of three individuals (non-sysnonymous) or two individuals for SNPs altering splice sites / stop codons. The SNP content from the exome studies was complemented with additional interesting SNP sets totalling 25,000 markers (GWA tag SNPs, grid of common variants, HLA, Mitochondrial, Y-chromosome etc) and were used to generate a custom iSELECT array, the exome chip. Adequately powered association studies to test low frequency variants for association to disease risk are still very expensive if conducted by whole exome sequencing. The exome chip provides a cost efficient way to undertake such an experiment and the Wellcome Trust Cases Control Consortium will be applying this approach to eight diseases, type 1 and type 2 diabetes, coronary artery disease, hypertension, multiple sclerosis, rheumatoid arthritis, bipolar, and ankylosing spondylitis. The first objective will be to generate a large set of at least 10,000 common UK controls as analysis of lower frequency variants will require large sample sizes. This includes ~6000 samples from the 1958 Birth Cohort.

  Study EGAS00001000584

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• Genetics of Mammographic Density in Ashkenazi Jews

  Mammographic density (MD) is a strong risk factor for breast cancer and is also a highly heritable trait with ~60-70% of the variance due to genetic factors, based on twin studies. MD is also higher in families with a strong history of breast cancer. Genome-wide association studies (GWAS), which focus on common genetic variants, have identified several single nucleotide polymorphisms (SNPs) associated with MD. However, these SNPs explain a very small fraction of the variance of MD, suggesting many other genes are involved. Thus, the vast majority of the heritability of mammographic density remains unexplained and may be explained, at least in part, by rare variants. Ashkenazi Jewish women are a founder population; founder populations frequently have alleles affecting phenotypes which may be unique and/or extremely rare in other populations. Prior reports have identified an association between higher mammographic density and Ashkenazi Jewish ancestry. Therefore, we developed a study of mammographic density in AJ women. We combined datasets from several different cohorts including (a) the California Pacific Medical Center Research Institute (b) the Athena Breast Health Cohort and (c) the Marin Women's study. In each study, we identified women who reported AJ ancestry (determined by self-report or by genetic analysis). We identified mammograms by linking the women to the San Francisco Mammography Registry. We retrieved digital mammographic results and used software to infer volumetric density and percent volumetric density for each woman. We then performed genome-wide genotyping of the samples using the Illumina MEGA array.

  Study phs001857

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007412

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types (RNAseq)

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007428

• Metagenomic Deep Sequencing in Meningitis and Encephalitis

  This is a prospective observational study seeking to identify pathogens in cases of unexplained neurological disease, particularly those in which there is a presumed infectious cause. This next generation analytical approach will hopefully allow for rapid identification of foreign genomic material, and through a sophisticated bioinformatics pipeline developed in the DeRisi lab, these foreign genomic sequences can be aligned to all known sequences in publicly available databases (i.e. GenBank) which may allow for identification of novel pathogens or known pathogens that are not frequently tested for as part of standard diagnostic work-ups.

  Study phs001067

• Idiopathic Pulmonary Fibrosis Network AntiCoagulant Effectiveness in Idiopathic Pulmonary Fibrosis (IPFNet-ACE-IPF-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The ACE-IPF trial tested the hypothesis that treatment with warfarin at recognized therapeutic doses would reduce rates of mortality, hospitalization, and declines in Forced Vital Capacity (FVC) in subjects with Idiopathic pulmonary fibrosis (IPF).Background: IPF is a chronic, progressive lung disease of unknown cause characterized by the histopathologic pattern of usual interstitial pneumonia. The median survival of patients with IPF after the onset of symptoms is 2 to 5 years. Prior animal and human studies in pulmonary fibrosis provide a compelling rationale to examine anticoagulation as a therapeutic approach in IPF. Large epidemiologic studies link IPF with thrombosis-related clinical events, such as an increased risk of acute coronary syndrome and deep vein thrombosis. The suspected causal relationship may extend beyond simple coagulation cascade-induced thrombus formation, as procoagulant enzymes may directly stimulate fibrosis via cell surface receptor - mediated responses.Participants: Patients aged 35 to 80 years with progressive IPF were potentially eligible. Progressive IPF was defined as a history of (1) worsening of dyspnea, or (2) physiologic deterioration defined as an absolute decline of either FVC greater than or equal to 10% or DlCO greater than or equal to 15%, a reduction in arterial oxygen saturation of greater than or equal to 5%, or progression of radiographic findings. Between December 14, 2009 and April 1, 2011, 145 subjects were enrolled: 72 in the warfarin group and 73 in the placebo group. The mean age for the population was 67 years. 27% of the subjects were women and 92% were white.Participants were excluded if they met any of the following criteria: current indication for, or treatment with, warfarin, prasugrel, or clopidogrel combined with aspirin; the presence of an increased risk of bleeding; a recent cerebral vascular accident or gastrointestinal bleeding; any current signs or symptoms of severe, progressive, or uncontrolled comorbid illness; and their presence on the active list for lung transplantation. Design: ACE-IPF was a double-blind, randomized, placebo-controlled trial of warfarin targeting an international normalized ratio (INR) of 2.0 to 3.0 in patients with IPF. Subjects were randomized in a 1:1 ratio to warfarin or matching placebo for a planned treatment period of 48 weeks. Study subjects were provided two strengths of warfarin tablets (1 mg and 2.5 mg) or matching placebos. Subjects measured their INR with encrypted meters at least weekly. Participants were seen at screening, baseline, and at 16, 32, and 48 weeks after enrollment. Home monitoring was validated by plasma INR measurement at the week 1 and 16 visits.The primary outcome was a composite endpoint based on the time to all-cause mortality; nonelective, nonbleeding hospitalization; or a decrease in the absolute FVC greater than or equal to 10% from baseline value. Secondary outcome measures included rates of mortality, hospitalization, respiratory-related hospitalization, acute exacerbation, bleeding, cardiovascular events, and changes over time in FVC, 6-minute walk test distance, DlCO, plasma fibrin D-dimer levels, and quality of life (QOL).Conclusions: The study did not show a benefit for warfarin in the treatment of patients with progressive IPF and was terminated due to excess mortality in the warfarin treatment group. Treatment with warfarin was associated with an increased risk of mortality in an IPF population who lacked other indications for anticoagulation.Reported causes of death indicated 11 of the 14 were respiratory-related in the warfarin group versus three of the three in the placebo group. There were also three cardiovascular deaths in the warfarin group versus none in the placebo group. No deaths were attributed to bleeding. The warfarin group also demonstrated an increased rate of combined all-cause hospitalization and all-cause mortality. (Am J Respir Crit Care Med. 2012 Jul 1;186(1):88-95.)

  Study phs004070

• Development of molecular targeted therapy for small cell lung cancer by comprehensive genome analysis

  Aims: Identifying new therapeutic targets of small cell lung cancer (SCLC), genome-wide mutation analysis has been performed. Methods: Genomic DNA was extracted from formalin-fixed or methanol-fixed tissue samples. 71 Mb of DNA fragments containing whole coding exons were concentrated using SureSelect Human All Exon V4+UTRs Kit (Agilent Technologies) followed by 100-bp paired end sequencing by HiSeq 2000 (Illumina). Participants/Materials: 51 of 1042 cases of pathologically diagnosed small seen lung cancer that were registered to National Cancer Hospital East Lung Cancer Database in 1992-2012, and which surgically resected or biopsy samples were suitable for DNA extraction for further analyses.

  Study JGAS000037

• Prevention and Early Treatment of Acute Lung Injury (PETAL) - Low Tidal Volume Universal Support Feasibility of Recruitment for Interventional Trial (LOTUS FRUIT) (PETAL-LOTUS FRUIT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The two main goals of PETAL-LOTUS FRUIT were to conduct a prospective, observational study within all PETAL Network sites to determine the frequency of and outcomes from acute respiratory failure and the current usual care for tidal volume ventilation in patients with and without acute respiratory distress syndrome (ARDS), and to simulate the design and power of the proposed LOTUS trial. Background: A previous study demonstrated improved survival among patients with ARDS receiving tidal volume (Vt) targeted to 6 ml/kg of predicted body weight (PBW). As a result, low–tidal volume ventilation (LTVV) is now recommended for all patients with ARDS, although penetration of this evidence-based practice has been limited, especially early in mechanical ventilation. LTVV may also benefit patients without ARDS. Consequently, there has been increasing call to apply LTVV for all patients with acute respiratory failure upon initiation of mechanical ventilation. The PETAL Network considered performing a pragmatic stepped-wedge, cluster-randomized, controlled, hybrid implementation trial to examine systematic implementation of a default 6 ml/kg PBW LTVV strategy in patients with acute respiratory failure requiring intubation to improve adherence to LTVV and decrease mortality in acute respiratory failure. Trial planning may be better estimated by simulation than routine, simplistic calculations, but such simulations require detailed data of initial parameters. Participants: 2848 patients from 49 hospitals were enrolled. Enrollment varied by hospital, ranging from 4 to 100 patients, the maximum enrollment allowed per site. Design: PETAL-LOTUS FRUIT was a multicenter, prospective, observational cohort study of patients with acute respiratory failure on mechanical ventilation in the PETAL Network hospitals. For all patients, baseline demographic data, the hospital location, indication for intubation (hypoxemic or hypercapnic respiratory failure or both, altered level of consciousness, or surgery), type of intensive care unit (ICU), and Sequential Organ Failure Assessment score in the first 24 hours after intubation were collected. Baseline ventilator data immediately after intubation, arterial blood gas results and oxygen saturation as measured by pulse oximetry, and presence of ARDS was also collected for all patients. ARDS was defined as a ratio of arterial oxygen tension to fraction of inspired oxygen (FiO2) less than or equal to 300 with a chest radiograph within 24 hours of the qualifying ratio of arterial oxygen tension to FiO2 that had bilateral infiltrates unexplained by mass, collapse, or effusion. For the first 50 patients enrolled at each hospital, daily data on ventilator mode, Vt, and presence of ARDS for the first 3 days after intubation was collected. Vt indexed to PBW was calculated from the set Vt for patients on ventilator mode with volume settings. For patients on pressure ventilation modes, Vt was calculated from the ratio of minute ventilation (in ml/min) to the respiratory rate. Enrolled patients were followed until hospital discharge or 28 days for clinical outcomes including mortality, ventilator-free days, and length of stay. To determine the possible improvement in mortality that could be observed with a reduction in Vt from current usual care in the PETAL-LOTUS FRUIT cohort to 6 ml/kg PBW, mortality was estimated as a function of initial Vt. Five models based on data from three distinct patient populations were used. 500 simulations of a stepped-wedge, cluster-randomized clinical trial using the model with greatest predicted benefit for lowering the Vt to 6 ml/kg PBW in PETAL-LOTUS FRUIT sites were performed. Conclusions: Use of initial tidal volumes less than 8 ml/kg predicted body weight was common at hospitals participating in the PETAL Network. After considering the size and budgetary requirement for a cluster-randomized trial of LTVV versus usual care in acute respiratory failure, the PETAL Network deemed the proposed trial infeasible (PMID: 30407869).

  Study phs003791

• Acquiring and sequencing of all 24 single human chromosomes

  Haplotype phased whole genome sequencing of individuals is a technical challenge when family members are unavailable for determining chromosome of origin and variant linkage. Completely phasing genome sequences with single chromosomes has been shown to be feasible however amplifying all the single chromosomes for subsequent whole genome sequencing has been proposed but not performed to date. We acquired single chromosome of one of each of the autosomes and sex chromosomes to assess the feasibility of this sequencing library template preparation process.

  Study EGAS00001003300