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• Extreme intratumor heterogeneity and driver evolution in mismatch repair deficient gastro-esophageal cancer

  The dataset includes multi-region exome sequencing (MSeq) of four resected treatment naïve mismatch repair deficient gastro-esophageal cancers. Paired-end sequencing was performed on the Illumina HiSeq 2500 or NovaSeq 6000 with a target depth of 200X. Seven primary tumor regions along with tumor-adjacent non malignant tissue were subjected to MSeq. An additional two lymph node metastases were also included from each of two cases.

  Dataset EGAD00001004594

• Myeloma Targeted Follow-up Study

  Targeted sequencing follow-up of genomic lesions in multiple myeloma.

  Dataset EGAD00001001215

• ENU-HT-29 BRAF Triple Therapy Clones

  KRAS mutant CRC is currently in clinical trial with a combination of a MEK and Akt inhibitor. These patients will likely develop resistance to this combination. We aim to identify the mechanisms of resistance via ENU mutagenesis, with a view to identifying additional therapeutics which have the ability to overcome this resistance.

  Dataset EGAD00001002066

• Congenital Heart Disease in UK Families

  This project aims to identify highly penetrant coding variants increasing the risk of Congenital Heart Disease (CHD) performing whole exome sequencing on DNA samples from 23 affected individuals, selected from 10 families with presumed Autosomal Recessive Inheritance. This is a collaboration with Prof. Eamonn Maher and Dr. Chirag Patel from the Department of Medical and Molecular Genetics, University of Birmingham plans to sequence 23 indexed Agilent whole exome pulldown libraries on 75Bp PE HiSeq (Illumina)

  Dataset EGAD00001000343

• Naive B-cell receptor heavy chain repertoire of celiac patients and healthy controls

  High throughput sequencing dataset of antibody repertoires from naive B-cells, taken from blood samples of 100 individuals from Norway. 48 healthy controls and 52 patients with celiac disease. Sequencing was performed using a 300*2 paired-end kit by Illumina MiSeq. The sequences were processed using pRESTO. Each fastq file in the dataset is the repertoire of a single individual.

  Dataset EGAD00001004512

• A case of colorectal cancer with ERBB2 c.2264T>C (p.Leu755Ser) mutation

  This data set contains next generation sequencing (NGS) data of two serial tumor samples (primary and a metastasis) from a patient with colorectal cancer showing an ERBB2 c.2264T>C (p.Leu755Ser). NGS was performed using the Illumina TruSeq Amplicon Cancer Panel (TSACP, Illumina) covering 212 amplicons in 48 cancer associated genes on the Illumina MiSeq sequencing platform. The dataset contains two BAM files.

  Dataset EGAD00001002252

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues.

  Dataset EGAD00001002266

• Methylation profiling by MCC-Seq of visceral fat (N=199) and whole-blood (N=206) derived from IUCPQ participants

  The study includes NGS-based methylC-capture sequencing (MCC-Seq) on 199 visceral adipose tissue and 206 whole-blood DNA samples derived from obese individuals (BMI >40 kg m-2) in the IUCPQ cohort. We generated 100bp paired-end reads using the Illumina HiSeq2000 or 2500 systems.

  Dataset EGAD00001004787

• MiRNome_pituitary_adenoma

  Small RNA (<100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

  Dataset EGAD00001004998

• Whole genome sequencing data of paediatric T cell acute lymphoblastic leukemia (T-ALL)

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy accounting for approximately 15–25% of pediatric and adult ALL cases. Despite significant therapeutic improvements over the last decade, the prognosis of T-ALL remains less favorable than that of B-ALL, with 5-year EFS and OS of around 76–82% and 80–88%, respectively, depending on the treatment protocol used. T-ALL patients often suffer from failure of induction therapy or early relapse, which is associated with a dismal prognosis. Approximately 10–15% of T-ALL patients experience relapse, and survival after relapse is poor.

  Study EGAS50000001387

• plasma DNA LINE-1 targeted bisulfite sequencing: a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Study EGAS50000000446

• A110632A

  Whole genome sequencing for single cells for library A110632A 1151 cells; filetype=bam

  Dataset EGAD00001007094

• A110632B

  Whole genome sequencing for single cells for library A110632B 892 cells; filetype=bam

  Dataset EGAD00001007095

• A118833A

  Whole genome sequencing for single cells for library A118833A 919 cells; filetype=bam

  Dataset EGAD00001007096

• A118833B

  Whole genome sequencing for single cells for library A118833B 1147 cells; filetype=bam

  Dataset EGAD00001007097

• A118845B

  Whole genome sequencing for single cells for library A118845B 1209 cells; filetype=bam

  Dataset EGAD00001007098

• A118869A

  Whole genome sequencing for single cells for library A118869A 1165 cells; filetype=bam

  Dataset EGAD00001007099

• A118869B

  Whole genome sequencing for single cells for library A118869B 1124 cells; filetype=bam

  Dataset EGAD00001007100

• A95626A

  Whole genome sequencing for single cells for library A95626A 1040 cells; filetype=bam

  Dataset EGAD00001007103

• A95634B

  Whole genome sequencing for single cells for library A95634B 1335 cells; filetype=bam

  Dataset EGAD00001007105

• A95646A

  Whole genome sequencing for single cells for library A95646A 1071 cells; filetype=bam

  Dataset EGAD00001007106

• A95653B

  Whole genome sequencing for single cells for library A95653B 1342 cells; filetype=bam

  Dataset EGAD00001007107

• A95663B

  Whole genome sequencing for single cells for library A95663B 1364 cells; filetype=bam

  Dataset EGAD00001007108

• A95675A

  Whole genome sequencing for single cells for library A95675A 668 cells; filetype=bam

  Dataset EGAD00001007109

• A95731B

  Whole genome sequencing for single cells for library A95731B 1307 cells; filetype=bam

  Dataset EGAD00001007110

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

• A96118A

  Whole genome sequencing for single cells for library A96118A 1193 cells; filetype=bam

  Dataset EGAD00001007113

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• A96178A

  Whole genome sequencing for single cells for library A96178A 788 cells; filetype=bam

  Dataset EGAD00001007115

• A96178B

  Whole genome sequencing for single cells for library A96178B 846 cells; filetype=bam

  Dataset EGAD00001007116

• A96181C

  Whole genome sequencing for single cells for library A96181C 1216 cells; filetype=bam

  Dataset EGAD00001007117

• A96225B

  Whole genome sequencing for single cells for library A96225B 959 cells; filetype=bam

  Dataset EGAD00001007119

• A96225C

  Whole genome sequencing for single cells for library A96225C 1034 cells; filetype=bam

  Dataset EGAD00001007120

• A96240A

  Whole genome sequencing for single cells for library A96240A 1493 cells; filetype=bam

  Dataset EGAD00001007121

• A98172A

  Whole genome sequencing for single cells for library A98172A 898 cells; filetype=bam

  Dataset EGAD00001007123

• A98256A

  Whole genome sequencing for single cells for library A98256A 1372 cells; filetype=bam

  Dataset EGAD00001007124

• A98256B

  Whole genome sequencing for single cells for library A98256B 1437 cells; filetype=bam

  Dataset EGAD00001007125

• A98257B

  Whole genome sequencing for single cells for library A98257B 1286 cells; filetype=bam

  Dataset EGAD00001007126

• A98258B

  Whole genome sequencing for single cells for library A98258B 1357 cells; filetype=bam

  Dataset EGAD00001007127

• A98274B

  Whole genome sequencing for single cells for library A98274B 1295 cells; filetype=bam

  Dataset EGAD00001007128

• A98282A

  Whole genome sequencing for single cells for library A98282A 1198 cells; filetype=bam

  Dataset EGAD00001007129

• A98283A

  Whole genome sequencing for single cells for library A98283A 1137 cells; filetype=bam

  Dataset EGAD00001007130

• A98285A

  Whole genome sequencing for single cells for library A98285A 1422 cells; filetype=bam

  Dataset EGAD00001007131

• A98295B

  Whole genome sequencing for single cells for library A98295B 1381 cells; filetype=bam

  Dataset EGAD00001007132

• Cardiogenics_re_sequencing

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Study EGAS00001000079

• Molecular Characterization of ETMRs

  ETMRs are poorly characterized embryonal brain tumors with a dismal outcome. We collected tumors from 184 ETMR patients and 23 matched recurrences to investigate the genomic landscape of this distinct entity. Tumors without C19MC amplification, the proposed driver, harbor other miRNA related aberrations like DICER1 mutations and amplifications of the MIR17-92 miRNA cluster. All tumors behave molecularly similar and no subgrouping was observed. Whole-genome sequencing revealed an overall low recurrence of SNVs, but highly prevalent R-loop associated genomic instability. Finally, we show that targeting R-loops with TOP1 and PARP inhibitors might be an effective treatment strategy for this deadly disease.

  Study EGAS00001003256

• Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Study EGAS00001000043

• Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Study EGAS00001000050

• A108732A

  Whole genome sequencing for single cells for library A108732A 1139 cells; filetype=bam

  Dataset EGAD00001007592

• A108833B

  Whole genome sequencing for single cells for library A108833B 866 cells; filetype=bam

  Dataset EGAD00001007594

• A108842A

  Whole genome sequencing for single cells for library A108842A 1477 cells; filetype=bam

  Dataset EGAD00001007595

• A108863A

  Whole genome sequencing for single cells for library A108863A 1301 cells; filetype=bam

  Dataset EGAD00001007597

• A110618A

  Whole genome sequencing for single cells for library A110618A 1184 cells; filetype=bam

  Dataset EGAD00001007599

• A110673B

  Whole genome sequencing for single cells for library A110673B 1153 cells; filetype=bam

  Dataset EGAD00001007603

• A118830A

  Whole genome sequencing for single cells for library A118830A 912 cells; filetype=bam

  Dataset EGAD00001007604

• A118862A

  Whole genome sequencing for single cells for library A118862A 1070 cells; filetype=bam

  Dataset EGAD00001007605

• A118862B

  Whole genome sequencing for single cells for library A118862B 1152 cells; filetype=bam

  Dataset EGAD00001007606

• A95623B

  Whole genome sequencing for single cells for library A95623B 1363 cells; filetype=bam

  Dataset EGAD00001007608

• A95697B

  Whole genome sequencing for single cells for library A95697B 1233 cells; filetype=bam

  Dataset EGAD00001007610

• A95700A

  Whole genome sequencing for single cells for library A95700A 1172 cells; filetype=bam

  Dataset EGAD00001007611

• A95703A

  Whole genome sequencing for single cells for library A95703A 740 cells; filetype=bam

  Dataset EGAD00001007612

• A96233A

  Whole genome sequencing for single cells for library A96233A 637 cells; filetype=bam

  Dataset EGAD00001007622

• A95730A

  Whole genome sequencing for single cells for library A95730A 739 cells; filetype=bam

  Dataset EGAD00001007614

• A96114A

  Whole genome sequencing for single cells for library A96114A 798 cells; filetype=bam

  Dataset EGAD00001007615

• A96124B

  Whole genome sequencing for single cells for library A96124B 1241 cells; filetype=bam

  Dataset EGAD00001007616

• A96155C

  Whole genome sequencing for single cells for library A96155C 1316 cells; filetype=bam

  Dataset EGAD00001007617

• A96162A

  Whole genome sequencing for single cells for library A96162A 1505 cells; filetype=bam

  Dataset EGAD00001007618

• A96183B

  Whole genome sequencing for single cells for library A96183B 1191 cells; filetype=bam

  Dataset EGAD00001007619

• A96226B

  Whole genome sequencing for single cells for library A96226B 1274 cells; filetype=bam

  Dataset EGAD00001007621

• A98168A

  Whole genome sequencing for single cells for library A98168A 1294 cells; filetype=bam

  Dataset EGAD00001007624

• A98168B

  Whole genome sequencing for single cells for library A98168B 1290 cells; filetype=bam

  Dataset EGAD00001007625

• A98234A

  Whole genome sequencing for single cells for library A98234A 1240 cells; filetype=bam

  Dataset EGAD00001007626

• A98244A

  Whole genome sequencing for single cells for library A98244A 1271 cells; filetype=bam

  Dataset EGAD00001007628

• A98253A

  Whole genome sequencing for single cells for library A98253A 1250 cells; filetype=bam

  Dataset EGAD00001007629

• A98253B

  Whole genome sequencing for single cells for library A98253B 1388 cells; filetype=bam

  Dataset EGAD00001007630

• A98254A

  Whole genome sequencing for single cells for library A98254A 1490 cells; filetype=bam

  Dataset EGAD00001007631

• A98255B

  Whole genome sequencing for single cells for library A98255B 1394 cells; filetype=bam

  Dataset EGAD00001007632

• A98271A

  Whole genome sequencing for single cells for library A98271A 1190 cells; filetype=bam

  Dataset EGAD00001007633

• A98289A

  Whole genome sequencing for single cells for library A98289A 1066 cells; filetype=bam

  Dataset EGAD00001007634

• A98290B

  Whole genome sequencing for single cells for library A98290B 869 cells; filetype=bam

  Dataset EGAD00001007635

• A98305A

  Whole genome sequencing for single cells for library A98305A 986 cells; filetype=bam

  Dataset EGAD00001007637

• Single Cell Genome Sequence for DLP+ library A118389B

  Single Cell Genome Sequence for Telomerase immortalized breast epithelium cell line 184-hTERT 85.14 p20 cell line AT135 on DLP+ library A118389B

  Dataset EGAD00001009433

• Single Cell Genome Sequence for DLP+ library A118782A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118782A

  Dataset EGAD00001009435

• Single Cell Genome Sequence for DLP+ library A118808A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096B passage 1 on DLP+ library A118808A

  Dataset EGAD00001009440

• Single Cell Genome Sequence for DLP+ library A118812B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118812B

  Dataset EGAD00001009442

• Single Cell Genome Sequence for DLP+ library A118816A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118816A

  Dataset EGAD00001009444

• Single Cell Genome Sequence for DLP+ library A118857B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1184D passage 1 on DLP+ library A118857B

  Dataset EGAD00001009445

• Single Cell Genome Sequence for DLP+ library A95663A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053F passage 1 on DLP+ library A95663A

  Dataset EGAD00001009446

• Single Cell Genome Sequence for DLP+ library A95668A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A95668A

  Dataset EGAD00001009447

• Single Cell Genome Sequence for DLP+ library A95670A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 5 on DLP+ library A95670A

  Dataset EGAD00001009448

• Single Cell Genome Sequence for DLP+ library A95670B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6 on DLP+ library A95670B

  Dataset EGAD00001009449

• Single Cell Genome Sequence for DLP+ library A95717A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096A passage 1 on DLP+ library A95717A

  Dataset EGAD00001009450

• Single Cell Genome Sequence for DLP+ library A95722A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A95722A

  Dataset EGAD00001009451

• Single Cell Genome Sequence for DLP+ library A96109A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A96109A

  Dataset EGAD00001009452

• Single Cell Genome Sequence for DLP+ library A96113A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage on DLP+ library A96113A

  Dataset EGAD00001009453

• Single Cell Genome Sequence for DLP+ library A96130A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 8 on DLP+ library A96130A

  Dataset EGAD00001009454

• Single Cell Genome Sequence for DLP+ library A96142B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A96142B

  Dataset EGAD00001009455

• Single Cell Genome Sequence for DLP+ library A96154A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1135, patient SA1162SA on DLP+ library A96154A

  Dataset EGAD00001009456

• Single Cell Genome Sequence for DLP+ library A96161A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96161A

  Dataset EGAD00001009457

• Single Cell Genome Sequence for DLP+ library A96173A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 15 on DLP+ library A96173A

  Dataset EGAD00001009459