14502 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Whole-Genome Sequencing in Multiplex Epilepsy Families

  Epilepsy is one of the most common neurologic disorders, affecting approximately 4% of individuals at some time in their lives. More than 30% of people with epilepsy continue to have seizures despite treatment, and improved approaches to treatment and prevention are sorely needed. In the search for new strategies to reduce the burden of disease, the discovery of specific genes that influence risk offers a novel opportunity to clarify pathogenic mechanisms, identify susceptible individuals prior to seizure onset, and treat and prevent seizures in people at risk. Despite clear evidence of the importance of genetics in susceptibility to epilepsy, only limited progress has been made in identifying the specific genes that influence risk. One of the greatest challenges for genetic research on this disorder is its extreme clinical and genetic heterogeneity. Although epilepsy is broadly defined by recurrent unprovoked seizures, it is so variable in its clinical manifestations, natural history, and treatment response that most epileptologists view it as a collection of different syndromes ("epilepsies") with distinct etiologies. The genetic effects on susceptibility are also likely to be extremely variable, ranging from rare variants with high penetrance (some of which produce Mendelian patterns of inheritance) to common variants with low penetrance. Recent findings strongly suggest that rare gene variants play a major role in the genetic architecture of the epilepsies. The purpose of this study was to discover new genetic risk factors for epilepsy. The primary approach was to use whole-genome sequencing to interrogate classes of genetic variants, including very rare variants, in multiplex families. Our main hypothesis was that, in at least some proportion of these families, a single variant would explain all instances of epilepsy. Variants identified within the families could then be tested for cosegregation within the family and also validated by seeing enrichment in sporadic epilepsy cases. Furthermore, understanding the impact of rare variation in epilepsy also has the potential to provide insight into the genetic architecture of other complex human diseases. Our analysis focused on families containing multiple individuals with non-acquired (idiopathic or unknown cause) epilepsy under the hypothesis that these would be enriched for genetic control. The families studied had been previously collected and phenotyped in detail, and contain an average of 3.8 individuals per family with a range of different types of epilepsy. We selected one or two affected individuals from each family for sequencing. This work has generated NGS data on 60 samples from 29 multiplex epilepsy families. We have established that, under a monogenic model of inheritance, sequencing pairs of distantly related relatives is an effective method for reducing the number of candidate variants. Critically, we have found that no single variant can explain a large proportion of these epilepsy families. This work emphasizes that identifying causal variants among the many genetic candidates found in this work will require very large sample sizes and gene-based analyses.

  Study phs000690

• MATCH-molecular driver

  Patients were biopsied at progression on molecular targeted agents and WES and/or WTS were performed to identify resistance mechanisms. 271 underwent one or sequential tissue biopsies.

  Dataset EGAD50000000697

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

  Four iPSC line data were sequenced by WGS. One of them has gene MYBPC3 modified.

  Dataset EGAD00001005066

• Matched FF and FFPE WGS from a metastatic prostate tumor

  This dataset contains three bam files. One normal blood sample and two matched FF and FFPE samples from the same metastatic prostate tumor.

  Dataset EGAD00001006180

• Whole exome and whole genome sequencing of pancreatic cancer

  These are seven sequencing files form whole exome and whole genome of five tissue samples collected from one pancreatic cancer patient

  Dataset EGAD00001003261

• RNA-seq of multi-regional CRC samples

  BAM files of RNA sequencing (RNA-seq) experiment on multi-regional colorectal cancer (CRC) samples. 58 samples corresponding to 16 patients were sequenced and there is one BAM file for each sample.

  Dataset EGAD00001006164

• Embryonal Rhabdomyosarcoma sequencing data

  This dataset contains samples from 9 patients with embryonal rhabdomyosarcoma. 9 samples have whole exome tumor data (one has multiple). 7 samples have tumor RNAseq data. 1 sample has matched normal dna sequence data

  Dataset EGAD00001007939

• Clinical data

  Clinical data for IMpower150 (one patient per line): anonymized_patient_id, train_test_split, ctDNA_status, ARM1, OS_months, OS_event, PFS_months, PFS_event, TTEOS_rebaseline_BL, TTEPFS_rebaseline_BL, TTEOS_rebaseline_C2D1, TTEPFS_rebaseline_C2D1, TTEOS_rebaseline_C3D1, TTEPFS_rebaseline_C3D1, TTEOS_rebaseline_C4D1, TTEPFS_rebaseline_C4D1, TTEOS_rebaseline_C8D1, TTEPFS_rebaseline_C8D1, pdl1_high, number_metastatic_sites, baseline_ECOG, age, sex_female, history_of_tobacco_use, sld_baseline, sld_wk6, sld_percent_change_bl_to_wk6, sld_difference_bl_to_wk6, AGEGRP, tumor_assessment_week_6, tumor_assessment_week_12, tumor_assessment_week_18, tumor_assessment_week_24, PFS_days, days_between_randomization_c3

  Dataset EGAD00001009726

• 71 Whole-exome sequencing of Esophageal Squamous Cell Carcinoma on Chinese Patients

  Esophageal Squamous Cell Carcinoma (ESCC) is one of the deadliest cancers worldwide. We performed 71 Whole-exome sequencing of Esophageal Squamous Cell Carcinoma on Chinese Patients.

  Dataset EGAD00001001926

• Illumina genome sequencing data for HICF2 craniosynostosis families (Genome Medicine)

  BAM files for two families recruited to the HICF2 genome sequencing project due to craniosynostosis. One family is a singleton and the other is an affected mother-daughter duo.

  Dataset EGAD00001011373