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• RNAseq for 4 pdx and 1 cell-line

  RNAseq for #1049, #111, #1217, #206, COV362

  Dataset EGAD50000000032

• PBMC

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000654

• DATA FILES FOR SJINF RNASeq

  DATA FILES FOR SJINF RNASeq

  Dataset EGAD00001001098

• Deep sequencing of melanoma for driver mutations

  Deep sequencing of melanoma for driver mutations

  Dataset EGAD00001001445

• Australian genomes

  Mapped data (bam files) for high-throughput whole genome sequence data for 83 modern Aboriginal Australians

  Dataset EGAD00001002001

• Panic study

  To manage Panic saliva microbiota 16S data produced in collaboration.

  Dac EGAC50000000408

• Evidence that ciliary genes contribute to non-syndromic familial tall stature

  Study EGAS00001005372

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Study EGAS00001007528

• Genetic Diseases of Immune Homeostasis and Autoimmunity Caused by GIMAP Deficiency

  We investigated 17 affected individuals in 9 kindreds with lymphopenia, splenomegaly, liver disease, thrombocytopenia, lymphadenopathy, severe recurrent lung infections, skin diseases, and lymphoma. Whole-exome sequencing of the cohort revealed mutations in GIMAP5. We also found another patient from one kindred with a unique mutation in the gene GIMAP6, discovered by whole-exome sequencing. A comprehensive investigation of this gene mutation through in vivo and in vitro experiments revealed that GIMAP6 deficiency results in defects in autophagy in patient T cells and interruption of GIMAP7 and GABARAPL2 interactions. GIMAP6 deficiency leads to affected patients to present with clinical phenotypes such as recurrent infections, lymphoproliferation, autoimmunity, and inflammation.

  Study phs002816

• Expressed Pseudogenes in the Transcriptional Landscape of Human Cancers

  In this study, we describe a systematic analysis of pseudogene 'transcription' from an RNA-Seq resource of 293 samples, from 13 cancer and normal tissue types. We observed a highly prevalent, genome-wide expression of pseudogenes that could be categorized as universally expressed or lineage- and/or cancer-specific. We also explored disease subtype specificity and functions of selected expressed pseudogenes. We provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.

  Study phs000525