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• ATAC-Seq on OCIAML-22 Fractions

  The donor AML patient (unsorted) that was used to generate OCI-AML22 was expanded for 3-4 months, then sorted for the indicated fraction (CD34p: CD34+; CD34m: CD34-)

  Study EGAS00001006511

• Bulk RNA-seq of stromal cells from multiple cancer types

  We sorted CD45-CD44+CD90+ stromal cells from multiple tumor types and performed bulk RNA-seq. The data allows to infer CAF programs active across indications.

  Study EGAS00001006497

• Targeted_NanoSeq___TwinsUK_Blood

  Utilising Targeted NanoSeq, we hope to explore the driver landscape in unprecedented detail in donors from TwinsUK. These donors have paired buccal swabs and data from this will help contextualise that work.

  Study EGAS00001007595

• RNA sequencing of Human Organoid Lines

  The study will use RNA sequencing to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there are any clonal differences introduced when culturing these lines in different conditions.

  Dataset EGAD00001007971

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to two different E.Coli strains and a dye control with three biological duplicates. Their original culture was harvested as a control. In total 10 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD00001005416

• Transcriptomic profiling of RIRCD patient skeletal muscle, comparing recovered to affected disease phase.

  Illumina MiSeq total RNA sequencing profiles of skeletal muscle biopsies from patient F3/1M during affected disease phase (4 replicates: F3-1M_Affected_1, F3-1M_Affected_2, F3-1M_Affected_3, F3-1M_Affected_4) compared to recovered phase (F3-1M_Recovered_1, F3-1M_Recovered_2, F3-1M_Recovered_3, F3-1M_Recovered_4).

  Dataset EGAD00001006382

• Tumor Educated Platelets (TEPs) for breast cancer detection

  The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

  Dataset EGAD00001009790

• Cohort of NGS lymphoma samples used as control

  Control cohort of lymphoma samples sequenced with a hybrid capture panel designed to be able to detect translocations and mutations in lymphoma samples. used in the paper "Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing"

  Dataset EGAD00001007711

• Ewings Sarcoma Rearrangement Screen

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000389

• In this study single cell RNA-Seq data was used to train a deconvolution algorithm. The algorithm was validated on paired bulk RNA-Seq profiles.

  In this study single cell RNA-Seq data was used to train a deconvolution algorithm. The algorithm was validated on paired bulk RNA-Seq profiles.

  Dataset EGAD00001009688