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• Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

  In this prospective study, targeted deep sequencing was performed on a total of 160 primary tumors (474 regions) and 112 lymph nodes from 125 patients with stage I-III lung cancer (LuCaTH). Progressive evolution at clonal divergence scale was observed while specific driver events were positively selected for clonal sweeps during tumor development. Between-region genetic divergence (BRGD) of tumors were assessed and positively correlated with tumor differentiation. A machine learning algorithm was employed to evaluate clinicopathological and molecular parameters of primary tumors underlying lymph node metastasis. By analyzing clonal lineages and metastatic trajectories across multiple nodal stations, we unraveled a common sequential LNM seeding pattern but with divergent modes of clonal spread.

  Dataset EGAD00001007587

• Fecal WMS UC metadata

  Metadata for fecal WMS data from NCT02749630 ulcerative colitis patients.

  Dataset EGAD00001008820

• Fecal 16S HV metadata

  Metadata for fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers.

  Dataset EGAD00001008821

• Fecal 16S UC metadata

  Metadata for fecal 16S-V4 rRNA gene sequence data from NCT02749630 ulcerative colitis patients.

  Dataset EGAD00001008822

• Dataset for breast_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 12 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008867

• Dataset for cancer_of_unknown_primary-WHOLE_GENOME

  Rare cancer sequencing data of 46 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008869

• Dataset for synovial_sarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 6 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008899

• High hyperdiploid ALL single cell whole genome sequencing

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15).

  Dataset EGAD00001008988

• sWGS of OV04 patient samples for ACN rascal study

  This dataset contains 142 .bam files of shallow WGS data (~0.1X) from OV04 patient samples. Sequencing reads were aligned to the 1000 Genomes Project GRCh37-derived reference genome using the BWA aligner (v.0.07.17; CRUK-CI alignment pipeline).

  Dataset EGAD00001008121

• atrial appendage RNA-seq in non-, paroxysmal and persistent atrial fibrillation

  64 left atrial appendages from patients without atrial fibrillation (AF) undergoing cardiac surgery, patients with paroxysmal AF and with persistent AF (~20 per group). Trizol RNA isolation, rRNA depletion, paired transcriptome sequencing on illumina NovaSeq 6000. Provided are FastQ and BAM files. Additional data (e.g. clinical characteristics, RIN values etc.) can be provided upon reasonable request. The same RNA samples (62 out of 64) were used for miRNA sequencing. Results from miRNA seuqencing are stored in the EGA database managed by the same DAC.

  Dataset EGAD00001007693