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• Multi-omic data of subjects of FUSION study

  Finland-United States Investigation of NIDDM Genetics (FUSION) Study has sought to understand the genetic basis of type 2 diabetes (T2D) and diabetes-related traits including glucose, insulin, lipid levels, and obesity. We have performed extensive multi-omic characterization of the study subjects, including SNP array genotyping, whole genome/exome DNA sequencing of blood/tissue/iPSC cells generated from fibroblast, as well as RNAs. The study has provided crucial data for understanding molecular and cellular mechanisms of the disease-causing variants and their respective target genes. This set of data will be a valuable resource to the T2D community.

  Study EGAS00001008440

• T-cell reconstitution after reduced dose ATLG induction in kidney transplant recipients

  Pre-sensitized kidney transplant recipients have a higher risk for rejection following kidney transplantation and therefore receive a lymphodepletional induction therapy with anti human T-lymphocyte globulin (ATLG). The time course of lymphocyte reconstitution with regards to overall and donor-reactive T-cell receptor (TCR) specificity remains elusive. In this study we aimed to describe the TCR repertoire in a reduced dose ATLG regimen making it possible to evaluate shifts in the shape of the immune repertoire and to detect the reappearance of donor-reactive T-cells following reduced lymphodepletional induction therapy.

  Study EGAS00001005941

• RNA-seq data for proximal and distal human LHBT UZH (CH)

  This dataset contains bulk RNA-seq data from 15 patients who underwent rotator cuff repair surgery, yielding paired proximal and distal samples of the long head of the biceps tendon (30 samples total). The submission includes 90 files, consisting of R1 and R2 FASTQ files for each sample as well asprocessed .TXT files containing gene-level counts generated after genome alignment. Raw sequencing reads were generated on an Illumina platform, aligned to the human reference genome GRCh38.p13, and quantified at the gene level.

  Dataset EGAD50000002095

• The evolutionary history of human colitis-associated colorectal cancer

  Inflammatory bowel disease confers an increased lifetime risk of developing colorectal cancer (CRC), and colitis-associated CRC (CA-CRC) is molecularly distinct from sporadic CRC (S-CRC). Here we have dissected the evolutionary history of CA-CRC using multi-region sequencing. Exome sequencing was performed on fresh-frozen multiple regions of carcinoma, adjacent non-cancerous mucosa and blood from 12 CA-CRC patients (n=55 exomes), and key variants were validated with orthogonal methods. Genome-wide copy number profiling was performed using SNP arrays and low-pass whole genome sequencing on archival non-dysplastic mucosa (n=9), low-grade dysplasia (LGD, n=30), high-grade dysplasia (HGD, n=13), mixed LGD/HGD (n=7) and CA-CRC (n=19). Phylogenetic trees were reconstructed, and evolutionary analysis used to reveal the temporal sequence of events leading to CA-CRC. 10/12 tumors were microsatellite stable with a median mutation burden of 3.0 single nucleotide alterations (SNAs) per Mb, around 20% higher than S-CRC (2.5 SNAs/Mb), and consistent with elevated aging-associated mutational processes. Non-dysplastic mucosa had considerable mutation burden (median 47 SNAs), including mutations shared with the neighboring CA-CRC, indicating a pre-cancer mutational field. CA-CRCs were often near-triploid (42%) or near-tetraploid (21%) and phylogenetic analysis revealed that copy number alterations (CNAs) began to accrue in non-dysplastic bowel, but the LGD/HGD transition often involved a punctuated catastrophic CNA increase.

  Study EGAS00001003028

• Targeted panel somatic variant sequencing dataset for "Molecular counting enables accurate and precise quantification of methylated ctDNA"

  Targeted panel somatic variant sequencing dataset for "Molecular counting enables accurate and precise quantification of methylated ctDNA." This dataset was created by running 60 cfDNA samples from patients with metastatic cancer to the lung through a research-use, tumor-naive, targeted-panel assay for measuring somatic mutations across a panel of 80 genes. All samples were sequenced on Illumina NextSeq 2000 with 150x2 paired end sequencing; files are in fastq.gz format. For the original study, the variant allele fractions of these somatic mutations were compared with the Tumor Methylation Scores calculated from Northstar Response in the same samples.

  Dataset EGAD50000001016

• Targeted long-read snIso-Seq of the human brain in neurodegenerative diseases

  Nuclei were extracted from postmortem human brain, and cDNA libraries were generated using the 10X Genomics 3' v3.1 kit. Prior to fragmentation, 75% of the library was reserved for long-read sequencing. This unfragmented library was used for target enrichment with a custom 50 gene probe panel from Twist Biosciences. The resulting amplified cDNA libraries were sequenced on a Sequel II. The files provided have undergone CCS generation, and we recommend following the guidelines in https://isoseq.how/ for further analysis starting with removal of primers using lima. The primer sequences that should be supplied are the Read 1 and TSO primers from the 10X Genomics kit.

  Dataset EGAD50000000179

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Korean Lung Cancer - 36 pair WES data

  This study includes 36 paired samples of Korean Lung Cancer paitients.36 Lung Cnacer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WES study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002843

• CRISPR transduction of iPS cells

  Genome engineering using CRISPR/Cas9 technology enables simple, efficient and precise genomic modifications in human cells. Conventional immortalized cell lines can be easily edited or screened using genome-wide libraries with lentiviral transduction. However, cell types derived from the differentiation of induced Pluripotent Stem Cells (iPSC), which often represent more relevant, patient-derived models for human pathology, are much more difficult to engineer as CRISPR/Cas9 delivery to these differentiated cells can be inefficient and toxic. Here, we present an efficient, lentiviral transduction protocol for delivery of CRISPR/Cas9 to macrophages derived from human iPSC with efficiencies close to 100%. We demonstrate CRISPR/Cas9 knockouts for three non-essential proof-of-concept genes - HPRT1, PPIB and CDK4. We then scale the protocol and validate for a genome-wide pooled CRISPR/Cas9 loss-of-function screen. This methodology enables, for the first time, systematic exploration of macrophage involvement in immune responses, chronic inflammation, neurodegenerative diseases and cancer progression, using efficient genome editing techniques.

  Study EGAS00001005102

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169