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• WTCCC case-control study for Tuberculosis

  WTCCC genome-wide case-control association study for Tuberculosis (TB) using the African samples as controls.

  Study EGAS00000000027

• Transcriptomics for the ALTTO study

  Transcriptomics for the ALTTO study by high-throughput sequencing. 386 HER2+ breast cancers treated by trastuzumab were sequenced. Two fastq files are given for each sample.

  Dataset EGAD50000000746

• NGS sequencing for genes from the patients of OU Genome Project

  This research aims to identify disease related HLA alleles by genome analysis for cardiac sarcoidosis.

  Study JGAS000568

• Targeted capture sequencing for LySeqST

  Targeted capture sequencing of 445 lymphoma samples and 13 normal samples for LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma.

  Dataset EGAD50000002290

• Exome sequencing data for LMS tumor and control samples

  The data set contains paired end fastq files for whole exome sequencing data for Leiomyosarcoma tumor and control samples

  Dataset EGAD00001003829

• DIAMOND PCR : plasma DNA LINE-1 targeted bisulfite sequencing, a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Dataset EGAD50000000646

• Microbiome

  16S-sequencing: All stool samples were processed according to the standards of the Flemish Gut Flora Project (Falony et al., 2016). All samples were processed together and sequenced in as a single batch (dual index run DI23R22) which included positive controls (PC, identical stool sample), negative controls (PCR-mix) and ‘blanks’ or negative controls of the extraction (no sample). In addition, a Runella strain (RS) was included to check for potential cross-contamination, as this strain is not present in human samples. The V4 region of the 16S rRNA gene was amplified with the primer pair 515F and 806R (GTGYCAGCMGCCGCGGTAA and GGACTACNVGGGTWTCTAAT, resp.), modified to contain a barcode sequence between each primer and the Illumina adaptor sequences to produce dual- barcoded libraries (Tito et al., 2019). Sequencing was performed on the Illumina MiSeq. Sequences were processed using the LotuS (Hildebrand et al., 2014) and DADA2 pipeline (Callahan et al., 2016) using RDP 16 as the reference taxonomy.

  Dataset EGAD50000002027

• RNA-seq FASTQ files from newborn screening dried blood spot samples

  Paired-end RNA-seq FASTQ files from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). Each sample was sequenced in 4 lanes, leading to 8 FASTQ files per sample and a total of 21x8=168 FASTQ files. There is an additional number of 8 FASTQ files corresponding to sample BS13, which was downsampled to 1/4 of its original depth (see BS13_README file for details).

  Dataset EGAD00001004991

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643