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• early-stage ESCC sequencing study

  We performed a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 esophageal squamous cell carcinoma phase (ESCC) patients, covering 9 histopathological stages in 3 phases as nontumor phase (NT phase), intraepithelial neoplasia phase (IEN phase), and ESCC phase. Proteogenomics elucidated the stage-specific molecular characterization and defined the cancer-driving waves along with the mutation accumulation in EC progression. The integrated multi-omics uncovered the chromosome 3q gain was the key event in the transmit from the NT to IEN phase, disclosed the top mutation of TP53 enhanced cell cycle and DNA replication in the IEN phase, and revealed the ESCC phase mutations of AKAP9 and MCAF1 elevated glycolysis and Wnt signaling, respectively. Furthermore, the trajectory analysis identified 6 major tracks related to different clinical features during ESCC progression. Growingly enhanced and hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) was detected and considered as a drug target in ESCC progression. Collectively, this study provides insight into the understanding of ESCC molecular mechanism and a valuable resource for the development of therapeutic targets.

  Study EGAS00001006126

• FusionSeq: a modular framework for finding gene fusions by analyzing Paired-End RNA-Sequencing data

  We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts such as misalignments or random pairing of transcript fragments and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including 8 cancers with and without known rearrangements.

  Study phs000311

• Spatial omics analysis of non-small cell lung cancers for revealing molecular statuses of intratumor heterogeneity and tumor microenvironment

  In this study, we perform spatial transcriptome analysis Visium/Xenium and other omics analysis using surgical specimens of Japanese non-small cell lung cancer cases to understand omics statuses of cancer cells and their surrounding stromal and immune cells in local tumor regions. We aim to stratify lung cancer patients with considering intratumor heterogeneity and complicated microenvironent of lung cancer tissues by using spatial omics data and histopathological information.

  Study JGAS000613

• Research for drug discovery and elucidation of pathophysiology using disease-specific iPS cells

  We investigated roles of KRAS on stemness maintenance and differentiation propensity in the context of induced pluripotent stem cells (iPSCs) using isogenic KRAS mutant (G13C/WT) and wild-type (WT/WT) iPSCs from the same RAS-associated autoimmune lymphoproliferative syndrome-like disease (RALD) patients. Exome-seq analysis was conducted to compare gene profiles of WT/WT and G13C/WT iPS cells. We have not found any differences of gene mutation in the two genotypes.

  Study JGAS000136

• Comparative genomics research for Chinese colorectal cancer

  In order to clarify the mechanisms of genesis and development of colorectal carcinoma, in this study, we performed comparative genomics research in Chinese colorectal cancer at various clinical stage via whole exon sequencing or whole genome sequencing. Comparative bioinformatical analysis was perform to find the difference on somatic single-nucleotide variants, short insert/deletion variants, genomic structural variants, and copy number variants between cancer tissue and normal tissue, or among cancer tissues at various clinical stages.

  Study EGAS00001002576

• Comparative genomics research for Chinese colorectal cancer

  In order to clarify the mechanisms of genesis and development of colorectal carcinoma, in this study, we performed comparative genomics research in Chinese colorectal cancer at various clinical stage via whole exon sequencing or whole genome sequencing. Comparative bioinformatical analysis was perform to find the difference on somatic single-nucleotide variants, short insert/deletion variants, genomic structural variants, and copy number variants between cancer tissue and normal tissue, or among cancer tissues at various clinical stages.

  Study EGAS00001002607

• Combinatorial CRISPR screen identifies fitness effects of paralogues FAM50A and FAM50B

  Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1,191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. This dataset includes CRISPR screening of cancer cell lines, RNA sequencing studies of cancer cell lines and also data from the sequencing of tumour xenografts collected from mice.

  Dataset EGAD00001006648

• Anthropological dataset 2 for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_233CaboVerde_GEOcoordFULL_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file Column 2-3 corresponds to X-Y GPS coordinates of individual's interview location in Cabo Verde Column 4-5 corresponds to X-Y GPS coordinates of individual's self-reported residence location at the time of the interview Column 6-7 corresponds to X-Y GPS coordinates of individual's self-reported birth-place location Column 8-9 corresponds to X-Y GPS coordinates of individual's self-reported paternal birth-place location Column 10-11 corresponds to X-Y GPS coordinates of individual's self-reported maternal birth-place location

  Dataset EGAD00001008977

• Interval whole-genome sequence (WGS) data

  Whole-genome sequencing (WGS) genotype data generated as part of the Interval project. The data are reported, separately per chromosome, in variant call format (VCF). The genotypes are denoted in diploid format (for chrY the genotype 1 denoted as 1/1 and 0 denoted as 0/0). Note that multi-allelic variants are present in the data, but encoded to appear on separate, consecutive lines. The data are reported in following versions - unphased, phased, phased with imputation, sites only. Note: the unphased version has additional genotype information, while the phased versions only contain the genotypes.

  Dataset EGAD00001008661

• Whole exome sequencing of SarBC-01- and UroBC-01-related samples.

  This dataset contains raw FASTQ files from DNA of SarBC-01-related samples (SarBC-01 patient Germline, SarBC-01 patient Urothelial tumor, SarBC-01 patient Sarcomatoid tumor, SarBC-01 Passage 6 organoids, SarBC-01 Passage 20 organoids) and UroBC-01 related samples (UroBC-01 patient Germline, UroBC-01 patient Urothelial tumor, UroBC-01 Passage 19 organoids, UroBC-01 Passage 6 organoids). DNA was extracted from FFPE tissue, using RecoverAll RNA/DNA extraction kit (Invitrogen, Carlsbad, CA, USA, AM1975) followed by incubation with Uracil-DNA Glycosylase, and fresh or flash frozen tissue, using Quick-DNA/RNA Miniprep kit (Zymo Research, Irvine, CA, USA, D7001). Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience, 102031) was used for the whole exome capturing. Sequencing was performed on Illumina NovaSeq 6000 using paired-end 100-bp reads.

  Dataset EGAD00001011157