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C20a5c29-7335-42d4-b0d0-5b85836bd769 - samples

ABSTRACT: Single-cell RNA sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

PROVIDER: EGAD00001011045 | EGA |

REPOSITORIES: EGA

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f744c9bb-447c-4f81-87cc-f1d2c5cfe381 - samples

Project description:TCRab sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

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Transcriptional regulation of germinal center B and plasma cell fates by dynamical control of IRF4 (ChIP-seq)

Project description:Temporal analysis of Irf4 and PU.1 genome binding during B cell activation and differentiation in vitro using antigen (NP-Ficoll) CD40L and IL-2/4/5 cytokines (see Molecular Systems Biology 7:495 for details of cellular system). The results provide insight in the target genes and binding specificity of IRF4 and PU.1 during coordination of different programs of B cell differentiation. Regrettably three of the FASTQ raw sequence files in our study were corrupted during storage. FASTQ data from our experimental and control groups are available for download via GEO SRA; however, two groups are missing select raw sequence files. These include one PU.1 Day 3 group file (Sample GSM1133499) and two of four input files used to generate a concatenated “super” input file (Sample GSM1133490); the raw data provided for input consists of the two input files recovered. Importantly, FASTA sequences for both of these datasets are available as supplementary data through GEO, and we can make available upon request (rsciamma@uchicago.edu) all files in our study in the ELAND-extended alignment format. Please note that GEO no longer supports this format.

2013-05-04 | GSE46607 | GEO

Spatial transcriptomic characterization of obesity-associated gene expression programs in endometrial cancer

Project description:This study investigates spatial transcriptomic alterations associated with obesity in endometrial cancer using NanoString GeoMx Digital Spatial Profiling. Tumor samples from obese and non-obese patients were profiled to identify gene expression programs linked to metabolic and oncogenic pathways. NOTE ON RAW DATA COMPLETENESS: 4 FASTQ files (F03_S3_L003_R1, F06_S6_L003_R2, F11_S11_L004_R1, F12_S12_L002_R2) were lost due to a server crash at the USC Center for Advanced Research Computing (CARC) and could not be recovered. All remaining raw and processed data files are complete and available.

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Transcriptional regulation of germinal center B and plasma cell fates by dynamical control of IRF4

Project description:The transcription factor IRF4 regulates immunoglobulin class switch recombination and plasma cell differentiation. Its differing concentrations appear to regulate mutually antagonistic programs of B and plasma cell gene expression. We show IRF4 to be also required for generation of germinal center (GC) B cells. Its transient expression in vivo induced the expression of key GC genes including Bcl6 and Aicda. In contrast, sustained and higher concentrations of IRF4 promoted the generation of plasma cells while antagonizing the GC fate. IRF4 cobound with the transcription factors PU.1 or BATF to Ets or AP-1 composite motifs, associated with genes involved in B cell activation and the GC response. At higher concentrations, IRF4 binding shifted to interferon sequence response motifs; these enriched for genes involved in plasma cell differentiation. Our results support a model of "kinetic control" in which signaling-induced dynamics of IRF4 in activated B cells control their cell-fate outcomes. Regrettably three of the FASTQ raw sequence files in our study were corrupted during storage. FASTQ data from our experimental and control groups are available for download via GEO SRA; however, two groups are missing select raw sequence files. These include one PU.1 Day 3 group file (Sample GSM1133499) and two of four input files used to generate a concatenated “super” input file (Sample GSM1133490); the raw data provided for input consists of the two input files recovered. Importantly, FASTA sequences for both of these datasets are available as supplementary data through GEO, and we can make available upon request (rsciamma@uchicago.edu) all files in our study in the ELAND-extended alignment format. Please note that GEO no longer supports this format.

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Project description:Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated through examination of the chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1482 distinct brain cell populations, adding over 446,000 new cCREs to the most recent such annotation in the mouse genome. Raw fastq files are demultiplexed. Out of 234 samples, fastq files for 6 samples are available in NCBI under the accession number GSE126724 (CEMBA180308_3B, CEMBA180312_3B, CEMBA180226_1A, CEMBA180227_1A, CEMBA180305_2B, CEMBA180306_2B). Processed data are SnapATAC2 (<= 2.4.0) h5ad files per sample, with raw fragments and 500-bp bmat. Important note: - Due to the break changes in SnapATAC2 >= 2.5.0, the data can not be handled rightly in SnapATAC2 >= 2.5.0. - In GSE246791_wmb_enhancer.tar.gz, the subclass-specific bedpe files can be downloaded here: https://catlas.org/catlasv1/wholemousebrain/data/pdc/.

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The influence of nt-LNA on cell composition and phenotypees in the atherosclerotic lesion.

Project description:Raw fastq files from paired-end, Illumina-based sequencing on NovaSeq6000

2021-11-01 | GSE160791 | GEO

High-throughput RNA Sequencing of THP-1 macrophages treated with or without native LDL for 24h.

Project description:Raw fastq files from paired-end, Illumina-based sequencing on NovaSeq6000

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Project description:Metagenomics sequencing raw fastq files

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Peptide design by optimization on a data-parameterized protein interaction landscape

Project description:We applied the high-throughput interaction assay SORTCERY to measure thousands of protein-peptide binding affinities and used the data to parameterize models of the peptide-binding landscape for three members of the Bcl-2 family of proteins. We applied the models to design peptides that bound with high affinity and specificity to just one of Bcl-xL, Mcl-1, or Bfl-1. We designed additional peptides that bound selectively to two out of three of these proteins. The raw data provided are the multiplexed fastq files that serve as inputs to our analysis pipeline. Additional detail is available in our corresponding publication and at the following github repository. https://github.com/KeatingLab/sortcery_design

2018-10-01 | GSE118147 | GEO

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