Trypo_round2_dataset - samples
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ABSTRACT:
PROVIDER: EGAD00001011666 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:TrypanoGen+ phenotype data containing 183 samples from DRC, Malawi and Uganda.
| EGAD00001011348 | EGA
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
Project description:Raw RNAseq data (fastq) files that were analyzed for circadian changes in RNA ribosome binding. The numbers in the file names (00 - 44) represent circadian time (0 to 44 hours in constant dark and constant temperature). Two separate sets of samples (independent biological replicates) were collected over a 44-hour period of time.
2021-09-06 | GSE183282 | GEO
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.
2013-05-04 | GSE46608 | GEO
Project description:Remarkably, tens of thousands of piwi-interacting RNAs (piRNAs) arise from a minimal number of discrete clustered regions in many organisms. However, it remains unclear if organization into these domains contributes to the highly coordinated, germline-specific expression of these small RNAs. Here, we show that SNPC-4, the DNA-binding subunit of the small nuclear RNA activating protein complex (SNAPc), binds piRNA clusters in a germline-specific manner and is required for global piRNA expression in C. elegans. Within piRNA domains, SNPC-4 not only binds at discrete sites through its established sequence motif, but also exhibits widely distributed binding across the region. Intriguingly, discrete peaks are not found at every piRNA, but instead occur frequently at Pol III-occupied tRNA genes, which have been previously implicated in chromatin organization. Given its unique binding pattern, we suggest that SNPC-4 promotes robust piRNA expression by establishing a permissive chromatin environment at clusters specifically in the germ line. This data submission includes a total of 11 ChIP-seq samples and 2 RNA-seq samples. The ChIP-seq samples include six timecourse samples (Emb-YA) and three tissue-specific samples (WA, GL, SO) for one factor called SNPC-4 (previously called GEI-11). The remaining two ChIP-seq samples are for pol II (AMA-1) and pol III (RPC-1) at one developmental stage. All of these samples were done in replicate, with inputs, yielding at least four sequencing files per sample. Some of the ChIP-seq samples already have fastq files submitted to GEO: (SNPC-4 EMB _GSE48744: GSM1183805, GSM1183806, GSM1183807, GSM1183808), (SNPC-4 L1_GSE48702: GSM1183629, GSM1183630, GSM1183631, GSM1183632), (SNPC-4 L2_GSE37809: GSM928364, GSM928365, GSM928366, GSM928367), (SNPC-4 L3_GSE35276: GSM864851, GSM864852, GSM864853, GSM864854), and (AMA-1_GSE15535: GSM389309, GSM389310, GSM389312, GSM389313). We are submitting fastq files for the remaining ChIP-seq datasets: SNPC-4 L4 - 4 files, SNPC-4 YA - 5 files, SNPC-4 WA - 4 files, SNPC-4 GL - 4 files, SNPC-4 SO - 4 files, and RPC-1 WA - 5 files. Thus we are submitting an additional 26 fastq files. Additionally, we are submitting processed files for all 11 datasets, consisting of one normalized file for the combined duplicate IP and one normalized file for the input sequence. In the case of the three tissue-specific samples for SNPC-4, we are submitting an additional processed (but not normalized) file that represents the IP data with input-subtracted. Thus, we are submitting a total of 25 processed files. NOTE: The processed files for the ChIP-seq samples that already have fastq files submitted to GEO (SNPC-4 EMB _GSE48744, etc.) are linked below as supplementary files at the foot of the Series record. The RNA-seq samples represent one control (control_RNAseq) and one treatment (SNPC-4(RNAi)_RNA-seq)and were not duplicated. We are submitting one fastq file for each, as well as one processed data file for each, for a total of 2 fastq and 2 processed data files.
2014-11-17 | E-GEOD-53412 | biostudies-arrayexpress
Project description:This submission consists of processed single-cell RNA-seq data of knockout village samples, provided as filtered feature–barcode matrices generated using Cell Ranger v7.1.0 with default parameters. We previously deposited the same biological samples and data processed by STAR under GEO accession GSE288587. The corresponding raw FASTQ files are available in ENA under accession ERP168459. The supplementary file (reanalysis_samples.xlsx) provides a reference table linking each sample in this submission to its corresponding GSM in GSE288587, which contains the detailed experimental descriptions of culture information, genotypes, and differentiation stages.
2025-12-12 | GSE313516 | GEO