{"database": "metadata", "table": "run_metadata", "rows": [[55484, "SRR10510896", "SRX7199567", "SRS5705122", "SRP231168", "PRJNA591000", "RNA seq analysis of transcriptomic changes in macrophage lineage cells post acute neural injury in larval zebrafish", "GSE140810", "Transcriptome Analysis", "Both brain resident microglia and peripheral macrophages are important cellular effectors of the inflammatory response to neural injury. They respond to neural injury by secreting a wide range of effector molecules including cytokines  chemokines and neurotrophic factors. To identify additional secreted signalling molecules  we used RNA seq gene expression profiling to detect changes in the transcriptome of macrophage lineage cells post acute neural injury in larval zebrafish. GO term analysis was then used to analyse the list of differentially expressed genes and identify secreted signalling molecules among them. Overall design: The transcriptomes of FACS purified macrophage lineage cells from mpeg1:GFP transgenic zebrafish larvae with or without xxx injury were compared.", null, "pubmed:32366533", null, "Injury 5", "GSM4186880", null, "tissue:Macrophage lineage cells|age:4 dpf", "Injury 5", "Reads were trimmed using Cutadapt version cutadapt 1.9.dev2. Reads were trimmed for quality at the 3\u2019 end using a quality threshold of 30 and for adapter sequences of the TruSeq DNA Nano kit AGATCGGAAGAGC. Reads post trimming were required to have a minimum length of 35. The reference used for mapping was the Danio rerio GRCz10 genome from Ensembl. The annotation used for counting was the standard GTF format annotation for that reference annotation version 84. Reads were aligned to the reference genome using STAR version 2.5.2b specifying paired end reads and the option   outSAMtype BAM Unsorted. All other parameters were left at default. Reads were assigned to features of type \u2018exon\u2019 in the input annotation grouped by gene id in the reference genome using featureCounts version 1.5.1. Strandness was set to \u2018reverse\u2019 and a minimum alignment quality of 10 was specified. Gene names and other fields were derived from input annotation and added to the count/expression matrices. The raw counts table was filtered to remove genes consisting predominantly of near zero counts  filtering on counts per million CPM to avoid artefacts due to library depth. Specifically  a row of the expression matrix was required to have values greater than 0.1 in at least 3 samples  corresponding to the smallest sample group as defined by Group  once any samples were removed where applicable. Reads were normalised using the weighted trimmed mean of M values method  passing \u2018TMM\u2019 as the method to the calcNormFactors method of edgeR. A principal components analysis was undertaken on normalised and filtered expression data to explore observed patterns with respect to experimental factors. The cumulative proportion of variance associated with each factor was used to study the level of structure in the data  while associations between continuous value ranges in principal components and categorical experimental factors was assessed with an ANOVA test. Three samples Injury 3  Injury 5 and Injury 6 were identified as having high duplication rate and low mapping rate during bioinformatics QC. The high levels of variation in these three samples caused signal from the remaining samples to be overwhelmed  and it was clear that inclusion of the poor quality samples would negatively affect the results of the analysis. In summary samples Injury 3  Injury 5 and Injury 6 were removed  and filtering and normalisation re performed  prior to generation of subsequent plots and downstream analysis. Differential analysis was carried out with edgeR version 3.20.1. Fold changes were estimated as per the default behaviour of edgeR  to avoid artefacts which occur with empirical calculation. Statistical assessment of differential expression was carried out with the quasi likelihood QL F test. Genome build: GRCz10 Supplementary files format and content: A comma separated value file of normalised gene wise counts  gene wise differential expression log fold changes and false discovery rates for every sample passed to downstream analysis.", "Macrophage lineage cells", "Neural injury was induced in mpeg1:GFP transgenic zebrafish larvae at 4 dpf by piercing the optic tectum with a fine metal pin. At 2 xxx post injury hpi  sham and injured larvae were anaesthesised  larval heads were transected  the tissue was homogenised  and GFP+ cells were isolated from the resulting cell suspension using FACS. Sorted cells from about 180 larvae were used per sample. Six samples each were generated for 'Sham' and 'Injury' experimental conditions.", "RNA was extracted from sorted cells using a RNeasy Plus Micro kit Qiagen. RNA was reverse transcribed and amplified using an Ovation RNA Seq System V2 NuGEN with an input of at least 500 ng RNA per sample. Libraries were prepared using a manual TruSeq DNA Nano gel free library kit Illumina.", null, "age:4 dpf", "GSM4186880", "GSM4186880: Injury 5; Danio rerio; RNA Seq", "GSM4186880", null, "1", "RNA was extracted from sorted cells using a RNeasy Plus Micro kit Qiagen. RNA was reverse transcribed and amplified using an Ovation RNA Seq System V2 NuGEN with an input of at least 500 ng RNA per sample. Libraries were prepared using a manual TruSeq DNA Nano gel free library kit Illumina.", "GEO Accession:GSM4186880", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP231168", null, null, "180809_A00291_0059_BH3FLKDRXX_2_11398HL0011L01_1.fastq.gz 180809_A00291_0059_BH3FLKDRXX_2_11398HL0011L01_2.fastq.gz", "fastq fastq", 3104558400.0, 31045584.0, "GSM4186880 r1", "0:50 1:50", "A:787529128;C:520514424;G:755538210;T:1040764721;N:211917", 50, 50, null, null, 787529128, 520514424, 755538210, 1040764721, 211917, "SRX7199567", "SRS5705122", "SRA1000323", "GEO", "Centre for Discovery Brain Sciences, University of Edinburgh", 2, 0.71708, 0.6862, 0.33746, 0.32646, 0.97104, 0.97195, 0.57901, 0.57237, 50, 50, "B", "B", "biological fallback assumption", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "trueseq", "bulk", "unknown", "unknown", null, "United Kingdom", "2019-11-21", "Larval", "Larval", "Blood", "Hematopoietic System"]], "columns": ["rowid", "run.accession", "experiment.accession", "sample.accession", "study.accession", "bioproject", "study.title", "study.alias", "study.type", "study.abstract", "study.attributes", "study.PMIDs", "sample.description", "sample.title", "sample.alias", "sample.centername", "sample.attributes", "GEOsample.title", "GEOsample.dataprocessing", "GEOsample.source", "GEOsample.treatmentprotocol", "GEOsample.extractprotocol", "GEOsample.growthprotocol", "GEOsample.characteristics", "GEOsample.accession", "experiment.title", "experiment.alias", "experiment.library_name", "experiment.design_description", "experiment.library_construction_protocol", "experiment.attributes", "experiment.library_strategy", "experiment.library_source", "experiment.library_selection", "experiment.library_layout", "experiment.platform", "experiment.instrument_model", "experiment.spot_descriptor", "experiment.study_ref", "run.title", "run.attributes", "run.filename", "run.semantic_name", "run.total_bases", "run.total_spots", "run.alias", "run.read_lengths", "run.base_counts", "run.r1_length", "run.r2_length", "run.r3_length", "run.r4_length", "run.Acount", "run.Ccount", "run.Gcount", "run.Tcount", "run.Ncount", "run.experiment", "run.pool_member", "submission.accession", "submission.srasource", "submission.bioprojectsource", "seqdetective.n_mates", "seqdetective.mapping_rate.mate1", "seqdetective.mapping_rate.mate2", "seqdetective.nofeature_rate.mate1", "seqdetective.nofeature_rate.mate2", "seqdetective.sparsity.mate1", "seqdetective.sparsity.mate2", "seqdetective.pos_strand_rate.mate1", "seqdetective.pos_strand_rate.mate2", "seqdetective.readlen.mate1", "seqdetective.readlen.mate2", "seqdetective.judgement.mate1", "seqdetective.judgement.mate2", "seqdetective.judgement.reason", "platform_family", "instrument_generation", "read_bias", "selection_class", "prep_kit", "sc_or_bulk", "tech_class", "technology", "tech_variant", "submission.bioprojectsource.country", "earliest_date", "devstage_curation", "devstage_curation_coarse", "tissue_curation", "tissue_curation_coarse"], "primary_keys": ["rowid"], "primary_key_values": ["55484"], "units": {}, "query_ms": 8.242780997534283}