run_metadata: 59291

This data as json

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
59291	SRR11806489	SRX8357867	SRS6673974	SRP262133	PRJNA633496	Single cell sequencing reveals heterogeneity effects of arsenic or/and 2 2 dichloroacetamide on zebrafish liver	GSE150751	Transcriptome Analysis	Arsenic and DBPs has been found to be one of the major risk in many regions of the world. However current understanding of thier combined toxicities are unclear. Here we used single cell RNA sequencing to provide the transcriptome heterogeneity of 13563 liver cells obtained from zebrafishes exposed to 100µg/L arsenic 300µg/L dichloroacetanilide DCAcAm and co exposure for 23 days. Five liver cell populations were identified. We found that the hepatocytes and macrophages were the main target of arsenic and DCAcAm exposure. And the hepatocytes of male and female showed a huge difference when expsoure to arsenic and DCAcAm. Overall design: Single cell RNA sequencing were adopted to learn the transcriptional variation in zebrafish liver exposure to arsenic and DCAcAm.				CK	GSM4558080		source name:liver cells\|tissue:liver single cell suspension\|age:16 wpf\|exposed pollutants:n1	CK	We use FastQC to perform basic statistics on the quality of the raw reads. Then those read sequences produced by the Illumina pipeline in FASTQ format were pre processed through Trimmomatic software which can be summarized as below:1 Remove low quality reads: scan the read with a 4 base wide sliding window cutting when the average quality per base drops below 10 SLIDINGWINDOW: 4:10 2 Remove trailing low quality or N bases below quality 3 TRAILING:3 3 Remove adapters : there are two modes to remove the adapter sequence: a. alignment with the adapter sequence the number of matching bases were greater than 7 and mismatch=2; b.when read1 and read2 overlapping base scoring greater than 30 removed non overlapping portions ILLUMINACLIP: adapter.fa: 2: 30: 7 4 Drop reads below the 26 bases long 5 Discard those reads that can not form paired The remaining reads that passed all the filtering steps was counted as clean reads and all subsequent analyses were based on this. At last we use FastQC to perform basic statistics on the quality of the clean reads. Cell Ranger uses an aligner called STAR which peforms splicing aware alignment of reads to the genome. Cell Ranger then uses the transcript annotation GTF to bucket the reads into exonic intronic and intergenic and by whether the reads align confidently to the genome. A read is exonic if at least 50% of it intersects an exon intronic if it is non exonic and intersects an intron and intergenic otherwise. For reads that align to a single exonic locus but also align to 1 or more non exonic loci the exonic locus is prioritized and the read is considered to be confidently mapped to the exonic locus with MAPQ 255. Cell Ranger further aligns exonic reads to annotated transcripts looking for compatibility. A read that is compatible with the exons of an annotated transcript and aligned to the same strand is considered mapped to the transcriptome. If the read is compatible with a single gene annotation it is considered uniquely confidently mapped to the transcriptome. Only reads that are confidently mapped to the transcriptome are used for UMI counting. Cell Ranger takes as input the expected number of recovered cells N see expect cells. Let m be a robust estimate of the maximum total UMI counts taken as the 99th percentile of the top N barcodes by total UMI counts. All barcodes whose total UMI counts exceed m/10 are called as cells. This is performed separately for each GEM group library and if the reference contains multiple genomes for each genome. Genome build: Danio rerio Ensemble 91 Supplementary files format and content: gene barcode expression matrix	liver cells	Exposure solutions were prepared by adding 100μg/L arsenic 300μg/L DCAcAm or both of them to culture water. The exposure solution were was replaced every 2 days. post 23 d exposure zebrafish were collected and liver were rapidly extracted on ice.	The isolated liver tissue was digested into cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell 3’ Gel Bead Chip and Library Kits 10x Genomics USA as per the manufacturer’s protocol. Libraries were sequenced on an Illumina Hiseq PE150.		tissue:liver single cell suspension\|age:16 wpf\|exposed pollutants:n1	GSM4558080	GSM4558080: CK; Danio rerio; RNA Seq	GSM4558080		1	The isolated liver tissue was digested into cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell three prime Gel Bead Chip and Library Kits 10x Genomics USA as per the manufacturer's protocol. Libraries were sequenced on an Illumina Hiseq PE150.	GEO Accession:GSM4558080	RNA-Seq	TRANSCRIPTOMIC	cDNA	PAIRED	ILLUMINA	Illumina NovaSeq 6000		SRP262133			CK_1.fq.gz CK_2.fq.gz	fastq fastq	133916231400.0	446387438.0	GSM4558080 r1	0:150 1:150	A:32477145943;C:25399997371;G:40326238358;T:35690408393;N:22441335	150	150			32477145943	25399997371	40326238358	35690408393	22441335	SRX8357867	SRS6673974	SRA1076689	GEO	Nanjing University	2	0.0	0.91836	0.0	0.02382	1.0	0.90871		0.46105	150	150	T	B	mate1 technical by mapping diff	illumina	novaseq_era	unknown	cdna_unspecified	unknown	sc	single_cell_droplet	10x		China	2020-05-18	Adult	Adult	Liver	Liver and Biliary System