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Sample GSM1657972 Query DataSets for GSM1657972
Status Public on May 20, 2015
Title healthy cortex cell 102
Sample type SRA
 
Source name Brain
Organism Homo sapiens
Characteristics tissue: cortex
cell type: endothelial
age: postnatal 37 years
c1 chip id: 1772078237
experiment_sample_name: AB_S11
Extracted molecule total RNA
Extraction protocol C1 autoprep standard protocol
C1 autoprep standard protocol, followed by clontech single cell RNA-seq for Fluidigm C1 protocol
Nextera tagmentation according to Fluidigms standard protocol for single cell RNA-seq on the C1 autoprep system.
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina NextSeq 500
 
Description Single cell from healthy human cortex
Data processing Short read trimming: Prinseq to remove short reads (-min_len 30) trim the first 10 bp on the 5’-end (-trim_left 10), trim reads with low quality on the 3’-end (-trim_qual_right 25) and filter low complexity reads (-lc_method entropy \-lc_threshold 65). We used FASTQC to determine overrepresented sequences and removed those using cutadapt (-e 0.15 –m 30). We then used Prinseq to remove orphan pairs less than 30bp in length followed by removal of nextera adapters using Trim Galore (--stringency 1).
Read alignment: reads were aligned to the hg19 genome with STAR using the following options (-outFilterType BySJout \--outFilterMultimapNmax 20 \--alignSJoverhangMin 8 \--alignSJDBoverhangMin 1 \--outFilterMismatchNmax 999 \--outFilterMismatchNoverLmax 0.04 \--alignIntronMin 20 \--alignIntronMax 1000000 \--alignMatesGapMax 1000000 \--outSAMstrandField intronMotif ).
Per-gene read assignement: aligned reads were converted to counts for every gene using HTSeq (-m intersection-nonempty \-s no).
Genome_build: hg19
Supplementary_files_format_and_content: tab-delimited text files with raw read values for each sample
 
Submission date Apr 15, 2015
Last update date May 15, 2019
Contact name Martin Enge
E-mail(s) martin.enge@ki.se
Organization name Karolinska Institute
Department Dep of Oncology-Pathology
Street address CCK, Z4
City Stockholm
ZIP/Postal code S-171 76
Country Sweden
 
Platform ID GPL18573
Series (1)
GSE67835 A survey of human brain transcriptome diversity at the single cell level
Relations
BioSample SAMN03486243
SRA SRX995962

Supplementary file Size Download File type/resource
GSM1657972_1772078237.C28.csv.gz 64.9 Kb (ftp)(http) CSV
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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