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Sample GSM4090923 Query DataSets for GSM4090923
Status Public on Mar 18, 2020
Title sample_83_T_cells_CD4
Sample type SRA
 
Source name T cells CD4
Organism Homo sapiens
Characteristics subject id: SUB35
cancer status: non-cancer
organ: blood
library: ACCEL-NGS Methyl-Seq DNA Library
Treatment protocol None
Growth protocol None
Extracted molecule genomic DNA
Extraction protocol DNA extracted using phenol-chloroform protocol after RNAse treatment. DNA was bisulfite converted with the EZ DNA methylation kit (Zymo).
For Nextera transposase-based library approach, genomic DNA was first tagmented using Nextera XT transposome and end repair was performed using 5mC. After bisulfite conversion, Illumina adapters and custom bisulfite converted adapters are attached by limited cycle PCR. Illumina TruSeq DNA Methylation Kit and ACCEL-NGS Methyl-Seq DNA Library kit were used according to the manufacturer’s instructions.
 
Library strategy Bisulfite-Seq
Library source genomic
Library selection RANDOM
Instrument model Illumina NovaSeq 6000
 
Description Bisulfite-converted DNA
Data processing Basecalls was performed using CASAVA
After trimming for low-quality bases (Phred score<30) and reads with a length <40 bp with TrimGalore, the reads were aligned to the human genome (GRCh37) using Bismark with paired end mode and default setting . For ACCEL-NGS Methyl-Seq DNA Library, as recommended by the manufacturer, 15 bp were trimmed on 5' and 3' of both reads.
Duplicate reads were removed using Picard tools and reads with more than 10% unconverted CHG or CHH cytosines were filtered out
SNP calling was performed with BisSNP using default settings, except for the maximum coverage filter set at 200. Heterozygous SNPs with less than 5 reads per allele were filtered out. In addition, SNP with multiple mapping positions were filtered out, as well as SNPs with more than one minor allele with allele frequency>0.05. or deviating significantly from Hardy-Weinberg equilibrium based on exact tests corrected for multiple tests. C/T and G/A SNPs were assessed after filtering out reads mapping to the C/T strand.
ASM calling was performed after separating the SNP-containing reads by allele using R. After Bismark methylation extractor is applied, CpG methylation calls by allele are retrieved using allele tagged read IDs. Paired reads with ambiguous SNP calling (i.e., called as REF allele on one paired end and ALT allele on the other) were discarded.
genome build: GRCh37
processed data files format and content: Processed files per sample contain difference in methylation percentage at the CpG level between the alternate and reference alleles for each SNPs associated with high confidence ASM (observed in >2 biological samples) if the given sample was informative. The columns include chromosome, start and end of the CpG (reported on positive strand), difference in methylayion percentage and SNP ID. The unique identifier in these files is the CpG coordinate AND SNP ID.
 
Submission date Sep 23, 2019
Last update date Mar 20, 2020
Contact name Benjamin Tycko
E-mail(s) bejamintycko@hackensackmeridian.org
Phone 5519963595
Organization name HUMC
Department Epigenetics
Street address 40 prospect avenue
City hackensack
State/province NJ
ZIP/Postal code 07601
Country USA
 
Platform ID GPL24676
Series (2)
GSE137879 Whole Genome Bisulfite sequencing: Allele-specific DNA methylation is increased in cancers and its dense mapping in normal plus neoplastic cells increases the yield of disease-associated regulatory SNPs
GSE137880 Whole genome bisulfite sequencing and Genome-wide targeted methyl-seq: Allele-specific DNA methylation is increased in cancers and its dense mapping in normal plus neoplastic cells increases the yield of disease-associated regulatory SNPs
Relations
BioSample SAMN12822371
SRA SRX6890847

Supplementary file Size Download File type/resource
GSM4090923_sample_83_T_cells_CD4_diff_cpg_level.txt.gz 15.2 Kb (ftp)(http) TXT
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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