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Following a change to our organizational structure effective April 1, 2026, this division has been renamed from the "Database Center for Life Science, Joint Support-Center for Data Science Research" to the "Database Division for Life Science (DBCLS), BioData Science Initiative (BSI), National Institute of Genetics (NIG)". Where the former name still appears in the guidelines, please read it as the new name.

Dataset ID

JGAD000755

Type of data
NGS (RNA-seq)
Access criteria
Controlled-access (Type I)
Total data volume
36.3 MB
File formats
  • TXT
Research
hum0214
Date published
2024-02-14
Date modified
2024-02-14

Analysis method

RNA-seq

Materials and participants
Rheumatoid Arthritis (ICD10: M0690): 19 cases
Systemic Lupus Erythematosus (ICD10: M329): 62 cases
Idiopathic Inflammatory Myopathy (ICD10: M339, M332): 40 cases
64 healthy controls
  • Health status
    Healthy
Disease
  • Rheumatoid Arthritis
  • Systemic Lupus Erythematosus
  • Idiopathic Inflammatory Myopathy
Sample description
Total RNAs extracted from 9 immune cell subsets (Naive_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, ThA)
  • Tissue
    CD4+ T cell, Peripheral blood, T cell, Treg cell
Sample provider
N/A
Experimental method
RNA-seq
Target
N/A
Reagent kit
SMART-Seq v4 Ultra Low Input RNA Kit
Fragmentation
SMART-seq v4 Ultra Low Input RNA Kit
Platform
Illumina HiSeq 2500
Read type
Paired-end
Read length
100 bp
Reference genome
GRCh38
Mapping
STAR (GRCh38)
QC and filtering
From sequenced reads, adaptor sequences were trimmed using cutadapt (v1.16). In addition, 3′- ends with low-quality bases (Phred quality score < 20) were trimmed using the fastx-toolkit (v0.0.14). Reads containing more than 20% low-quality bases were removed. Subsequently, reads were aligned against the GRCh38 reference sequence using STAR (v2.5.3) in two-pass mode with Gencode version 27 annotations. We excluded samples with uniquely mapped read rates < 90% (with the exception of < 70% for plasmablasts and <85% for the other B cell subsets) or unique read counts < 6 × 10^6. Expression was quantified using HTSeq (v 0.11.2.). For QC of the expression data, in each cell population, we filtered low count genes (< 10 in > 90% of samples), normalized between samples with a trimmed mean of M values (TMM) implemented in edgeR software, converted to log-transformed count per million (CPM), removed batch effects using ComBat software and computed inter-sample Spearman's correlations of expression levels between each sample and the remaining samples from the same cell subset. We excluded samples with mean correlation coefficients less than 0.9.
Gene count
26,353
Processed data type
Count data