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| Status |
Public on Dec 23, 2017 |
| Title |
MED_s90 |
| Sample type |
SRA |
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| Source name |
Single dendritic cell
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| Organism |
Homo sapiens |
| Characteristics |
cell type: DC
exposure: MED
exposuretime: 24H
donor: P1
platebatch: 11
viabilitysortbatch: no
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| Extracted molecule |
total RNA |
| Extraction protocol |
Single cells lysates were put directly into SPRI
[Trombetta et al CPMB 2014]
[Single cell Whole Transcriptome Amplification]: Following sorting, 96-well plates of single cells were whole transcriptome amplified as described in Trombetta et al. Lysed cell samples were cleaned with 2.2x volume AMPure XP SPRI beads (Beckman Coulter). Reverse transcription and PCR were then performed on the samples. For population samples total RNA was isolated using a column (RNeasy plus Micro RNA kit; Qiagen) following manufacturer’s instructions. Two μL of extracted RNA were added to 8 μL of water and cleaned with 2.2x volume beads. While transcriptome amplification wa performed on these samples analogous to the amplification of the single cell samples.
[Preparation of cDNA Libraries for RNAseq]: WTA products were diluted to a concentration of 0.1 to 0.4 ng/μL and tagmented and amplified using Nextera XT DNA Sample preparation reagents (Illumina). Tagmentation was performed according to manufacturer’s instructions, modified to use ¼ the recommended volume of reagents, extended tagmentation time to 10 minutes and extended PCR time to 60s. PCR primers were ordered form Integrated DNA Technologies. Nextera products were then cleaned twice with at 0.9x volume of SPRI beads and eluted in water. The library was quantified using Qubit and analyzed using a high sensitivity DNA chip. The library was diluted to 2.2 pM and sequenced on a NextSeq 500 (Illumina)
Indexing length: 8bp
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
norm_tpm.csv
s90
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| Data processing |
[Single-Cell RNA-Seq Expression Quantification] RNA-seq reads were aligned to the RefSeq hg38 transcriptome (GRCh38.2) using Bowtie2 (Langmead et al., 2012). The resulting transcriptome alignments were processed by RSEM to estimate the abundance (expected counts and TPM) of RefSeq transcripts (Li et al., 2011).
[Single-Cell Filtering and Gene Filtering] For each single-cell library we computed transcriptome alignment metrics using FastQC, Picard tools, and in-house scripts. Computed metrics included: (1) number of reads, (2) number of aligned reads, (3) percentage of aligned reads, (4) number of duplicate reads, (5) primer sequence contamination, (6) average insert size (7) variance of insert size, (8) sequence complexity, (9) percentage of unique reads (10) ribosomal read fraction, (11) coding read fraction, (12) UTR read fraction, (13) intronic read fraction, (14) intergenic read fraction, (15) mRNA read fraction, (16) coefficient of variation of coverage, (17) mean 5’ coverage bias, (18) mean 3’ coverage bias, and (19) mean 5’ to 3’ coverage bias.
We excluded from further analysis libraries with poor values for number of aligned reads (< 28,840), the percentage of aligned reads (< 15%), or the percentage of detected transcripts (< 33% of protein-coding genes expressed at >100 TPM in at least 10% of samples). Out of 2489 initial samples, only 393 samples passed.
Following cell filtering, genes were retained for downstream analysis if they were annotated as protein-coding, and expressed at levels greater than 100 TPM in at least 5 high-quality cells.
[Single-Cell Data Normalization] In order to normalize TPM data, we applied full-quantile normalization method, restoring original zero values to zero following normalization.
Genome_build: GRCh38.2
Supplementary_files_format_and_content: TPMs
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| Submission date |
Dec 22, 2017 |
| Last update date |
Dec 27, 2017 |
| Contact name |
Michael B Cole |
| E-mail(s) |
[email protected]
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| Organization name |
UC Berkeley
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| Street address |
378 Stanley Hall
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| City |
Berkeley |
| State/province |
CA |
| ZIP/Postal code |
94720 |
| Country |
USA |
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| Platform ID |
GPL18573 |
| Series (2) |
| GSE80212 |
A Reproducibility-Based Computational Framework Identifies An Inducible, Enhanced Antiviral Dendritic Cell State In HIV-1 Elite Controllers (scRNA-Seq) |
| GSE108445 |
A Reproducibility-Based Computational Framework Identifies An Inducible, Enhanced Antiviral Dendritic Cell State In HIV-1 Elite Controllers |
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| Relations |
| BioSample |
SAMN08226603 |
| SRA |
SRX3513059 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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