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| Status |
Public on Sep 26, 2016 |
| Title |
human pancreatic islets, sample 4 |
| Sample type |
SRA |
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| Source name |
Female donor, age 59, BMI: 29.9
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| Organism |
Homo sapiens |
| Characteristics |
age: 59
Sex: female
bmi: 29.9
type 2 diabetes mellitus: Yes
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| Treatment protocol |
Human pancreatic islets were obtained from Prodo or NDRI and recovered in CMRLS at 37°C for 24h-48h hours after receipt. Mouse islets were prepared using gradient centrifugation and islets from the same strain were pooled, then recovered in XX for 24h.
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| Extracted molecule |
total RNA |
| Extraction protocol |
Cells were encapsulated using the inDrop platform, into droplets on ice and lysed in the 4nL microfluidic droplets using a final concentration of 0.4% NP-40. Single cell lysates were subject to reverse transcription at 50°C without purification of RNA (as previously described in Klein et al., Cell 2015).
Cells were barcoded using the inDrop platform (Klein et al., Cell 2015), which makes use of the CEL-Seq protocol for library construction Hashimshony et al., Cell Reports 2012)
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2500 |
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| Data processing |
Reads were first filtered based on presence in read 1 of two sample barcode components separated by the W1 adaptor sequence (GAGTGATTGCTTGTGACGCCTT), as previously described (Klein et al., Cell 2015)
Read 2 was then trimmed using Trimomatic (5) (version 0.32; parameters: LEADING:28 SLIDINGWINDOW:4:20 MINLEN:30).
Barcodes for each read were matched against a list of the pre-determined barcodes, and errors of up to two nucleotides mismatch were corrected. Reads with a barcode separated by more than two nucleotides from the reference list were discarded. The reads were then split into barcode-specific files for mapping and UMI filtering.
The trimmed reads were aligned using Bowtie (version 1.1.1, parameters: -n 1 -l 15 -e 80 -m 200 -best -strata -a) to the human or mouse transcriptome. The reference transcriptome was built using annotations from ENSEMBL (Homo sapiens: GRCh38.82, Mus musculus: GRCm38.84) including all annotations with "Transcript Support Levels" of 1, 2, or NA (only accepted for protein coding genes).
A custom Python and PySAM script to process mapped reads into counts of UMI-filtered transcripts per gene, as previously described (Klein et al., Cell 2015)
Genome_build: GRCh38 (human sample), GRCm38 (mouse samples)
Supplementary_files_format_and_content: Columns = gene; rows = cells. Column 1 contains cell identifier. Column 2 contains matching cell barcode. Column 3 contains cell-type assignment for analysis. Columns 4+ contain counts for each gene. Values show unique molecular identifier (UMI)-filtered counts per cell detected in the raw data. No normalization is performed.
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| Submission date |
Jul 11, 2016 |
| Last update date |
May 15, 2019 |
| Contact name |
Adrian Veres |
| Organization name |
Harvard University
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| Street address |
7 Divinity Ave
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| City |
Cambridge |
| State/province |
Massachusetts |
| ZIP/Postal code |
02138 |
| Country |
USA |
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| Platform ID |
GPL16791 |
| Series (1) |
| GSE84133 |
A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure |
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| Relations |
| BioSample |
SAMN05379705 |
| SRA |
SRX1935942 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM2230760_human4_umifm_counts.csv.gz |
4.1 Mb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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