Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2
Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.
- 78 samples
- DAC: EGAC00001000551
- Technology: Illumina HiSeq 4000
- HMB DUO:0000006 (version: 2019-01-07)health or medical or biomedical researchThis data use permission indicates that use is allowed for health/medical/biomedical purposes; does not include the study of population origins or ancestry.
- RU DUO:0000014 (version: 2019-01-07)research use onlyThis data use limitation indicates that use is limited to research purposes (e.g., does not include its use in clinical care).
- PUB DUO:0000019 (version: 2019-01-07)publication requiredThis data use modifier indicates that requestor agrees to make results of studies using the data available to the larger scientific community.
- US DUO:0000026 (version: 2019-01-07)user specific restrictionThis data use modifier indicates that use is limited to use by approved users.
- IS DUO:0000028 (version: 2019-01-07)institution specific restrictionThis data use modifier indicates that use is limited to use within an approved institution.
Data access policy of sequencing data from BIOPIC, Peking University.The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application, and the authorization by EGA. In general this process will take about two weeks. In principal, any academic research institutions complying with the laws and bioethic regulation policies of China will be approved.
Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.
Study ID | Study Title | Study Type |
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EGAS00001003973 | Other |
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