scholarly journals Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1297 ◽  
Author(s):  
Saskia Freytag ◽  
Luyi Tian ◽  
Ingrid Lönnstedt ◽  
Milica Ng ◽  
Melanie Bahlo
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Gold Standard ◽  
Mononuclear Cells ◽  
Rna Seq ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Silver Standard ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Background: The commercially available 10x Genomics protocol to generate droplet-based single cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as multiple silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also running time and robustness of a dozen methods. Results: We found that Seurat outperformed other methods, although performance seems to be dependent on many factors, including the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.

scholarly journals Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1297 ◽  
Author(s):  
Saskia Freytag ◽  
Luyi Tian ◽  
Ingrid Lönnstedt ◽  
Milica Ng ◽  
Melanie Bahlo
Keyword(s):  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Gold Standard ◽  
Mononuclear Cells ◽  
Rna Seq ◽  
Sequencing Data ◽  
Peripheral Blood Mononuclear ◽  
Silver Standard ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Background: The commercially available 10x Genomics protocol to generate droplet-based single-cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as three silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also robustness of a dozen methods. Results: We found that some methods, including Seurat and Cell Ranger, outperform other methods, although performance seems to be dependent on the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this, we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.

scholarly journals Scalable full-transcript coverage single cell RNA sequencing with Smart-seq3xpress

2021 ◽  
Author(s):  
Michael Hagemann-Jensen ◽  
Christoph Ziegenhain ◽  
Rickard Sandberg
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Mononuclear Cells ◽  
Human Peripheral Blood ◽  
Cell Types ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells ◽  
Additional Protein

Plate-based single-cell RNA-sequencing methods with full-transcript coverage typically excel at sensitivity but are more resource and time-consuming. Here, we miniaturized and streamlined the Smart-seq3 protocol for drastically reduced cost and increased throughput. Applying Smart-seq3xpress to 16,349 human peripheral blood mononuclear cells revealed a highly granular atlas complete with both common and rare cell types whose identification previously relied on additional protein measurements or the integration with a reference atlas.

scholarly journals The Characteristics of Peripheral Blood Mononuclear Cells in Takayasu Arteritis by Single Cell RNA Sequencing

2021 ◽  
Author(s):  
Qing Gao ◽  
Jinge Yu ◽  
Zuoguan Chen ◽  
Yongpeng Diao ◽  
Yuqing Miao ◽  
...  
Keyword(s):  
B Cells ◽  
Nk Cells ◽  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Takayasu Arteritis ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

Objectives Takayasu Arteritis (TA) is a rare non-specific vascular inflammation and has deleterious effects on patients’ health. Recent studies have advanced in TA diagnosis and treatment, but the research on the immune cell atlas of peripheral blood is still less. For this purpose, we performed single-cell RNA sequencing (scRNA-seq) to analyze the inflammatory cell types and cell markers in TA patients’ Peripheral blood mononuclear cells (PBMCs). Methods 4 TA patients and 4 health controls were enrolled in our study from 2019.10 to 2020.5. Their PBMCs samples were collected and performed scRNA-seq. We used Seurat package (v.3.2.2) in R studio (v.3.5.3) for data analysis, and 2 tests were applied for comparing the composition ratio of each cell type by SPSS 20.0. Results CD14+ monocytes, GZMB+ NKT cells, CD56dim CD16+ NK cells, and naive B cells were significantly increased in TA patients as compared to healthy controls and the expression of THBS1, CD163, AREG, IFITM1, TXNIP, and IGHGs was elevated in the peripheral blood of TA patients. Conclusion Except CD4+ T cells, monocytes, NK cells, NKT cells, B cells also play an important role in TA pathogenesis. The elevated markers have different functions in different types of PBMCs, and they can be used as potential diagnostic markers for TA diagnosis.

scholarly journals No detectable alloreactive transcriptional responses during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells

2020 ◽  
Author(s):  
Christopher S. McGinnis ◽  
David A. Siegel ◽  
Guorui Xie ◽  
Mars Stone ◽  
Zev J. Gartner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Transcriptional Responses ◽  
Peripheral Blood Mononuclear ◽  
Single Cell Rna Sequencing ◽  
Blood Mononuclear Cells

ABSTRACTSingle-cell RNA sequencing (scRNA-seq) provides high-dimensional measurement of transcript counts in individual cells. However, high assay costs limit the study of large numbers of samples. Sample multiplexing technologies such as antibody hashing and MULTI-seq use sample-specific sequence tags to enable individual samples (e.g., different patients) to be sequenced in a pooled format before downstream computational demultiplexing. Critically, no study to date has evaluated whether the mixing of samples from different donors in this manner results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self immune antigens). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures,. Here, we compared the expression profiles of peripheral blood mononuclear cells (PBMCs) from a single donor with and without pooling with PBMCs isolated from other donors with different blood types. We find that there was no evidence of alloreactivity in the multiplexed samples following three distinct multiplexing workflows (antibody hashing, MULTI-seq, and in silico genotyping using souporcell). Moreover, we identified biases amongst antibody hashing sample classification results in this particular experimental system, as well as gene expression signatures linked to PBMC preparation method (e.g., Ficoll-Paque density gradient centrifugation with or without apheresis using Trima filtration).

Abstract MP44: A Novel And 2 Known Differentially Expressed MicroRNAs Were Identified In Peripheral Blood Mononuclear Cells Of Patients With Hypertension Associated With Metabolic Syndrome

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Olga Berillo ◽  
Kugeng Huo ◽  
Julio C Fraulob-Aquino ◽  
Chantal Richer ◽  
Na Li ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Peripheral Blood Mononuclear Cells ◽  
Immune Cells ◽  
Mononuclear Cells ◽  
Target Organ Damage ◽  
Organ Damage ◽  
Target Organ ◽  
Rna Seq ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells

Background: Hypertension (HTN) is associated with subclinical target organ damage including cardiac, vascular and kidney injury. The immune system plays a role in hypertension and target organ damage. Activation of T cells has been reported among peripheral blood mononuclear cells (PBMCs) of patients with HTN. MicroRNAs (miRNAs) are crucial post-transcriptional regulators of immune cells. Whether miRNAs play a role in the activation of immune cells in hypertension complicated by target organ damage in humans remains unknown. We aimed to address this question by identifying differentially expressed (DE) miRNAs and their mRNA targets in PBMCs of patients with hypertension complicated or not with metabolic syndrome (MetS) or chronic kidney disease (CKD). Methods: Normotensive subjects and patients with hypertension (HTN) associated or not with at least 2 other features of MetS or CKD were studied (n=15-16). PBMCs were isolated from blood, RNA extracted for small and total RNA sequencing (RNA-seq) using Illumina HiSeq-2500 and data were analyzed using a systems biology approach. MiRDeep2 was used for novel miRNAs prediction, miRNA annotation and counting. TargetScan 7.07 was used to predict DE miRNA targets with weighted context score percentile >50%. DE genes miRNAs and mRNAs were identified with fold change (FC) >1.5 and P <0.005. DE miRNAs with FC>2 and mean read count number (MRCM) >500, and with predicted targets with MRCM>300 were validated by reverse transcription-quantitative PCR (RT-qPCR). Results: DE miRNAs, mRNAs and non-coding RNAs were identified in HTN (22, 19 and 0), MetS (57, 401 and 11) and CKD (6, 26 and 2) compared to NTN. TargetScan predicted that 7 miRNAs target 3 mRNAs in NTN, 57 miRNAs target 55 mRNAs in MetS and 3 miRNAs target 2 mRNAs in CKD. DE miR-409-5p (FC: 0.54±0.10 vs 1.00±0.09, P <0.05), miR-411-5p (FC: 0.40±0.06, vs 1.00±0.11, P <0.001) and the novel miR-pl-86 (FC: 1.96±0.17 vs 1.00±0.15, P <0.05) in MetS vs NTN were validated by RT-qPCR. RNA-seq data were correlated with RT-qPCR for miR-409-5p (R 2 =0.40, P <2.4E-07, n=55), miR-411-5p (R 2 =0.55, P <1.1E-10, n=55), miR-pl-86 (R 2 =0.37, P <5.5E-07, n=56). Conclusion: This study showed that DE miR-409-5p, miR-411-5p and miR-pl-86 may play a role in HTN associated with MetS.

scholarly journals Gene-regulatory network study of rheumatoid arthritis in single-cell chromatin landscapes of peripheral blood mononuclear cells

2021 ◽  
Author(s):  
Cantong Zhang ◽  
Xiaoping Hong ◽  
Haiyan Yu ◽  
Hongwei Wu ◽  
Huixuan Xu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Single Cell ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Peripheral Blood Mononuclear ◽  
Blood Mononuclear Cells ◽  
High Resolution Map ◽  
The Impact ◽  
Accessible Chromatin

Abstract Rheumatoid arthritis is a chronic autoinflammatory disease with an elusive etiology. Assays for transposase-accessible chromatin with single-cell sequencing (scATAC-seq) contribute to the progress in epigenetic studies. However, the impact of epigenetic technology on autoimmune diseases has not been objectively analyzed. Therefore, scATAC-seq was performed to generate a high-resolution map of accessible loci in peripheral blood mononuclear cells (PBMCs) of RA patients at the single-cell level. The purpose of our project was to discover the transcription factors (TFs) that were involved in the pathogenesis of RA at single-cell resolution. In our research, we obtained 22 accessible chromatin patterns. Then, 10 key TFs were involved in the RA pathogenesis by regulating the activity of MAP kinase. Consequently, two genes (PTPRC, SPAG9) regulated by 10 key TFs were found that may be associated with RA disease pathogenesis and these TFs were obviously enriched in RA patients (p<0.05, FC>1.2). With further qPCR validation on PTPRC and SPAG9 in monocytes, we found differential expression of these two genes, which were regulated by eight TFs (ZNF384, HNF1B, DMRTA2, MEF2A, NFE2L1, CREB3L4 (var. 2), FOSL2::JUNB (var. 2), MEF2B). What is more, the eight TFs showed highly accessible binding sites in RA patients. These findings demonstrate the value of using scATAC-seq to reveal transcriptional regulatory variation in RA-derived PBMCs, providing insights on therapy from an epigenetic perspective.

Sign in / Sign up

Export Citation Format

Share Document