Most genomes contain thousands of genes, but for most functional responses, only a subset of those genes are relevant. To facilitate many single-cell RNASeq (scRNASeq) analyses the set of genes is ...often reduced through feature selection, i.e. by removing genes only subject to technical noise.
We present M3Drop, an R package that implements popular existing feature selection methods and two novel methods which take advantage of the prevalence of zeros (dropouts) in scRNASeq data to identify features. We show these new methods outperform existing methods on simulated and real datasets.
M3Drop is freely available on github as an R package and is compatible with other popular scRNASeq tools: https://github.com/tallulandrews/M3Drop.
Supplementary data are available at Bioinformatics online.
Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the ...analysis of these data, as it is used to identify putative cell types. However, there are many challenges involved. We discuss why clustering is a challenging problem from a computational point of view and what aspects of the data make it challenging. We also consider the difficulties related to the biological interpretation and annotation of the identified clusters.
Identifying cell populations with scRNASeq Andrews, Tallulah S.; Hemberg, Martin
Molecular aspects of medicine,
February 2018, 2018-02-00, 20180201, Letnik:
59
Journal Article
Recenzirano
Odprti dostop
Single-cell RNASeq (scRNASeq) has emerged as a powerful method for quantifying the transcriptome of individual cells. However, the data from scRNASeq experiments is often both noisy and high ...dimensional, making the computational analysis non-trivial. Here we provide an overview of different experimental protocols and the most popular methods for facilitating the computational analysis. We focus on approaches for identifying biologically important genes, projecting data into lower dimensions and clustering data into putative cell-populations. Finally we discuss approaches to validation and biological interpretation of the identified cell-types or cell-states.
Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows you to profile the whole transcriptome of a large number of individual cells. However, the analysis of the ...large volumes of data generated from these experiments requires specialized statistical and computational methods. Here we present an overview of the computational workflow involved in processing scRNA-seq data. We discuss some of the most common tasks and the tools available for addressing central biological questions. In this article and our companion website ( https://scrnaseq-course.cog.sanger.ac.uk/website/index.html ), we provide guidelines regarding best practices for performing computational analyses. This tutorial provides a hands-on guide for experimentalists interested in analyzing their data as well as an overview for bioinformaticians seeking to develop new computational methods.
Akt is a pro‐survival kinase frequently activated in human cancers and is associated with more aggressive tumors that resist therapy. Here, we connect Akt pathway activation to reduced sensitivity to ...chemotherapy via Akt phosphorylation of Bax at residue S184, one of the pro‐apoptotic Bcl‐2 family proteins required for cells to undergo apoptosis. We show that phosphorylation by Akt converts the pro‐apoptotic protein Bax into an anti‐apoptotic protein. Mechanistically, we show that phosphorylation (i) enables Bax binding to pro‐apoptotic BH3 proteins in solution, and (ii) prevents Bax inserting into mitochondria. Together, these alterations promote resistance to apoptotic stimuli by sequestering pro‐apoptotic activator BH3 proteins. Bax phosphorylation correlates with cellular resistance to BH3 mimetics in primary ovarian cancer cells. Further, analysis of the TCGA database reveals that 98% of cancer patients with increased BAX levels also have an upregulated Akt pathway, compared to 47% of patients with unchanged or decreased BAX levels. These results suggest that in patients, increased phosphorylated anti‐apoptotic Bax promotes resistance of cancer cells to inherent and drug‐induced apoptosis.
Synopsis
Phosphorylation of Bax at S184 by Akt converts it from pro‐ to anti‐apoptotic and confers resistance to drugs and pro‐apoptotic signalling. In patients, Akt is increased in tumours with high Bax and phosphorylation correlates with drug resistance.
Phosphorylation of Bax at residue S184 by Akt inhibits apoptosis in cancer cell lines.
Phosphorylation converts pro‐apoptotic Bax into an anti‐apoptotic protein.
Phosphomimetic Bax sequesters and thereby inactivates pro‐apoptotic BH3‐proteins.
In patients, levels of Akt and Bax are correlated and Bax phosphorylation correlates with resistance to BH3‐mimetics.
Phosphorylation of Bax at S184 by Akt converts it from pro‐ to anti‐apoptotic and confers resistance to drugs and pro‐apoptotic signalling. In patients, Akt is increased in tumours with high Bax and phosphorylation correlates with drug resistance.
Droplet-based single-cell RNA sequencing protocols have dramatically increased the throughput of single-cell transcriptomics studies. A key computational challenge when processing these data is to ...distinguish libraries for real cells from empty droplets. Here, we describe a new statistical method for calling cells from droplet-based data, based on detecting significant deviations from the expression profile of the ambient solution. Using simulations, we demonstrate that EmptyDrops has greater power than existing approaches while controlling the false discovery rate among detected cells. Our method also retains distinct cell types that would have been discarded by existing methods in several real data sets.
Over 250 million people suffer from schistosomiasis, a tropical disease caused by parasitic flatworms known as schistosomes. Humans become infected by free-swimming, water-borne larvae, which ...penetrate the skin. The earliest intra-mammalian stage, called the schistosomulum, undergoes a series of developmental transitions. These changes are critical for the parasite to adapt to its new environment as it navigates through host tissues to reach its niche, where it will grow to reproductive maturity. Unravelling the mechanisms that drive intra-mammalian development requires knowledge of the spatial organisation and transcriptional dynamics of different cell types that comprise the schistomulum body. To fill these important knowledge gaps, we perform single-cell RNA sequencing on two-day old schistosomula of Schistosoma mansoni. We identify likely gene expression profiles for muscle, nervous system, tegument, oesophageal gland, parenchymal/primordial gut cells, and stem cells. In addition, we validate cell markers for all these clusters by in situ hybridisation in schistosomula and adult parasites. Taken together, this study provides a comprehensive cell-type atlas for the early intra-mammalian stage of this devastating metazoan parasite.
PDF
