Posts Tagged ‘singlecell’
Everyday Scientist » deconvoluting deconvolving
January 13, 2018A survey of human brain transcriptome diversity at the single cell level
June 27, 2017Brain #transcriptome diversity at the single cell level
http://www.PNAS.org/content/112/23/7285 Has useful gene-exp. profiles of specific neural cell types
has profiles for 185 biomarker genes for 6 cell types
Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors : Nature Genetics : Nature Research
May 6, 2017http://www.nature.com/ng/journal/v49/n5/full/ng.3818.html
Ref component analysis..of transcriptomes, by @Robson_Paul &co http://www.Nature.com/ng/journal/v49/n5/full/ng.3818.html Clustering similarity of samples to tissue references
Aging increases cell-to-cell transcriptional variability upon immune stimulation | Science
April 21, 2017#Aging increases cell-to-cell transcriptional variability upon immune stimulation, but just for 225 up-reg. genes http://science.ScienceMag.org/content/355/6332/1433
Single-Cell Co-expression Analysis Reveals Distinct Functional Modules, Co-regulation Mechanisms and Clinical Outcomes
July 2, 2016#SingleCell Coexpression…Reveals Distinct Func. Modules [v clustering bulk RNAseq]… & Clinical Outcomes [in GBM]
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004892
QT:{{”
We found that the co-expressed genes observed in single cells and bulk tumors have little overlap and show distinct characteristics. The co-expressed genes identified in bulk tumors tend to have similar biological functions, and are enriched for intrachromosomal
interactions with synchronized promoter activity. In contrast, single-cell co-expressed genes are enriched for known protein-protein interactions, and are regulated through interchromosomal interactions. “}}
Cell lineage analysis in human brain using endogenous retroelements. – PubMed – NCBI
May 7, 2016Cell-lineage analysis in human #brain using endogenous retroelements http://www.cell.com/neuron/abstract/S0896-6273(14)01137-4 Tracing L1 insertions w/ #singlecell sequencing
Using single cell WGS of 16 neuronal cells the authors investigated two somatic insertions of L1Hs elements in an adult human brain. Using these results the authors infer that L1 somatic insertions are infrequent and ALUs and SVAs somatic retrotransposition are extremely rare. Assessing two L1Hs insertions in 32 samples across different regions of this same adult brain, they found that while one insertion was spatially restricted (2x1cm region), the other was found across all samples of the adult brain (but not found in other tissues such as Heart, Lung, etc.). The more restricted one (L1Hs#1) is inferred to have happened during the Fetal stage (first trimester) while the broader one happened earlier, approximately 2 weeks
post-fertilization. Overall the paper is clear, concise, and simple. It answers an interesting biological question: Can retrotransposition be used as a marker of cell clonal expansion? It does, although the retrotransposition frequency is very small and SNVs might support better results for the same analysis due to their higher frequency..
Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution : Nature : Nature Publishing Group
January 23, 2016Dynamics of genomic clones in breast #cancer PDX at #singlecell resolution http://www.nature.com/nature/journal/v518/n7539/full/nature13952.html Extensive trees of samples & some WGS
Peter Eirew,
Adi Steif,
Jaswinder Khattra,
Gavin Ha,
…
Jazmine Brimhall,
Arusha Oloumi,
Tomo Osako
et al.
Nature 518, 422–426 (19 February 2015) doi:10.1038/nature13952
Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells | Science
January 13, 2016#SingleCell #RNASeq Reveals Dynamic, Random Monoallelic Gene Expression, occurring in ~20% of genes in mice cells
http://science.sciencemag.org/content/343/6167/193.abstract
Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells : Nature Biotechnology : Nature Publishing Group
November 14, 2015Heterogeneity in #singlecell RNAseq…hidden subpopulations by @OliverStegle lab http://www.nature.com/nbt/journal/v33/n2/full/nbt.3102.html scLVM corrects for cell cycle phase
Buettner, Florian, Kedar N. Natarajan, F. Paolo Casale, Valentina
Proserpio, Antonio Scialdone, Fabian J. Theis, Sarah A. Teichmann,
John C. Marioni, and Oliver Stegle. "Computational analysis of
cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals
hidden subpopulations of cells." Nature biotechnology 33, no. 2
(2015): 155-160.
Single-cell ChIP-seq
October 23, 2015#Singlecell ChIPseq reveals…subpopulations defined by chromatin statehttp://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3383.html Sparse data: on order of 1K uniq. reads/cell
http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3383.html
