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10.1038/nbt.3383 http://scihub22266oqcxt.onion/10.1038/nbt.3383 C4636926!4636926!26458175     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Nat+Biotechnol 2015 ; 33 (11): 1165-72 Nephropedia Template TP {{tp|p=26458175|t=2015. Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state |pdf=|usr=}}{{26458175}} gab.com Text Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state JO: Nat Biotechnol http://www.kidney.de/pget.php?&tw=1&pmid=26458175 #FOAvip Chromatin profiling provides a versatile means to investigate functional genomic elements and their regulation. However, current methods yield ensemble profiles that are insensitive to cell-to-cell variation. Here we combine microfluidics, DNA barcoding and sequencing to collect chromatin data at single-cell resolution. We demonstrate the utility of the technology by assaying thousands of individual cells, and using the data to deconvolute a mixture of ES cells, fibroblasts and hematopoietic progenitors into high-quality chromatin state maps for each cell type. The data from each single cell is sparse, comprising on the order of 1000 unique reads. However, by assaying thousands of ES cells, we identify a spectrum of sub-populations defined by differences in chromatin signatures of pluripotency and differentiation priming. We corroborate these findings by comparison to orthogonal single-cell gene expression data. Our method for single-cell analysis reveals aspects of epigenetic heterogeneity not captured by transcriptional analysis alone. Twit Text FOAVip Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state ????Nat Biotechnol http://www.kidney.de/pget.php?&tw=1&pmid=26458175 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26458175 #FOAvip English Wikipedia <ref>{{Cite pmid|26458175}}</ref> Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state #MMPMID26458175 Rotem A; Ram O; Shoresh N; Sperling RA; Goren A; Weitz DA; Bernstein BE Nat Biotechnol 2015[Nov]; 33 (11): 1165-72 PMID26458175show ga Chromatin profiling provides a versatile means to investigate functional genomic elements and their regulation. However, current methods yield ensemble profiles that are insensitive to cell-to-cell variation. Here we combine microfluidics, DNA barcoding and sequencing to collect chromatin data at single-cell resolution. We demonstrate the utility of the technology by assaying thousands of individual cells, and using the data to deconvolute a mixture of ES cells, fibroblasts and hematopoietic progenitors into high-quality chromatin state maps for each cell type. The data from each single cell is sparse, comprising on the order of 1000 unique reads. However, by assaying thousands of ES cells, we identify a spectrum of sub-populations defined by differences in chromatin signatures of pluripotency and differentiation priming. We corroborate these findings by comparison to orthogonal single-cell gene expression data. Our method for single-cell analysis reveals aspects of epigenetic heterogeneity not captured by transcriptional analysis alone. äSingle-cell ChIP-seq reveals cell subpopulations defined by chromatin (epmc).pdf DeepDyve Pubget Overpricing