Posts Tagged ‘from_mrs’
Quantifying the tradeoff between sequencing depth and cell number in single-cell RNA-seq
November 2, 2019interesting perspective on cancer research in wsj + upcoming book
October 8, 2019The focus is on improving detection vs. treatment of late stage disease.
https://www.wsj.com/articles/cancer-is-still-beating-uswe-need-a-new-start-11570206319
genome-wide starr-seq + sources of experimental bias
August 12, 2018quite relevant
https://www.nature.com/articles/nmeth.4534
Resolving systematic errors in widely used enhancer activity assays in human cells
Felix Muerdter
, Łukasz M Boryń
, Ashley R Woodfin
, Christoph Neumayr
, Martina Rath
, Muhammad A Zabidi
, Michaela Pagani
, Vanja Haberle
, Tomáš Kazmar
, Rui R Catarino
, Katharina Schernhuber
, Cosmas D Arnold
& Alexander Stark
Nature Methods volume 15, pages141–149 (2018)
Inferring chromatin-bound protein complexes from genome-wide binding assays – Genome Research
February 26, 2017Inferring [w. NMF] chromatin-bound protein complexes [of TFs] from [ENCODE ChIP-seq] binding assays, by @ElementoLab
http://genome.cshlp.org/content/23/8/1295.full
Giannopoulou E, Elemento O. 2013. Inferring chromatin-bound
protein complexes from genome-wide binding assays. Genome Research, Published in Advance April 3, 2013, doi: 10.1101/gr.149419.112.
This study uses nonnegative matrix factorization (NMF) of ENCODE CHIP-seq data (transcription
factors and histone modifications) to predict complexes of
transcription factors that bind DNA
together; it then assesses how these predicted complexes regulate gene expression. It goes beyond
previous studies in that it attempts to treat the TFs as complexes rather than individuals. A handful of
the predicted complexes correspond to known regulatory complexes, e.g. PRC2, and overall, the
complexes were enriched for known protein-protein interactions. Linear regression and random forest
models were then used to predict the effects of the complexes on the expression of adjacent genes. In
both models, the complexes performed better than those predicted from a scrambled TF read count
matrix. Overall, this study provides a large set of hypotheses for combinations of TFs that may
function together, as well as potential new components of known complexes.
Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay: Cell
August 18, 2016Identification of…expr.-Modulating Variants using #MPRA, by @sabeti_lab http://www.cell.com/cell/fulltext/S0092-8674(16)30421-4 Some w. allelic skew related to PWM change
Learning the Sequence Determinants of Alternative Splicing from Millions of Random Sequences: Cell
April 24, 2016Learning the…Determinants of Alternative #Splicing [in a largely linear model] from Millions of Random Sequences
http://www.cell.com/cell/abstract/S0092-8674(15)01271-4
** Rosenberg et al Cell. 2015
Builds a model of splicing using a library of randomized sequence Also, builds a generalized model for predicting effect of a SNP in the Geuvadis RNAseq
7mer model does well with lots of data
linkstream2 microblog 