Posts Tagged ‘funseq’

Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data | Nature Genetics

March 18, 2018

Fast, scalable prediction of deleterious #noncoding variants from functional & population genomic data
https://www.Nature.com/articles/ng.3810 LINSIGHT, by @ASiepel et al., combines DNAse & conservation information

Yi-Fei Huang, Brad Gulko & Adam Siepel
Nature Genetics 49, 618–624 (2017)
doi:10.1038/ng.3810
Published online:
13 March 2017

Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma | Nature Genetics

February 11, 2018

https://www.nature.com/articles/ng.3861?WT.ec_id=NG-201706&spMailingID=54145295&spUserID=MTc2NTYxNjY4OQS2&spJobID=1164335784&spReportId=MTE2NDMzNTc4NAS2

Journal Club Paper

June 18, 2017

Zhou, J. and Troyanskaya, O.G. (2015). Predicting effects of noncoding variants with deep learning–based sequence model. Nature Methods, 12, 931–934.

Predicting (& prioritizing) effects of noncoding variants w. [DeepSEA] #DeepLearning…model
https://www.Nature.com/nmeth/journal/v12/n10/full/nmeth.3547.html Trained w #ENCODE data

PLOS Computational Biology: PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions

October 9, 2016

PredictSNP2: A Unified Platform http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004962 Ensembles many scores for the impact of non-coding variants, including #FunSeq

PETModule: a motif module based approach for enhancer target gene prediction : Scientific Reports

September 17, 2016

PETModule…enhancer-target-gene prediction
http://www.nature.com/articles/srep30043 Compares activity
correlations against a Hi-C/ChIA-PET gold std.

GERV: a statis,tical method for generative evaluation of regulatory variants for transcription factor binding

July 23, 2016

GERV: stats method for generative evaluation of regulatory variants
for TF binding http://bioinformatics.oxfordjournals.org/content/early/2015/11/05/bioinformatics.btv565 Predicts effect of #allelic SNPs

GERV: a statistical method for generative evaluation of regulatory ariants for transcription factor binding

> Haoyang Zeng
> Tatsunori Hashimoto
> Daniel D. Kang
> David K. Gifford

Journal Club

July 23, 2016

Basset: #DeepLearning the regulatory code w/…NNs by @noncodarnia lab http://genome.cshlp.org/content/early/2016/05/03/gr.200535.115 Has score for all possible SNVs in the genome

“Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks”

GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding

June 21, 2016

http://bioinformatics.oxfordjournals.org/content/early/2015/11/05/bioinformatics.btv565

GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding

Haoyang Zeng
Tatsunori Hashimoto
Daniel D. Kang
David K. Gifford

Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq

February 21, 2015

Human & mouse [mRNA] #methylomes revealed by m6A-seq http://www.nature.com/nature/journal/v485/n7397/full/nature11112.html Conservation across species & conditions (for most sites)

Dan Dominissini,
Sharon Moshitch-Moshkovitz,
Schraga Schwartz,

Rotem Sorek
& Gideon Rechavi

Nature 485, 201–206 (10 May 2012) doi:10.1038/nature11112

PLOS Genetics: A Massively Parallel Pipeline to Clone DNA Variants and Examine Molecular Phenotypes of Human Disease Mutations

February 7, 2015

Massively Parallel Pipeline to Clone DNA Variants & Examine…Disease
Mutations http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004819 CloneSeq leverages NextGen sequencing

With the advance of sequencing technologies, tens of millions of genomic variants have been discovered in the human population. However, there is no available method to date that is capable of determining the functional impact of these variants on a large scale, which has increasingly become a huge bottleneck for the development of population genetics and personal genomics. Clone-seq and comparative interactome-profiling pipeline is a first to address this issue.

Can be coupled to many readouts.