Posts Tagged ‘funseq’

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

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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.

Price AL, Kryukov GV, de Bakker PI, Purcell SM, Staples J, Wei LJ, Sunyaev SR. Pooled association tests for rare variants in exon-resequencing studies. American Journal of Human Genetics (2010) 86: 832-838.

February 1, 2015

Pooled association tests for rare variants in exon-resequencing http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3032073 Simulation shows advantage of mult. rarity thresholds

Price AL, Kryukov GV, de Bakker PI, Purcell SM, Staples J, Wei LJ,
Sunyaev SR. Pooled association tests for rare variants in
exon-resequencing studies. American Journal of Human Genetics (2010)
86: 832-838.

SUMMARY

Multiple studies indicate strong association between rare variants and
resulting phenotype. This paper describes a population-genetics
simulation framework to study the influence of variant allele
frequency on the corresponding phenotype. In a prior study, causal
relationship between variants and phenotype was resolved by performing
association test on set of variants having allele frequency below a
fixed threshold. However, here it is observed that simulation
frameworks based on a variable allele frequency threshold provide
higher accuracy in association test compared to the fixed allele
frequency model. In addition, inclusion of predicted functional
effects of variants (Polyphen-2 scores) increases the accuracy of the
variable frequency threshold model. Overall, this paper describes a novel methodology, which can be
used to explore the association between rare variants and various
diseases.

Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types : Nature Genetics : Nature Publishing Group

January 8, 2015

Analysis of noncoding somatic mutations &…expression alterations http://www.nature.com/ng/journal/v46/n12/full/ng.3141.html 505 WGS variants w. RNAseq, #TCGA as of Mar ’14

all of what’s in TCGA as of spring ’14

505 TCGA WGS Somatic mutations, Expression Calls, CNA
via
https://www.synapse.org/#!Synapse:syn2882200

Orthogonal to PCAWG-607 (Alexandrov et al + 100 "public" stomach cancers)