Wednesday, May 17, 2017

day3, 20170517Wed Jackson Lab, Galaxy, IGV,

=> Paola Vera-Licona
gene network

time series gene expression data -> network

structure-based control of signaling networks (optimization of interaction? )

HER2-positive breast cancer

BiNoM           -> geneXplain --> OCSANA
gene expression -> list TFs ---> mapping pathways + master regulator --> identify optimal combination of intervention from network analysis

candidate genes with p-values
pick largest connected component
using random sampling permutation to evaluate the choice of p-value cutoff.

Using annotated pathway to build a directed nework for intervention analysis and prediction.

How drugble? Drug reposition?


=> Reinhard Laubenbacher

Karl Broman, Reproducible research (should added to my REU bootcamp training).

biostatistics and medical informatics

IGV: need *bam file for alignment, *bai file for index. 

vcf file can be visualized in IGV or Ensembl Variant Effect Predictor.

Usually, large genes tend to have more mutations than small genes. Genes with repetitive elements tend to have more mutations.

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