Casey Hanson
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View article: Polyclonal origins of human premalignant colorectal lesions
Polyclonal origins of human premalignant colorectal lesions Open
Cancer is generally thought to be caused by expansion of a single mutant cell 1 . However, analyses of early colorectal cancer lesions suggest that tumors may instead originate from multiple, genetically distinct cell populations 2,3 . Det…
View article: Multiomic analysis of familial adenomatous polyposis reveals molecular pathways associated with early tumorigenesis
Multiomic analysis of familial adenomatous polyposis reveals molecular pathways associated with early tumorigenesis Open
Familial adenomatous polyposis (FAP) is a genetic disease causing hundreds of premalignant polyps in affected persons and is an ideal model to study transitions of early precancer states to colorectal cancer (CRC). We performed deep multio…
View article: Multi-omic Analysis of Familial Adenomatous Polyposis Reveals Molecular Pathways and Polyclonal Spreading Associated with Early Tumorigenesis
Multi-omic Analysis of Familial Adenomatous Polyposis Reveals Molecular Pathways and Polyclonal Spreading Associated with Early Tumorigenesis Open
Familial adenomatous polyposis (FAP) is a genetic disease causing hundreds of premalignant polyps in affected patients, leading to colorectal cancer (CRC), and is an ideal model to study early transition to CRC. We performed deep multi-omi…
View article: Additional file 5 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes
Additional file 5 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes Open
Additional file 5. Predicted mediators of JunD influence on CRC progression. Table 1. contains the model-predicted targets of JunD (top 500 RPOR scores in down-analysis) that were differentially expressed upon knock-down of JunD (p-value <…
View article: Additional file 2 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes
Additional file 2 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes Open
Additional file 2. Gene set characterization. Gene set characterization of the DE genes between early and late stages. The downregulated genes are significantly enriched for cancer-related gene signatures from mSigDB.
View article: Additional file 4 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes
Additional file 4 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes Open
Additional file 4: Table S1. List of HCT116 TFs and their corresponding files obtained from ENCODE portal ( https://www.encodeproject.org/ ). Table S2. Interpretations of the different combinations of signs of TF and histone mark change we…
View article: Additional file 3 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes
Additional file 3 of An integrated multi-omics approach to identify regulatory mechanisms in cancer metastatic processes Open
Additional file 3. Annotated list of genes with SNVs that exhibited significant shifts in alternative allele frequency between M0 and M6.
View article: Additional file 2: of Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response
Additional file 2: of Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response Open
The file includes seven supplementary tables. All supplementary tables are included as sheets in this Excel file. Legends for these tables are provided here. (1) Table S1. The number of motifs for each TF. (2) Table S2. Accuracy values (co…
View article: Additional file 3: of Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response
Additional file 3: of Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response Open
Transcription factor binding motifs. We obtained 239 PWMs from three different data sources: (1) factor book motifs processed by ENCODE UCSC; (2) motifs downloaded from Factorbook; (3) HOCOMOCO Human (v10) motifs. STAP models are trained s…
View article: Principled multi-omic analysis reveals gene regulatory mechanisms of phenotype variation
Principled multi-omic analysis reveals gene regulatory mechanisms of phenotype variation Open
Recent studies have analyzed large-scale data sets of gene expression to identify genes associated with interindividual variation in phenotypes ranging from cancer subtypes to drug sensitivity, promising new avenues of research in personal…
View article: Principled Multi-Omic Analysis Reveals Gene Regulatory Mechanisms Of Phenotype Variation
Principled Multi-Omic Analysis Reveals Gene Regulatory Mechanisms Of Phenotype Variation Open
Recent studies have analyzed large scale data sets of gene expression to identify genes associated with inter-individual variation in phenotypes ranging from cancer sub-types to drug sensitivity, promising new avenues of research in person…
View article: Computational discovery of transcription factors associated with drug response
Computational discovery of transcription factors associated with drug response Open
This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulato…