Difference between revisions of "Simpler methods for High Throughput Data analysis"

From Ilya Nemenman: Theoretical Biophysics @ Emory
Jump to: navigation, search
nemenman>Ilya
(Bibliography)
 
m (1 revision imported)
 
(No difference)

Latest revision as of 11:28, 4 July 2018

Here I collect some references for simpler analysis methods, like PCS, clustering, correlation analysis, etc. These are usually foundational papers for particular model systems, which provide great descriptive knowledge, but require better quantitative analysis to become truly predictive modeling papers.

Bibliography

  • Plants:
    1. J Keurentjes, J Fu, I Terpstra, J Garcia, G van den Ackerveken, L Snoek, A Peeters, D Vreugdenhil, M Koornneef, and R Jansen. Regulatory network construction in Arabidopsisby using genome-wide gene expression quantitative trait loci. PNAS 104, 1708–1713 (2007), PDF.
      Abstract
      Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genomewide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation in expression could be explained by expression quantitative trait loci (eQTLs). The nature and consequences of this variation are discussed based on additional genetic parameters, such as heritability and transgression and by examining the genomic position of eQTLs versus gene position, polymorphism frequency, and gene ontology. Furthermore, we developed an approach for genetic regulatory network construction by combining eQTL mapping and regulator candidate gene selection. The power of our method was shown in a case study of genes associated with flowering time, a well studied regulatory network in Arabidopsis. Results that revealed clusters of coregulated genes and their most likely regulators were in agreement with published data, and unknown relationships could be predicted.
      Comments
      How can they be allowed to say that only very few transcriptional networks of eykaryotes have been reverse-engineered? There are dozens of examples, including many from us. Otherwise, I cannot really make sense of the paper, but it looks like the method they have is quite effort-consuming, and cannot be readily applied in a system-wide fashion.
  • Burkholderia pseudomallei:
    1. F Rodrigues et al. Global Map of Growth-Regulated Gene Expression in Burkholderia pseudomallei, the Causative Agent of Melioidosis. J Bacteriol. 188:8178–8188, 2006. PDF.