Update netwas.rst

docs/netwas.rst

@@ -3,15 +3,6 @@ NetWAS - Network-wide Association Study
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 Tissue-specific networks provide a new means to generate hypotheses related to the molecular basis of human disease. We developed an approach, termed network-wide association study (NetWAS). In NetWAS, the statistical associations from a standard GWAS guide the analysis of functional networks. This reprioritization method is driven by discovery and does not depend on prior disease knowledge. NetWAS, in conjunction with tissue-specific networks, effectively reprioritizes statistical associations from distinct GWAS to identify disease-associated genes, and tissue-specific NetWAS better identifies genes associated with hypertension than either GWAS or tissue-naive NetWAS.
 
-GWAS File
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-NetWAS requires as input a GWAS result file, with per-gene p-values. We suggest the versatile gene-based association study (VEGAS) system for calculating gene p-values, but we also support forge and pseq formats.
-
-* `VEGAS <http://gump.qimr.edu.au/VEGAS/>`_: versatile gene-based association study
-* `FORGE <https://github.com/inti/FORGE>`_: multivariate calculation of gene-wide p-values from Genome-Wide Association Studies Authors and Affiliations
-* `PLINK/SEQ <https://atgu.mgh.harvard.edu/plinkseq/index.shtml>`_: a library for the analysis of genetic variation data
-
-
 Method
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 NetWAS trains a support vector machine classifier using nominally significant (P < 0.01) genes as positive examples and 10,000 randomly selected non-significant (P ≥ 0.01) genes as negatives. The classifier is constructed using a tissue network relevant to a disease (e.g. kidney for hypertension), where the features of the classifier are the edge weights of the labeled examples to all the genes in the network. Genes are re-ranked using their distance from the hyperplane, which represent a network-based prioritization of a GWAS, termed NetWAS.
@@ -20,6 +11,14 @@ To calculate per-gene P values for a GWAS, we suggest the versatile gene-based a
 
 We have performed and evaluated NetWAS on six GWAS: C-reactive protein levels (lnCRP), type 2 diabetes (T2D), body mass index (BMI), hypertension (ht), alzheimer's (adni) and advanced age-related macular degeneration (advanced AMD). 
 
+GWAS File
+---------------------------------------
+NetWAS requires as input a GWAS result file, with per-gene p-values. We suggest the versatile gene-based association study (VEGAS) system for calculating gene p-values, but we also support forge and pseq formats.
+
+* `VEGAS <http://gump.qimr.edu.au/VEGAS/>`_: versatile gene-based association study
+* `FORGE <https://github.com/inti/FORGE>`_: multivariate calculation of gene-wide p-values from Genome-Wide Association Studies Authors and Affiliations
+* `PLINK/SEQ <https://atgu.mgh.harvard.edu/plinkseq/index.shtml>`_: a library for the analysis of genetic variation data
+
 Examples
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