# HG changeset patch # User chemteam # Date 1570466705 14400 # Node ID 24867ab16f369a718e73b6717b02a3e77f96dbc5 # Parent 994c509873db276d02dbeb858415fc2b8189d17a "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/tree/master/tools/bio3d commit 3b99f08f22b9e0c16c0a0adc82f8c16c1a25cedf" diff -r 994c509873db -r 24867ab16f36 macros.xml --- a/macros.xml Wed Apr 03 15:44:21 2019 -0400 +++ b/macros.xml Mon Oct 07 12:45:05 2019 -0400 @@ -1,14 +1,14 @@ - 2.3 + 2.3.4 - r-bio3d + r-bio3d - - + + diff -r 994c509873db -r 24867ab16f36 pca.xml --- a/pca.xml Wed Apr 03 15:44:21 2019 -0400 +++ b/pca.xml Mon Oct 07 12:45:05 2019 -0400 @@ -1,5 +1,5 @@ - Principle component analysis using Bio3D + - principal component analysis using Bio3D macros.xml @@ -62,16 +62,16 @@ label="Use singular value decomposition (SVD) instead of default eigenvalue decomposition ?" help="Default: No" /> - - + + - - - - + + + + @@ -88,13 +88,13 @@ - + - + - + @@ -122,7 +122,7 @@ **What it does** -PCA can be used to determine the relationship between statistically meaningful conformations (major global motions) +Principal component analysis (PCA) can be used to determine the relationship between statistically meaningful conformations (major global motions) sampled during the trajectory. _____ @@ -133,7 +133,7 @@ **Input** - Input file in PDB format - - Input file in dcd format + - Input file in DCD format _____ @@ -142,9 +142,9 @@ **Output** - - Image (as PNG) of the pca plot - - Image (as PNG) of the pca clusterd plot - - Image (as PNG) of the PC1 plotted on RMSF + - Image (as PNG) of the PCA plot + - Image (as PNG) of the PCA clustered plot + - Image (as PNG) of the first principal component plotted on RMSF - Tab-separated file of raw data ]]>