inst/scripts/analysis/plots/rotamer_recovery/rotamer_recovery_hbond_geometry.R
In momeara/RosettaFeatures: Tools for analyzing macromolecular feature distributions with Rosetta
# -*- tab-width:2;indent-tabs-mode:t;show-trailing-whitespace:t;rm-trailing-spaces:t -*-
# vi: set ts=2 noet:
#
# (c) Copyright Rosetta Commons Member Institutions.
# (c) This file is part of the Rosetta software suite and is made available under license.
# (c) The Rosetta software is developed by the contributing members of the Rosetta Commons.
# (c) For more information, see http://www.rosettacommons.org. Questions about this can be
# (c) addressed to University of Washington UW TechTransfer, email: license@u.washington.edu.
library(reshape2)
library(ggplot2)
library(ascii)
feature_analyses <- c(feature_analyses, methods::new("FeaturesAnalysis",
id = "rotamer_recovery_hbond_geometry",
author = "Matthew O'Meara",
brief_description = "",
feature_reporter_dependencies = c("ResidueFeatures", "RotamerRecoveryFeatures", "ResidueSecondaryStructureFeatures", "PdbDataFeatures"),
run=function(self, sample_sources, output_dir, output_formats){
sele <-"
CREATE TEMPORARY TABLE IF NOT EXISTS chi_recovered (
struct_id INTEGER,
resNum INTEGER,
first,
PRIMARY KEY(struct_id, resNum));
INSERT INTO chi_recovered
SELECT
res.struct_id AS struct_id, res.resNum,
rr.divergence < 2 AS second
FROM
residues AS res,
residue_pdb_confidence AS bb,
rotamer_recovery AS rr,
residue_secondary_structure AS ss, dssp_codes AS dssp_code
WHERE
rr.struct_id = res.struct_id AND rr.resNum = res.resNum AND
bb.struct_id = res.struct_id AND bb.residue_number = res.resNum AND
bb.max_sc_temperature < 30 AND
ss.struct_id = res.struct_id AND ss.resNum = res.resNum AND
dssp_code.code = ss.dssp AND res.name3 = 'GLU';
CREATE INDEX IF NOT EXISTS hbonds_struct_id_acc_id ON hbonds(
struct_id, acc_id);
SELECT
rr.first,
geo.AHdist, geo.cosBAH, geo.cosAHD, geo.chi,
acc.HBChemType AS acc_chem_type, don.HBChemType AS don_chem_type,
CASE don.resNum - acc.resNum
WHEN -1 THEN '-1' WHEN -2 THEN '-2' WHEN -3 THEN '-3' WHEN -4 THEN '-4'
WHEN 1 THEN '1' WHEN 2 THEN '2' WHEN 3 THEN '3' WHEN 4 THEN '4'
ELSE 'long' END AS seq_sep
FROM
hbonds AS hb,
hbond_sites AS acc,
chi_recovered AS rr,
hbond_sites AS don,
hbond_geom_coords AS geo
WHERE
geo.struct_id = hb.struct_id AND geo.hbond_id = hb.hbond_id AND
acc.struct_id = hb.struct_id AND acc.site_id = hb.acc_id AND
don.struct_id = hb.struct_id AND don.site_id = hb.don_id AND
acc.HBChemType = 'hbacc_CXL' AND
rr.struct_id = acc.struct_id AND rr.resNum = acc.resNum;"
#ANALYZE;
#
#SELECT
# hb.struct_id,
# geo.AHdist, geo.cosBAH, geo.cosAHD, geo.chi,
# acc.resNum,
# acc.HBChemType AS acc_chem_type, don.HBChemType AS don_chem_type,
# CASE don.resNum - acc.resNum
# WHEN -1 THEN '-1' WHEN -2 THEN '-2' WHEN -3 THEN '-3' WHEN -4 THEN '-4'
# WHEN 1 THEN '1' WHEN 2 THEN '2' WHEN 3 THEN '3' WHEN 4 THEN '4'
# ELSE 'long' END AS seq_sep
#FROM
# hbonds AS hb,
# hbond_sites AS acc,
# hbond_sites AS don,
# hbond_geom_coords AS geo
#WHERE
# geo.struct_id = hb.struct_id AND geo.hbond_id = hb.hbond_id AND
# acc.struct_id = hb.struct_id AND acc.site_id = hb.acc_id AND
# don.struct_id = hb.struct_id AND don.site_id = hb.don_id AND
# acc.HBChemType = 'hbacc_CLX' AND
# rr.struct_id = acc.struct_id AND rr.resNum = acc.resNum;"
#
f <- query_sample_sources(sample_sources, sele)
sele <- "
DROP TABLE chi_recovered;"
query_sample_sources(sample_sources, sele, warn_zero_rows=F)
# Order the plots better and give more descriptive labels
f$don_chem_type <- factor(f$don_chem_type,
levels = c("hbdon_IMD", "hbdon_IME", "hbdon_GDE", "hbdon_GDH",
"hbdon_AHX", "hbdon_HXL", "hbdon_IND", "hbdon_AMO", "hbdon_CXA", "hbdon_PBA"),
labels = c("dIMD: h", "dIME: h", "dGDE: r", "dGDH: r",
"dAHX: y", "dHXL: s,t", "dIND: w", "dAMO: k", "dCXA: n,q", "dPBA: bb"))
# Order the plots better and give more descriptive labels
f$acc_chem_type <- factor(f$acc_chem_type,
levels = c("hbacc_IMD", "hbacc_IME", "hbacc_AHX", "hbacc_HXL",
"hbacc_CXA", "hbacc_CXL", "hbacc_PBA"),
labels = c("aIMD: h", "aIME: h", "aAHX: y", "aHXL: s,t",
"aCXA: n,q", "aCXL: d,e", "aPBA: bb"))
f$first <- factor(f$first, levels=c(1,0), labels=c("Recovered", "Not Recovered"))
plot_parts <- list(
theme_bw(),
geom_line(aes(x=x, y=y, colour=sample_source, size=first)),
geom_indicator(aes(indicator=counts, colour=sample_source, group=sample_source)),
scale_y_continuous("FeatureDensity)", limits=c(0,6), breaks=c(1,3,5)),
scale_size_manual("first chi angle", values=c(.5, 1)))
plot_id <- "hbond_GLU_helical_rotamer_recovery_AHdist_by_don_chem_type"
dens <- estimate_density_1d(
f, c("sample_source", "don_chem_type", "first"),
"AHdist", weight_fun = radial_3d_normalization)
p <- ggplot(data=dens) + plot_parts +
ggtitle("HBond A-H Distance for GLU by Donor Type, B-Factor < 30\nnormalized for equal weight per unit distance") +
facet_wrap(~don_chem_type) +
scale_x_continuous(expression(paste('Acceptor -- Proton Distance (', ring(A), ')')), limits=c(1.4,2.7), breaks=c(1.6, 1.9, 2.2, 2.6))
if(nrow(sample_sources) <= 3){
p <- p + theme(legend.position="bottom", legend.direction="horizontal")
}
save_plots(self, plot_id, sample_sources, output_dir, output_formats)
plot_id <- "hbond_GLU_helical_rotamer_recovery_AHdist_by_seq_sep"
dens <- estimate_density_1d(
f, c("sample_source", "seq_sep", "first"),
"AHdist", weight_fun = radial_3d_normalization)
p <- ggplot(data=dens) + plot_parts +
ggtitle("HBond A-H Distance for GLU by Sequence Separation, B-Factor < 30\nnormalized for equal weight per unit distance") +
facet_wrap(~seq_sep) +
scale_x_continuous(expression(paste('Acceptor -- Proton Distance (', ring(A), ')')), limits=c(1.4,2.7), breaks=c(1.6, 1.9, 2.2, 2.6))
if(nrow(sample_sources) <= 3){
p <- p + theme(legend.position="bottom", legend.direction="horizontal")
}
save_plots(self, plot_id, sample_sources, output_dir, output_formats)
plot_id <- "hbond_GLU_helical_rotamer_recovery_AHdist_by_seq_sep_don_chem_type"
dens <- estimate_density_1d(
f, c("sample_source", "seq_sep", "first", "don_chem_type"),
"AHdist", weight_fun = radial_3d_normalization)
p <- ggplot(data=dens) + plot_parts +
ggtitle("HBond A-H Distance for GLU by Sequence Separation and Donor Type, B-Factor < 30\nnormalized for equal weight per unit distance") +
facet_grid(seq_sep ~ don_chem_type) +
scale_x_continuous(expression(paste('Acceptor -- Proton Distance (', ring(A), ')')), limits=c(1.4,2.7), breaks=c(1.6, 1.9, 2.2, 2.6))
if(nrow(sample_sources) <= 3){
p <- p + theme(legend.position="bottom", legend.direction="horizontal")
}
save_plots(self, plot_id, sample_sources, output_dir, output_formats)
f$first_indicator <- f$first == "Recovered"
g <- dcast(f, seq_sep + sample_source ~ don_chem_type, margins=T, value="first_indicator", mean)
ascii(g, header=F, digits=4)
#|==============================================================================================================================================================
#1.1+| | seq_sep | sample_source | dIMD: h | dIME: h | dGDE: r | dGDH: r | dAHX: y | dHXL: s,t | dIND: w | dAMO: k | dCXA: n,q | dPBA: bb | (all)
#| 1 | 1 | top8000_r45890_111114 | | 0.8889 | 0.5122 | 0.6957 | 0.6923 | 0.5294 | 0.6667 | 0.7143 | 0.5714 | 0.7072 | 0.6874
#| 2 | 1 | top8000_olf_r45890_111114 | | 0.8333 | 0.5625 | 0.6415 | 0.8333 | 0.6250 | | 0.5897 | 0.5676 | 0.6544 | 0.6395
#
#| 4 | -1 | top8000_r45890_111114 | 0.5000 | 1.0000 | 0.7931 | 0.8158 | 0.4000 | 0.5514 | 1.0000 | 0.7386 | 0.7193 | 0.6071 | 0.7019
#| 5 | -1 | top8000_olf_r45890_111114 | 0.4444 | 1.0000 | 0.8100 | 0.8302 | 0.6667 | 0.5204 | | 0.6944 | 0.8108 | 0.5938 | 0.7118
#
#| 7 | 2 | top8000_r45890_111114 | 0.6364 | 0.8827 | 0.8477 | 0.8369 | 0.9157 | 0.7517 | 0.9008 | 0.8079 | 0.8503 | 0.7696 | 0.8228
#| 8 | 2 | top8000_olf_r45890_111114 | 0.6667 | 0.8609 | 0.8694 | 0.8489 | 0.8812 | 0.7448 | 0.9196 | 0.7877 | 0.9026 | 0.7731 | 0.8254
#
#| 10 | -2 | top8000_r45890_111114 | 0.7838 | 0.8710 | 0.7855 | 0.7711 | 0.8647 | 0.6983 | 0.8615 | 0.7660 | 0.7800 | 0.8056 | 0.7813
#| 11 | -2 | top8000_olf_r45890_111114 | 0.6944 | 0.8276 | 0.7739 | 0.7594 | 0.8284 | 0.7034 | 0.7937 | 0.6944 | 0.6818 | 0.8415 | 0.7667
#
#| 13 | 3 | top8000_r45890_111114 | 0.5385 | 0.8462 | 0.6482 | 0.6172 | 0.8667 | 0.7983 | 0.7500 | 0.6112 | 0.6839 | 0.6555 | 0.6362
#| 14 | 3 | top8000_olf_r45890_111114 | 0.7333 | 0.6000 | 0.6417 | 0.6347 | 0.7143 | 0.8182 | 0.7143 | 0.7151 | 0.6963 | 0.6796 | 0.6707
#
#| 16 | -3 | top8000_r45890_111114 | 0.8750 | 1.0000 | 0.9083 | 0.8601 | 0.3333 | 0.8529 | 0.8333 | 0.8478 | 0.7760 | 0.9098 | 0.8873
#| 17 | -3 | top8000_olf_r45890_111114 | 0.7727 | 0.6000 | 0.8769 | 0.8472 | 0.3125 | 0.7808 | 1.0000 | 0.7870 | 0.7840 | 0.8573 | 0.8413
#
#| 19 | 4 | top8000_r45890_111114 | 0.7727 | 0.7288 | 0.7699 | 0.7795 | 0.8140 | 0.5379 | 0.7778 | 0.7562 | 0.5708 | 0.9106 | 0.7329
#| 20 | 4 | top8000_olf_r45890_111114 | 0.8947 | 0.7347 | 0.7651 | 0.7541 | 0.7750 | 0.7130 | 0.7188 | 0.7453 | 0.6336 | 0.9115 | 0.7426
#
#| 22 | -4 | top8000_r45890_111114 | 0.7333 | 0.7812 | 0.8864 | 0.8507 | 0.7436 | 0.8794 | 0.9057 | 0.9156 | 0.9115 | 0.9253 | 0.8931
#| 23 | -4 | top8000_olf_r45890_111114 | 0.6923 | 0.6429 | 0.8386 | 0.7996 | 0.7059 | 0.8271 | 0.7500 | 0.8445 | 0.8392 | 0.8766 | 0.8375
#
#| 25 | long | top8000_r45890_111114 | 0.8801 | 0.8584 | 0.8452 | 0.8357 | 0.8450 | 0.8746 | 0.8654 | 0.8302 | 0.8447 | 0.8998 | 0.8559
#| 26 | long | top8000_olf_r45890_111114 | 0.8310 | 0.8189 | 0.8347 | 0.8164 | 0.8143 | 0.8491 | 0.8164 | 0.7785 | 0.8190 | 0.8877 | 0.8324
#
#| 28 | (all) | (all) | 0.8318 | 0.8371 | 0.8116 | 0.8094 | 0.8284 | 0.8360 | 0.8450 | 0.7903 | 0.8068 | 0.8742 | 0.8272
#|==============================================================================================================================================================
})) # end FeaturesAnalysis
momeara/RosettaFeatures documentation built on May 23, 2019, 6:07 a.m.
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# -*- tab-width:2;indent-tabs-mode:t;show-trailing-whitespace:t;rm-trailing-spaces:t -*-
# vi: set ts=2 noet:
#
# (c) Copyright Rosetta Commons Member Institutions.
# (c) This file is part of the Rosetta software suite and is made available under license.
# (c) The Rosetta software is developed by the contributing members of the Rosetta Commons.
# (c) For more information, see http://www.rosettacommons.org. Questions about this can be
# (c) addressed to University of Washington UW TechTransfer, email: license@u.washington.edu.
library(reshape2)
library(ggplot2)
library(ascii)
feature_analyses <- c(feature_analyses, methods::new("FeaturesAnalysis",
id = "rotamer_recovery_hbond_geometry",
author = "Matthew O'Meara",
brief_description = "",
feature_reporter_dependencies = c("ResidueFeatures", "RotamerRecoveryFeatures", "ResidueSecondaryStructureFeatures", "PdbDataFeatures"),
run=function(self, sample_sources, output_dir, output_formats){
sele <-"
CREATE TEMPORARY TABLE IF NOT EXISTS chi_recovered (
struct_id INTEGER,
resNum INTEGER,
first,
PRIMARY KEY(struct_id, resNum));
INSERT INTO chi_recovered
SELECT
res.struct_id AS struct_id, res.resNum,
rr.divergence < 2 AS second
FROM
residues AS res,
residue_pdb_confidence AS bb,
rotamer_recovery AS rr,
residue_secondary_structure AS ss, dssp_codes AS dssp_code
WHERE
rr.struct_id = res.struct_id AND rr.resNum = res.resNum AND
bb.struct_id = res.struct_id AND bb.residue_number = res.resNum AND
bb.max_sc_temperature < 30 AND
ss.struct_id = res.struct_id AND ss.resNum = res.resNum AND
dssp_code.code = ss.dssp AND res.name3 = 'GLU';
CREATE INDEX IF NOT EXISTS hbonds_struct_id_acc_id ON hbonds(
struct_id, acc_id);
SELECT
rr.first,
geo.AHdist, geo.cosBAH, geo.cosAHD, geo.chi,
acc.HBChemType AS acc_chem_type, don.HBChemType AS don_chem_type,
CASE don.resNum - acc.resNum
WHEN -1 THEN '-1' WHEN -2 THEN '-2' WHEN -3 THEN '-3' WHEN -4 THEN '-4'
WHEN 1 THEN '1' WHEN 2 THEN '2' WHEN 3 THEN '3' WHEN 4 THEN '4'
ELSE 'long' END AS seq_sep
FROM
hbonds AS hb,
hbond_sites AS acc,
chi_recovered AS rr,
hbond_sites AS don,
hbond_geom_coords AS geo
WHERE
geo.struct_id = hb.struct_id AND geo.hbond_id = hb.hbond_id AND
acc.struct_id = hb.struct_id AND acc.site_id = hb.acc_id AND
don.struct_id = hb.struct_id AND don.site_id = hb.don_id AND
acc.HBChemType = 'hbacc_CXL' AND
rr.struct_id = acc.struct_id AND rr.resNum = acc.resNum;"
#ANALYZE;
#
#SELECT
# hb.struct_id,
# geo.AHdist, geo.cosBAH, geo.cosAHD, geo.chi,
# acc.resNum,
# acc.HBChemType AS acc_chem_type, don.HBChemType AS don_chem_type,
# CASE don.resNum - acc.resNum
# WHEN -1 THEN '-1' WHEN -2 THEN '-2' WHEN -3 THEN '-3' WHEN -4 THEN '-4'
# WHEN 1 THEN '1' WHEN 2 THEN '2' WHEN 3 THEN '3' WHEN 4 THEN '4'
# ELSE 'long' END AS seq_sep
#FROM
# hbonds AS hb,
# hbond_sites AS acc,
# hbond_sites AS don,
# hbond_geom_coords AS geo
#WHERE
# geo.struct_id = hb.struct_id AND geo.hbond_id = hb.hbond_id AND
# acc.struct_id = hb.struct_id AND acc.site_id = hb.acc_id AND
# don.struct_id = hb.struct_id AND don.site_id = hb.don_id AND
# acc.HBChemType = 'hbacc_CLX' AND
# rr.struct_id = acc.struct_id AND rr.resNum = acc.resNum;"
#
f <- query_sample_sources(sample_sources, sele)
sele <- "
DROP TABLE chi_recovered;"
query_sample_sources(sample_sources, sele, warn_zero_rows=F)
# Order the plots better and give more descriptive labels
f$don_chem_type <- factor(f$don_chem_type,
levels = c("hbdon_IMD", "hbdon_IME", "hbdon_GDE", "hbdon_GDH",
"hbdon_AHX", "hbdon_HXL", "hbdon_IND", "hbdon_AMO", "hbdon_CXA", "hbdon_PBA"),
labels = c("dIMD: h", "dIME: h", "dGDE: r", "dGDH: r",
"dAHX: y", "dHXL: s,t", "dIND: w", "dAMO: k", "dCXA: n,q", "dPBA: bb"))
# Order the plots better and give more descriptive labels
f$acc_chem_type <- factor(f$acc_chem_type,
levels = c("hbacc_IMD", "hbacc_IME", "hbacc_AHX", "hbacc_HXL",
"hbacc_CXA", "hbacc_CXL", "hbacc_PBA"),
labels = c("aIMD: h", "aIME: h", "aAHX: y", "aHXL: s,t",
"aCXA: n,q", "aCXL: d,e", "aPBA: bb"))
f$first <- factor(f$first, levels=c(1,0), labels=c("Recovered", "Not Recovered"))
plot_parts <- list(
theme_bw(),
geom_line(aes(x=x, y=y, colour=sample_source, size=first)),
geom_indicator(aes(indicator=counts, colour=sample_source, group=sample_source)),
scale_y_continuous("FeatureDensity)", limits=c(0,6), breaks=c(1,3,5)),
scale_size_manual("first chi angle", values=c(.5, 1)))
plot_id <- "hbond_GLU_helical_rotamer_recovery_AHdist_by_don_chem_type"
dens <- estimate_density_1d(
f, c("sample_source", "don_chem_type", "first"),
"AHdist", weight_fun = radial_3d_normalization)
p <- ggplot(data=dens) + plot_parts +
ggtitle("HBond A-H Distance for GLU by Donor Type, B-Factor < 30\nnormalized for equal weight per unit distance") +
facet_wrap(~don_chem_type) +
scale_x_continuous(expression(paste('Acceptor -- Proton Distance (', ring(A), ')')), limits=c(1.4,2.7), breaks=c(1.6, 1.9, 2.2, 2.6))
if(nrow(sample_sources) <= 3){
p <- p + theme(legend.position="bottom", legend.direction="horizontal")
}
save_plots(self, plot_id, sample_sources, output_dir, output_formats)
plot_id <- "hbond_GLU_helical_rotamer_recovery_AHdist_by_seq_sep"
dens <- estimate_density_1d(
f, c("sample_source", "seq_sep", "first"),
"AHdist", weight_fun = radial_3d_normalization)
p <- ggplot(data=dens) + plot_parts +
ggtitle("HBond A-H Distance for GLU by Sequence Separation, B-Factor < 30\nnormalized for equal weight per unit distance") +
facet_wrap(~seq_sep) +
scale_x_continuous(expression(paste('Acceptor -- Proton Distance (', ring(A), ')')), limits=c(1.4,2.7), breaks=c(1.6, 1.9, 2.2, 2.6))
if(nrow(sample_sources) <= 3){
p <- p + theme(legend.position="bottom", legend.direction="horizontal")
}
save_plots(self, plot_id, sample_sources, output_dir, output_formats)
plot_id <- "hbond_GLU_helical_rotamer_recovery_AHdist_by_seq_sep_don_chem_type"
dens <- estimate_density_1d(
f, c("sample_source", "seq_sep", "first", "don_chem_type"),
"AHdist", weight_fun = radial_3d_normalization)
p <- ggplot(data=dens) + plot_parts +
ggtitle("HBond A-H Distance for GLU by Sequence Separation and Donor Type, B-Factor < 30\nnormalized for equal weight per unit distance") +
facet_grid(seq_sep ~ don_chem_type) +
scale_x_continuous(expression(paste('Acceptor -- Proton Distance (', ring(A), ')')), limits=c(1.4,2.7), breaks=c(1.6, 1.9, 2.2, 2.6))
if(nrow(sample_sources) <= 3){
p <- p + theme(legend.position="bottom", legend.direction="horizontal")
}
save_plots(self, plot_id, sample_sources, output_dir, output_formats)
f$first_indicator <- f$first == "Recovered"
g <- dcast(f, seq_sep + sample_source ~ don_chem_type, margins=T, value="first_indicator", mean)
ascii(g, header=F, digits=4)
#|==============================================================================================================================================================
#1.1+| | seq_sep | sample_source | dIMD: h | dIME: h | dGDE: r | dGDH: r | dAHX: y | dHXL: s,t | dIND: w | dAMO: k | dCXA: n,q | dPBA: bb | (all)
#| 1 | 1 | top8000_r45890_111114 | | 0.8889 | 0.5122 | 0.6957 | 0.6923 | 0.5294 | 0.6667 | 0.7143 | 0.5714 | 0.7072 | 0.6874
#| 2 | 1 | top8000_olf_r45890_111114 | | 0.8333 | 0.5625 | 0.6415 | 0.8333 | 0.6250 | | 0.5897 | 0.5676 | 0.6544 | 0.6395
#
#| 4 | -1 | top8000_r45890_111114 | 0.5000 | 1.0000 | 0.7931 | 0.8158 | 0.4000 | 0.5514 | 1.0000 | 0.7386 | 0.7193 | 0.6071 | 0.7019
#| 5 | -1 | top8000_olf_r45890_111114 | 0.4444 | 1.0000 | 0.8100 | 0.8302 | 0.6667 | 0.5204 | | 0.6944 | 0.8108 | 0.5938 | 0.7118
#
#| 7 | 2 | top8000_r45890_111114 | 0.6364 | 0.8827 | 0.8477 | 0.8369 | 0.9157 | 0.7517 | 0.9008 | 0.8079 | 0.8503 | 0.7696 | 0.8228
#| 8 | 2 | top8000_olf_r45890_111114 | 0.6667 | 0.8609 | 0.8694 | 0.8489 | 0.8812 | 0.7448 | 0.9196 | 0.7877 | 0.9026 | 0.7731 | 0.8254
#
#| 10 | -2 | top8000_r45890_111114 | 0.7838 | 0.8710 | 0.7855 | 0.7711 | 0.8647 | 0.6983 | 0.8615 | 0.7660 | 0.7800 | 0.8056 | 0.7813
#| 11 | -2 | top8000_olf_r45890_111114 | 0.6944 | 0.8276 | 0.7739 | 0.7594 | 0.8284 | 0.7034 | 0.7937 | 0.6944 | 0.6818 | 0.8415 | 0.7667
#
#| 13 | 3 | top8000_r45890_111114 | 0.5385 | 0.8462 | 0.6482 | 0.6172 | 0.8667 | 0.7983 | 0.7500 | 0.6112 | 0.6839 | 0.6555 | 0.6362
#| 14 | 3 | top8000_olf_r45890_111114 | 0.7333 | 0.6000 | 0.6417 | 0.6347 | 0.7143 | 0.8182 | 0.7143 | 0.7151 | 0.6963 | 0.6796 | 0.6707
#
#| 16 | -3 | top8000_r45890_111114 | 0.8750 | 1.0000 | 0.9083 | 0.8601 | 0.3333 | 0.8529 | 0.8333 | 0.8478 | 0.7760 | 0.9098 | 0.8873
#| 17 | -3 | top8000_olf_r45890_111114 | 0.7727 | 0.6000 | 0.8769 | 0.8472 | 0.3125 | 0.7808 | 1.0000 | 0.7870 | 0.7840 | 0.8573 | 0.8413
#
#| 19 | 4 | top8000_r45890_111114 | 0.7727 | 0.7288 | 0.7699 | 0.7795 | 0.8140 | 0.5379 | 0.7778 | 0.7562 | 0.5708 | 0.9106 | 0.7329
#| 20 | 4 | top8000_olf_r45890_111114 | 0.8947 | 0.7347 | 0.7651 | 0.7541 | 0.7750 | 0.7130 | 0.7188 | 0.7453 | 0.6336 | 0.9115 | 0.7426
#
#| 22 | -4 | top8000_r45890_111114 | 0.7333 | 0.7812 | 0.8864 | 0.8507 | 0.7436 | 0.8794 | 0.9057 | 0.9156 | 0.9115 | 0.9253 | 0.8931
#| 23 | -4 | top8000_olf_r45890_111114 | 0.6923 | 0.6429 | 0.8386 | 0.7996 | 0.7059 | 0.8271 | 0.7500 | 0.8445 | 0.8392 | 0.8766 | 0.8375
#
#| 25 | long | top8000_r45890_111114 | 0.8801 | 0.8584 | 0.8452 | 0.8357 | 0.8450 | 0.8746 | 0.8654 | 0.8302 | 0.8447 | 0.8998 | 0.8559
#| 26 | long | top8000_olf_r45890_111114 | 0.8310 | 0.8189 | 0.8347 | 0.8164 | 0.8143 | 0.8491 | 0.8164 | 0.7785 | 0.8190 | 0.8877 | 0.8324
#
#| 28 | (all) | (all) | 0.8318 | 0.8371 | 0.8116 | 0.8094 | 0.8284 | 0.8360 | 0.8450 | 0.7903 | 0.8068 | 0.8742 | 0.8272
#|==============================================================================================================================================================
})) # end FeaturesAnalysis
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