From 50a1dfa4b2cbc8fb1734848a4efe13a3ca33715a Mon Sep 17 00:00:00 2001
From: Venkat Malladi <Venkat.Malladi@utsouthwestern.edu>
Date: Mon, 5 Jun 2017 14:28:36 -0500
Subject: [PATCH] Complete analysis of ranked clusters.

---
 .../box_plot_cluster_1_enhancers_rpkm.png     |  Bin 0 -> 12924 bytes
 .../box_plot_cluster_1_genes_fpkm.png         |  Bin 0 -> 11884 bytes
 GRO_seq_TFSEE/box_plot_cluster_1_tfs_fpkm.png |  Bin 0 -> 11891 bytes
 .../box_plot_cluster_2_enhancers_rpkm.png     |  Bin 0 -> 14440 bytes
 .../box_plot_cluster_2_genes_fpkm.png         |  Bin 0 -> 11653 bytes
 GRO_seq_TFSEE/box_plot_cluster_2_tfs_fpkm.png |  Bin 0 -> 12278 bytes
 .../box_plot_cluster_3_genes_fpkm.png         |  Bin 0 -> 11403 bytes
 .../box_plot_cluster_4_genes_fpkm.png         |  Bin 0 -> 12305 bytes
 GRO_seq_TFSEE/closest_genes.py                |  105 +
 GRO_seq_TFSEE/closest_genes.sh                |    8 +
 GRO_seq_TFSEE/cluster1_enriched_tfs.png       |  Bin 0 -> 98555 bytes
 GRO_seq_TFSEE/cluster2_enriched_tfs.png       |  Bin 0 -> 87635 bytes
 GRO_seq_TFSEE/cluster_1_enhancers.csv         | 1806 ++++++++++++
 .../cluster_1_enhancers_locations.bed         | 1805 ++++++++++++
 GRO_seq_TFSEE/cluster_1_genes.txt             |  822 ++++++
 GRO_seq_TFSEE/cluster_1_tfs.csv               |   65 +
 GRO_seq_TFSEE/cluster_2_enhancers.csv         | 1221 ++++++++
 .../cluster_2_enhancers_locations.bed         | 1220 ++++++++
 GRO_seq_TFSEE/cluster_2_genes.txt             |  593 ++++
 GRO_seq_TFSEE/cluster_2_tfs.csv               |   25 +
 .../cluster_3_enhancers_locations.bed         | 2465 +++++++++++++++++
 GRO_seq_TFSEE/cluster_3_genes.txt             | 1016 +++++++
 .../cluster_4_enhancers_locations.bed         | 1371 +++++++++
 GRO_seq_TFSEE/cluster_4_genes.txt             |  661 +++++
 GRO_seq_TFSEE/matrix_analysis.py              |  159 +-
 25 files changed, 13341 insertions(+), 1 deletion(-)
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_1_enhancers_rpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_1_genes_fpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_1_tfs_fpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_2_enhancers_rpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_2_genes_fpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_2_tfs_fpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_3_genes_fpkm.png
 create mode 100644 GRO_seq_TFSEE/box_plot_cluster_4_genes_fpkm.png
 create mode 100644 GRO_seq_TFSEE/cluster1_enriched_tfs.png
 create mode 100644 GRO_seq_TFSEE/cluster2_enriched_tfs.png
 create mode 100644 GRO_seq_TFSEE/cluster_1_enhancers.csv
 create mode 100644 GRO_seq_TFSEE/cluster_1_enhancers_locations.bed
 create mode 100644 GRO_seq_TFSEE/cluster_1_genes.txt
 create mode 100644 GRO_seq_TFSEE/cluster_1_tfs.csv
 create mode 100644 GRO_seq_TFSEE/cluster_2_enhancers.csv
 create mode 100644 GRO_seq_TFSEE/cluster_2_enhancers_locations.bed
 create mode 100644 GRO_seq_TFSEE/cluster_2_genes.txt
 create mode 100644 GRO_seq_TFSEE/cluster_2_tfs.csv
 create mode 100644 GRO_seq_TFSEE/cluster_3_enhancers_locations.bed
 create mode 100644 GRO_seq_TFSEE/cluster_3_genes.txt
 create mode 100644 GRO_seq_TFSEE/cluster_4_enhancers_locations.bed
 create mode 100644 GRO_seq_TFSEE/cluster_4_genes.txt

diff --git a/GRO_seq_TFSEE/box_plot_cluster_1_enhancers_rpkm.png b/GRO_seq_TFSEE/box_plot_cluster_1_enhancers_rpkm.png
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diff --git a/GRO_seq_TFSEE/closest_genes.py b/GRO_seq_TFSEE/closest_genes.py
index 320acf9..4bcce56 100644
--- a/GRO_seq_TFSEE/closest_genes.py
+++ b/GRO_seq_TFSEE/closest_genes.py
@@ -119,3 +119,108 @@ scipy.stats.ranksums(cluster3_genes_expressed['ES_D5'],cluster3_genes_expressed[
 scipy.stats.ranksums(cluster3_genes_expressed['ES_D5'],cluster3_genes_expressed['ES_D10'])
 
 scipy.stats.ranksums(cluster3_genes_expressed['ES_D7'],cluster3_genes_expressed['ES_D10'])
+
+
+
+# Read in cluster 1 enhancers
+cluster_1 = pd.DataFrame.from_csv("cluster_1_enhancers.csv", sep=",", header=0, index_col=0)
+
+# Choose enhacners exprssed in cluster 1
+enhancers_universe_cluster_1 = enhancers_universe.loc[cluster_1.index.values]
+enhancers_universe_cluster_1.to_csv("cluster_1_enhancers_locations.bed", sep="\t",header=None, index=False)
+
+
+# Read in nearest genes
+genes_id = pd.DataFrame.from_csv("cluster_1_genes.txt", sep="\t", header=None, index_col=None)
+
+needed_rows = [row for row in fpkm_symbol.index if row in genes_id[0].values]
+cluster1_genes_expressed = fpkm_symbol.loc[needed_rows]
+
+
+# col_colors
+plt.style.use('classic')
+colors = ["#FFD66F","#2E6A44","#862743", "#4FA6C7", "#3398CC"]
+medianprops = dict(linestyle='-', linewidth=2, color='black')
+box = cluster1_genes_expressed.boxplot(column=['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'],patch_artist=True,showfliers=False,manage_xticks=False,widths = 0.6, medianprops = medianprops)
+plt.setp(box['whiskers'], color='k', linestyle='-', linewidth = 5)
+plt.setp(box['boxes'], color='k', linestyle='-', linewidth = 5)
+
+for patch, color in zip(box['boxes'], colors):
+    patch.set_facecolor(color)
+
+plt.tick_params(axis='y', direction='out')
+plt.tick_params(axis='x', direction='out')
+plt.tick_params(top='off', right='off')
+plt.grid(b=False)
+plt.ylim((-5,55))
+plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
+plt.savefig('box_plot_cluster_1_genes_fpkm.png')
+plt.clf()
+
+# Cluster tfs 1 e-4
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D0'],cluster1_genes_expressed['ES_D2'])
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D0'],cluster1_genes_expressed['ES_D5'])
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D0'],cluster1_genes_expressed['ES_D7'])
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D0'],cluster1_genes_expressed['ES_D10'])
+
+
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D2'],cluster1_genes_expressed['ES_D5'])
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D2'],cluster1_genes_expressed['ES_D7'])
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D2'],cluster1_genes_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D5'],cluster1_genes_expressed['ES_D7'])
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D5'],cluster1_genes_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster1_genes_expressed['ES_D7'],cluster1_genes_expressed['ES_D10'])
+
+
+# Read in cluster 2 enhancers
+cluster_2 = pd.DataFrame.from_csv("cluster_2_enhancers.csv", sep=",", header=0, index_col=0)
+
+# Choose enhacners exprssed in cluster 2
+enhancers_universe_cluster_2 = enhancers_universe.loc[cluster_2.index.values]
+enhancers_universe_cluster_2.to_csv("cluster_2_enhancers_locations.bed", sep="\t",header=None, index=False)
+
+
+# Read in nearest genes
+genes_id = pd.DataFrame.from_csv("cluster_2_genes.txt", sep="\t", header=None, index_col=None)
+
+needed_rows = [row for row in fpkm_symbol.index if row in genes_id[0].values]
+cluster2_genes_expressed = fpkm_symbol.loc[needed_rows]
+
+
+# col_colors
+plt.style.use('classic')
+colors = ["#FFD66F","#2E6A44","#862743", "#4FA6C7", "#3398CC"]
+medianprops = dict(linestyle='-', linewidth=2, color='black')
+box = cluster2_genes_expressed.boxplot(column=['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'],patch_artist=True,showfliers=False,manage_xticks=False,widths = 0.6, medianprops = medianprops)
+plt.setp(box['whiskers'], color='k', linestyle='-', linewidth = 5)
+plt.setp(box['boxes'], color='k', linestyle='-', linewidth = 5)
+
+for patch, color in zip(box['boxes'], colors):
+    patch.set_facecolor(color)
+
+plt.tick_params(axis='y', direction='out')
+plt.tick_params(axis='x', direction='out')
+plt.tick_params(top='off', right='off')
+plt.grid(b=False)
+plt.ylim((-5,50))
+plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
+plt.savefig('box_plot_cluster_2_genes_fpkm.png')
+plt.clf()
+
+# Cluster tfs 1 e-4
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D0'],cluster2_genes_expressed['ES_D2'])
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D0'],cluster2_genes_expressed['ES_D5'])
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D0'],cluster2_genes_expressed['ES_D7'])
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D0'],cluster2_genes_expressed['ES_D10'])
+
+
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D2'],cluster2_genes_expressed['ES_D5'])
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D2'],cluster2_genes_expressed['ES_D7'])
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D2'],cluster2_genes_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D5'],cluster2_genes_expressed['ES_D7'])
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D5'],cluster2_genes_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster2_genes_expressed['ES_D7'],cluster2_genes_expressed['ES_D10'])
diff --git a/GRO_seq_TFSEE/closest_genes.sh b/GRO_seq_TFSEE/closest_genes.sh
index 0db0029..f39a2c7 100644
--- a/GRO_seq_TFSEE/closest_genes.sh
+++ b/GRO_seq_TFSEE/closest_genes.sh
@@ -4,3 +4,11 @@ bedtools sort -i cluster_4_enhancers_locations.bed | bedtools closest -a - -b  g
 
 #Closest genes Cluster 3
 bedtools sort -i cluster_3_enhancers_locations.bed | bedtools closest -a - -b  gencode.v19.annotation_protein_coding_sorted.gtf | cut -f12 | cut -f1 -d ';' | cut -f2 -d ' ' | sort | uniq | sed 's/"//g' > cluster_3_genes.txt
+
+
+#Closest genes Cluster 1
+bedtools sort -i cluster_1_enhancers_locations.bed | bedtools closest -a - -b  gencode.v19.annotation_protein_coding_sorted.gtf | cut -f12 | cut -f1 -d ';' | cut -f2 -d ' ' | sort | uniq | sed 's/"//g' > cluster_1_genes.txt
+
+
+#Closest genes Cluster 2
+bedtools sort -i cluster_2_enhancers_locations.bed | bedtools closest -a - -b  gencode.v19.annotation_protein_coding_sorted.gtf | cut -f12 | cut -f1 -d ';' | cut -f2 -d ' ' | sort | uniq | sed 's/"//g' > cluster_2_genes.txt
diff --git a/GRO_seq_TFSEE/cluster1_enriched_tfs.png b/GRO_seq_TFSEE/cluster1_enriched_tfs.png
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diff --git a/GRO_seq_TFSEE/cluster_1_enhancers.csv b/GRO_seq_TFSEE/cluster_1_enhancers.csv
new file mode 100644
index 0000000..5328c1a
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_1_enhancers.csv
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diff --git a/GRO_seq_TFSEE/cluster_1_enhancers_locations.bed b/GRO_seq_TFSEE/cluster_1_enhancers_locations.bed
new file mode 100644
index 0000000..3692bfa
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diff --git a/GRO_seq_TFSEE/cluster_1_genes.txt b/GRO_seq_TFSEE/cluster_1_genes.txt
new file mode 100644
index 0000000..3ac14fc
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_1_genes.txt
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diff --git a/GRO_seq_TFSEE/cluster_1_tfs.csv b/GRO_seq_TFSEE/cluster_1_tfs.csv
new file mode 100644
index 0000000..40c8fa6
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_1_tfs.csv
@@ -0,0 +1,65 @@
+symbol,ES_D0,ES_D2,ES_D5,ES_D7,ES_D10
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diff --git a/GRO_seq_TFSEE/cluster_2_enhancers.csv b/GRO_seq_TFSEE/cluster_2_enhancers.csv
new file mode 100644
index 0000000..b856d91
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_2_enhancers.csv
@@ -0,0 +1,1221 @@
+,ES_D0,ES_D2,ES_D5,ES_D7,ES_D10
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diff --git a/GRO_seq_TFSEE/cluster_2_enhancers_locations.bed b/GRO_seq_TFSEE/cluster_2_enhancers_locations.bed
new file mode 100644
index 0000000..db1e0b2
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_2_enhancers_locations.bed
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diff --git a/GRO_seq_TFSEE/cluster_2_genes.txt b/GRO_seq_TFSEE/cluster_2_genes.txt
new file mode 100644
index 0000000..424cf30
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_2_genes.txt
@@ -0,0 +1,593 @@
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diff --git a/GRO_seq_TFSEE/cluster_2_tfs.csv b/GRO_seq_TFSEE/cluster_2_tfs.csv
new file mode 100644
index 0000000..9bf48a8
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_2_tfs.csv
@@ -0,0 +1,25 @@
+symbol,ES_D0,ES_D2,ES_D5,ES_D7,ES_D10
+DMBX1,0.01,0.07,0.485,0.0,0.045
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+MZF1,8.885,12.365,17.5,26.0,23.355
+NFE2L2,18.59,23.265,27.355,42.5,29.845
+NKX2-8,0.0,0.0,2.84,0.0,0.01
+OTX1,0.28,1.395,6.275,0.635,0.33
+PAX1,0.005,0.005,3.895,1.11,0.035
+PAX9,0.155,0.07,1.1,0.055,0.16
+PRDM1,0.255,33.89,7.5,8.065,0.79
+RARB,0.125,9.755,14.765,36.265,2.48
+REL,0.91,1.47,2.805,3.635,3.23
+RHOXF1,0.075,0.27,0.885,1.405,0.58
+RXRA,13.38,31.955,56.265,27.41,34.875
+RXRG,0.005,5.185,0.59,0.0,0.755
+SNAI2,0.09,0.055,0.565,0.36,0.66
+SP3,16.795,14.03,30.47,22.055,22.605
+TCF3,136.215,124.305,134.515,121.675,163.045
+TEAD3,19.265,15.565,27.705,25.44,35.495
+TFAP2A,0.01,0.19,2.715,0.39,0.52
+ZNF354C,2.225,2.455,4.71,4.635,4.235
diff --git a/GRO_seq_TFSEE/cluster_3_enhancers_locations.bed b/GRO_seq_TFSEE/cluster_3_enhancers_locations.bed
new file mode 100644
index 0000000..82c324a
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_3_enhancers_locations.bed
@@ -0,0 +1,2465 @@
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diff --git a/GRO_seq_TFSEE/cluster_3_genes.txt b/GRO_seq_TFSEE/cluster_3_genes.txt
new file mode 100644
index 0000000..fce39f9
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_3_genes.txt
@@ -0,0 +1,1016 @@
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diff --git a/GRO_seq_TFSEE/cluster_4_enhancers_locations.bed b/GRO_seq_TFSEE/cluster_4_enhancers_locations.bed
new file mode 100644
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diff --git a/GRO_seq_TFSEE/cluster_4_genes.txt b/GRO_seq_TFSEE/cluster_4_genes.txt
new file mode 100644
index 0000000..7fefca4
--- /dev/null
+++ b/GRO_seq_TFSEE/cluster_4_genes.txt
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diff --git a/GRO_seq_TFSEE/matrix_analysis.py b/GRO_seq_TFSEE/matrix_analysis.py
index 98cdc69..b1ebb3f 100644
--- a/GRO_seq_TFSEE/matrix_analysis.py
+++ b/GRO_seq_TFSEE/matrix_analysis.py
@@ -686,7 +686,7 @@ plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
 plt.savefig('box_plot_cluster_3_tfs_fpkm.png')
 plt.clf()
 
-# Cluster tfs 1 e-3 (NS)
+# Cluster tfs 1 e-3
 scipy.stats.ranksums(cluster3_tfs['ES_D0'],cluster3_tfs['ES_D2'])
 scipy.stats.ranksums(cluster3_tfs['ES_D0'],cluster3_tfs['ES_D5'])
 scipy.stats.ranksums(cluster3_tfs['ES_D0'],cluster3_tfs['ES_D7'])
@@ -745,6 +745,163 @@ scipy.stats.ranksums(cluster3_enhancers_expressed['ES_D5'],cluster3_enhancers_ex
 scipy.stats.ranksums(cluster3_enhancers_expressed['ES_D7'],cluster3_enhancers_expressed['ES_D10'])
 
 
+# Look at Cluster 1 for expression of TF's
+cluster1_tfs = tf_cell_lines.loc[cell_tf_values_std_cluster_1.index.values]
+cluster1_tfs.to_csv("cluster_1_tfs.csv")
+
+box = cluster1_tfs.boxplot(column=['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'],patch_artist=True,showfliers=False,manage_xticks=False,widths = 0.6, medianprops = medianprops)
+plt.setp(box['whiskers'], color='k', linestyle='-', linewidth = 5)
+plt.setp(box['boxes'], color='k', linestyle='-', linewidth = 5)
+
+for patch, color in zip(box['boxes'], colors):
+    patch.set_facecolor(color)
+
+plt.tick_params(axis='y', direction='out')
+plt.tick_params(axis='x', direction='out')
+plt.tick_params(top='off', right='off')
+plt.grid(b=False)
+plt.ylim((-5,55))
+plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
+plt.savefig('box_plot_cluster_1_tfs_fpkm.png')
+plt.clf()
+
+# Cluster tfs 1 e-12 (NS)
+scipy.stats.ranksums(cluster1_tfs['ES_D0'],cluster1_tfs['ES_D2'])
+scipy.stats.ranksums(cluster1_tfs['ES_D0'],cluster1_tfs['ES_D5'])
+scipy.stats.ranksums(cluster1_tfs['ES_D0'],cluster1_tfs['ES_D7'])
+scipy.stats.ranksums(cluster1_tfs['ES_D0'],cluster1_tfs['ES_D10'])
+
+
+scipy.stats.ranksums(cluster1_tfs['ES_D2'],cluster1_tfs['ES_D5'])
+scipy.stats.ranksums(cluster1_tfs['ES_D2'],cluster1_tfs['ES_D7'])
+scipy.stats.ranksums(cluster1_tfs['ES_D2'],cluster1_tfs['ES_D10'])
+
+scipy.stats.ranksums(cluster1_tfs['ES_D5'],cluster1_tfs['ES_D7'])
+scipy.stats.ranksums(cluster1_tfs['ES_D5'],cluster1_tfs['ES_D10'])
+
+scipy.stats.ranksums(cluster1_tfs['ES_D7'],cluster1_tfs['ES_D10'])
+
+
+
+
+cluster1_motifs = motif_enhancers.loc[cell_tf_values_std_cluster_1.index.values]
+cluster1_enhancers = only_rpkm_values.loc[cluster1_motifs.loc[:, (cluster1_motifs >1).any(axis=0)].columns.values]
+cluster_1_expressed_enhancers = np.concatenate((rpkm_ssp[(rpkm_ssp['ES_D0'] >= 0.5) | (rpkm_ssp['ES_D2'] >= 0.5) | (rpkm_ssp['ES_D7'] >= 0.5) | (rpkm_ssp['ES_D10'] >= 0.5)].index.values,rpkm_sunp[(rpkm_sunp['ES_D0'] >= 1) | (rpkm_sunp['ES_D2'] >=1) | (rpkm_sunp['ES_D7'] >= 1) | (rpkm_sunp['ES_D10'] >=1)].index.values))
+needed_rows = [row for row in cluster1_enhancers.index if row in cluster_1_expressed_enhancers]
+cluster1_enhancers_expressed = cluster1_enhancers.loc[needed_rows]
+cluster1_enhancers_expressed.to_csv("cluster_1_enhancers.csv")
+
+box = cluster1_enhancers_expressed.boxplot(column=['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'],patch_artist=True,showfliers=False,manage_xticks=False,widths = 0.6, medianprops = medianprops)
+plt.setp(box['whiskers'], color='k', linestyle='-', linewidth = 5)
+plt.setp(box['boxes'], color='k', linestyle='-', linewidth = 5)
+
+for patch, color in zip(box['boxes'], colors):
+    patch.set_facecolor(color)
+
+plt.tick_params(axis='y', direction='out')
+plt.tick_params(axis='x', direction='out')
+plt.tick_params(top='off', right='off')
+plt.grid(b=False)
+plt.ylim((-5,60))
+plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
+plt.savefig('box_plot_cluster_1_enhancers_rpkm.png')
+plt.clf()
+
+# Cluster tfs 1 e-4
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D0'],cluster1_enhancers_expressed['ES_D2'])
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D0'],cluster1_enhancers_expressed['ES_D5'])
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D0'],cluster1_enhancers_expressed['ES_D7'])
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D0'],cluster1_enhancers_expressed['ES_D10'])
+
+
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D2'],cluster1_enhancers_expressed['ES_D5'])
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D2'],cluster1_enhancers_expressed['ES_D7'])
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D2'],cluster1_enhancers_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D5'],cluster1_enhancers_expressed['ES_D7'])
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D5'],cluster1_enhancers_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster1_enhancers_expressed['ES_D7'],cluster1_enhancers_expressed['ES_D10'])
+
+# Look at Cluster 2 for expression of TF's
+cluster2_tfs = tf_cell_lines.loc[cell_tf_values_std_cluster_2.index.values]
+cluster2_tfs.to_csv("cluster_2_tfs.csv")
+
+box = cluster2_tfs.boxplot(column=['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'],patch_artist=True,showfliers=False,manage_xticks=False,widths = 0.6, medianprops = medianprops)
+plt.setp(box['whiskers'], color='k', linestyle='-', linewidth = 5)
+plt.setp(box['boxes'], color='k', linestyle='-', linewidth = 5)
+
+for patch, color in zip(box['boxes'], colors):
+    patch.set_facecolor(color)
+
+plt.tick_params(axis='y', direction='out')
+plt.tick_params(axis='x', direction='out')
+plt.tick_params(top='off', right='off')
+plt.grid(b=False)
+plt.ylim((-5,55))
+plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
+plt.savefig('box_plot_cluster_2_tfs_fpkm.png')
+plt.clf()
+
+# Cluster tfs 1
+scipy.stats.ranksums(cluster2_tfs['ES_D0'],cluster2_tfs['ES_D2'])
+scipy.stats.ranksums(cluster2_tfs['ES_D0'],cluster2_tfs['ES_D5'])
+scipy.stats.ranksums(cluster2_tfs['ES_D0'],cluster2_tfs['ES_D7'])
+scipy.stats.ranksums(cluster2_tfs['ES_D0'],cluster2_tfs['ES_D10'])
+
+
+scipy.stats.ranksums(cluster2_tfs['ES_D2'],cluster2_tfs['ES_D5'])
+scipy.stats.ranksums(cluster2_tfs['ES_D2'],cluster2_tfs['ES_D7'])
+scipy.stats.ranksums(cluster2_tfs['ES_D2'],cluster2_tfs['ES_D10'])
+
+scipy.stats.ranksums(cluster2_tfs['ES_D5'],cluster2_tfs['ES_D7'])
+scipy.stats.ranksums(cluster2_tfs['ES_D5'],cluster2_tfs['ES_D10'])
+
+scipy.stats.ranksums(cluster2_tfs['ES_D7'],cluster2_tfs['ES_D10'])
+
+
+
+
+cluster2_motifs = motif_enhancers.loc[cell_tf_values_std_cluster_2.index.values]
+cluster2_enhancers = only_rpkm_values.loc[cluster2_motifs.loc[:, (cluster2_motifs >1).any(axis=0)].columns.values]
+cluster_2_expressed_enhancers = np.concatenate((rpkm_ssp[(rpkm_ssp['ES_D5'] >= 0.5)].index.values,rpkm_sunp[(rpkm_sunp['ES_D5'] >= 1)].index.values))
+needed_rows = [row for row in cluster2_enhancers.index if row in cluster_2_expressed_enhancers]
+cluster2_enhancers_expressed = cluster2_enhancers.loc[needed_rows]
+cluster2_enhancers_expressed.to_csv("cluster_2_enhancers.csv")
+
+box = cluster2_enhancers_expressed.boxplot(column=['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'],patch_artist=True,showfliers=False,manage_xticks=False,widths = 0.6, medianprops = medianprops)
+plt.setp(box['whiskers'], color='k', linestyle='-', linewidth = 5)
+plt.setp(box['boxes'], color='k', linestyle='-', linewidth = 5)
+
+for patch, color in zip(box['boxes'], colors):
+    patch.set_facecolor(color)
+
+plt.tick_params(axis='y', direction='out')
+plt.tick_params(axis='x', direction='out')
+plt.tick_params(top='off', right='off')
+plt.grid(b=False)
+plt.ylim((-5,80))
+plt.xticks([1,2,3,4,5], ['ES_D0', 'ES_D2', 'ES_D5', 'ES_D7',  'ES_D10'])
+plt.savefig('box_plot_cluster_2_enhancers_rpkm.png')
+plt.clf()
+
+# Cluster tfs 1 e-4
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D0'],cluster2_enhancers_expressed['ES_D2'])
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D0'],cluster2_enhancers_expressed['ES_D5'])
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D0'],cluster2_enhancers_expressed['ES_D7'])
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D0'],cluster2_enhancers_expressed['ES_D10'])
+
+
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D2'],cluster2_enhancers_expressed['ES_D5'])
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D2'],cluster2_enhancers_expressed['ES_D7'])
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D2'],cluster2_enhancers_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D5'],cluster2_enhancers_expressed['ES_D7'])
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D5'],cluster2_enhancers_expressed['ES_D10'])
+
+scipy.stats.ranksums(cluster2_enhancers_expressed['ES_D7'],cluster2_enhancers_expressed['ES_D10'])
+
+
 ## Analysis of only RNA-seq
 # 1. Z-score Standardize for each cell line to see important TF's
 scaler = preprocessing.StandardScaler()
-- 
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