Merge pull request #5 from aweimann/master

Pfam annotation fixed, hmm2gff.py execution fixed

Dockerfile

@@ -13,8 +13,8 @@ RUN echo "deb http://archive.ubuntu.com/ubuntu trusty-backports main restricted
 RUN apt-get update
 RUN apt-get install -y hmmer prodigal
 RUN apt-get install -y wget 
-COPY dist/traitar-1.0.1.tar.gz /tmp
+COPY dist/traitar-1.0.4.tar.gz /tmp
 COPY traitar/data/sample_data /tmp/sample_data
-RUN pip install /tmp/traitar-1.0.1.tar.gz
+RUN pip install /tmp/traitar-1.0.4.tar.gz
 COPY Pfam-A.hmm /tmp
 RUN traitar pfam --local /tmp

setup.py

@@ -25,6 +25,6 @@
         license='GNU General Public License, version 3 (GPL-3.0)',
         packages= ['traitar'],
         include_package_data = True,
-        scripts = ['traitar/traitar', 'traitar/merge_preds.py', 'traitar/heatmap.py', 'traitar/domtblout2gene_generic.py', 'traitar/predict.py', 'traitar/hmmer2filtered_best.py'],
+        scripts = ['traitar/traitar', 'traitar/merge_preds.py', 'traitar/heatmap.py', 'traitar/domtblout2gene_generic.py', 'traitar/predict.py', 'traitar/hmmer2filtered_best.py', 'traitar/hmm2gff.py'],
         zip_safe=False,
         install_requires = ["pandas >= 0.13.1", "matplotlib >= 1.3.1", "numpy >= 1.6", "scipy >= 0.13.3"])

traitar/_version.py

@@ -1 +1 @@
-__version__ = "1.0.3"
+__version__ = "1.0.4"

traitar/hmmer2filtered_best.py

@@ -3,7 +3,7 @@
 import sys
 import pandas as ps
 from StringIO import StringIO
-hmmer_colnames = ['target name','accession','tlen','query name','accession','qlen','E-value','score','bias','#','of','c-Evalue','i-Evalue','score','bias','from','to','from','to','from','to','acc','description of target']
+hmmer_colnames = ['target name','target accession','tlen','query name','accession','qlen','E-value','score_overall','bias_overall','#','of','c-Evalue','i-Evalue','score_domain','bias_domain','from_hmm','to_hmm','ali_from','ali_to','env_from','env_to','acc','description of target']
 def apply_thresholds(infile_f, eval_threshold, bit_score_thresh, out_filt_f, out_excl_f):
     """parse HMMER output file and apply thresholds for e-valu and bit score)"""
     #preparse lines by replacing white space delimitation by tabs

traitar/traitar

@@ -244,7 +244,7 @@ class Traitar:
 
     def run_feature_track_generation(self, in_samples, mode, gene_gffs = None, gene_gff_type = "prodigal"):
         #create output directory for the pfam annotation 
-        hmm2gff = "%(phenolyzer)s/hmm2gff.py %(out_dir)s/pfam_annotation/%(sample)s_filtered_best.dat %(gene_gff)s  %(out_gff_dir)s %(sample)s " + gene_gff_type + " %(model_tar)s %(predicted_pts)s"
+        hmm2gff = "hmm2gff.py %(out_dir)s/pfam_annotation/%(sample)s_filtered_best.dat %(gene_gff)s  %(out_gff_dir)s %(sample)s " + gene_gff_type + " %(model_tar)s %(predicted_pts)s"
         #read in phypat predictions
         phypat_preds = ps.read_csv(os.path.join(self.phypat_dir, "predictions_majority-vote.txt"), index_col = 0, sep = "\t")
         phypat_pgl_preds = ps.read_csv(os.path.join(self.phypat_pgl_dir, "predictions_majority-vote.txt"), index_col = 0, sep = "\t")