sphinx corrections

Author: dorimolnar

sphinx/_build/doctrees/about.doctree

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: ae80a17fba3a79d8ec53a7d5b4a765d6
+config: 14f0da3deab56c51bd3eb0ddaab4ba31
 tags: 645f666f9bcd5a90fca523b33c5a78b7

sphinx/_build/doctrees/environment.pickle

@@ -9,7 +9,7 @@ Availability
 TFpredict is available in two different versions that are merged into one branch. During execution the ``-prokaryote`` argument can be used to choose between the classification of transcription factors from two different domains:
 
 1. Eukaryotic transcription factors (default)
-2. Prokaryotic σ-factors (-prokaryote option) The algorithm itself is identical. What is different are the training data and weights for both scenarios. So, this distinction is more for convenience to directly provide preconfigured versions of TFpredict for both domains of organisms.
+2. Prokaryotic σ-factors (``-prokaryote`` option): The algorithm itself is identical. What is different are the training data and weights for both scenarios. So, this distinction is more for convenience to directly provide preconfigured versions of TFpredict for both domains of organisms.
 
 Introduction
 -------------

sphinx/_build/doctrees/getting_started.doctree

@@ -6,13 +6,13 @@ This section will guide you through the installation, setup, and first steps to
 How to get started
 -------------------
 
-The stand-alone version of TFpredict is equipped with a command-line interface which can be used for the batch processing of multiple protein sequences given in FASTA format. For convenience, TFpredict uses the webservice version of InterproScan. Thus, installing the perl stand-alone version of InterProScan (approx. 40GB) is not required. To support applications, which require the processing of a large number of sequences (e.g., the genome-wide prediction of TFs in a specific organism) TFpredict can alternatively be used with a local installation of InterProScan.
+The stand-alone version of TFpredict is equipped with a command-line interface which can be used for the batch processing of multiple protein sequences given in FASTA format. For convenience, TFpredict uses the webservice version of InterproScan. Thus, installing the perl stand-alone version of InterProScan (approx. 40GB) is not required.
 
 
 Installing TFpredict
 ---------------------
 
-Download the JAR file TFpredict from https://github.com/draeger-lab/TFpredict/releases and also the example file test_seq.fasta.
+Download the JAR file TFpredict_1.4 from https://github.com/draeger-lab/TFpredict/releases and also the example file test_seq.fasta.
 
 You can also clone this repository and build a new snapshot release using the ant script shipped with this project by executing the following command in the ``dist`` folder:
 
@@ -73,7 +73,7 @@ before executing TFpredict.
 Next Steps
 ----------
 
-Now that you have TFpredict set up, explore the detailed :ref:`how-to-use`.!
+Now that you have TFpredict set up, explore the detailed :ref:`how-to-use`!
 
 If you encounter any issues or need further assistance, please refer to other sections of this documentation or feel free to create an issue on our `GitHub repository`_. 
 

sphinx/_build/doctrees/use.doctree

@@ -17,7 +17,7 @@ The input of TFpredict is a FASTA file: contains the protein identifiers and seq
 
 .. code-block:: text
    
-   java -jar TFpredict.jar <input_filename> [OPTIONS]
+   java -jar TFpredict_1.4.jar <input_filename> [OPTIONS]
 
 Options
 --------
@@ -28,7 +28,6 @@ Options
 - ``-species <organism_name>`` Organism name (e.g., Homo sapiens). See list of `supported organisms`_.
 - ``-tfClassifier <classifier_name>`` Classifier used for TF/non-TF classification possible values: SVM_linear, NaiveBayes, KNN
 - ``-superClassifier <classifier_name>`` Classifier used for superclass prediction possible values: SVM_linear, NaiveBayes, KNN
-- ``-iprscanPath <path_to_iprscan>`` Path to iprscan executable from local InterProScan installation. Only needed if you have a local installation of InterProScan which shall be used by TFpredict.
 - ``-blastPath <path_to_blast>`` Path to "bin" directory containing BLAST executables (e.g., /opt/blast/latest). Only needed if environment variable BLAST_PATH is not set.
 - ``-ignoreCharacteristicDomains`` no classification based on predefined InterPro domains.
 - ``--help`` to display the usage of the script and an overview of the command line options.
@@ -42,11 +41,11 @@ First, you need to generate an input file in FASTA format (see :ref:`form_spec`
 - Organism (see list of `supported organisms`_)
 - Protein sequence
 
-To run TFpredict on the example input file, use the command:
+To run the newest version of TFpredict on the example input file, use the command:
 
 .. code-block:: text
    
-   java -jar TFpredict.jar test_seq.fasta
+   java -jar TFpredict_1.4.jar test_seq.fasta
 
 
 To post-process the results generated by TFpredict with SABINE to predict DNA-motives for transcription factors identified among the input protein sequences, you have to pass two additional arguments to the program. First, the destination to which the output file shall be written has to be specified, and second, the correct species has to be provided. Please ensure that SABINE supports the given species (see list of `supported organisms`_).
@@ -55,19 +54,9 @@ An exemplary call of the program which facilitates the post-processing of the re
 
 .. code-block:: text
    
-   java -jar TFpredict.jar example_input.fasta -sabineOutfile example_output.txt -species "Homo sapiens"
-
-A sutitable example.input file
-TFpredict returns an output file, which contains the results of the performed prediction steps in the SABINE input file format.
-
-If you have a local installation of the tool InterProScan, which shall be used by TFpredict, you have to pass the destination of the main executable of InterProScan as an argument to TFpredict.
-
-Assuming that InterProScan was installed to the directory ``/opt/iprscan`` you could use the following command:
-
-.. code-block:: text
-   
-   java -jar TFpredict.jar test_seq.fasta -iprscanPath /opt/iprscan/bin/iprscan
+   java -jar TFpredict_1.4.jar example_input.fasta -sabineOutfile example_output.txt -species "Homo sapiens"
 
+For a suitable example_input.fasta file (can be found in the `SABINE`_ GitHub repository) TFpredict returns an output file, which contains the results of the performed prediction steps in the SABINE input file format.
 
 
 .. _form_spec:

sphinx/_build/html/.buildinfo

@@ -107,7 +107,7 @@ <h2>Availability<a class="headerlink" href="#availability" title="Link to this h
 <p>TFpredict is available in two different versions that are merged into one branch. During execution the <code class="docutils literal notranslate"><span class="pre">-prokaryote</span></code> argument can be used to choose between the classification of transcription factors from two different domains:</p>
 <ol class="arabic simple">
 <li><p>Eukaryotic transcription factors (default)</p></li>
-<li><p>Prokaryotic σ-factors (-prokaryote option) The algorithm itself is identical. What is different are the training data and weights for both scenarios. So, this distinction is more for convenience to directly provide preconfigured versions of TFpredict for both domains of organisms.</p></li>
+<li><p>Prokaryotic σ-factors (<code class="docutils literal notranslate"><span class="pre">-prokaryote</span></code> option): The algorithm itself is identical. What is different are the training data and weights for both scenarios. So, this distinction is more for convenience to directly provide preconfigured versions of TFpredict for both domains of organisms.</p></li>
 </ol>
 </section>
 <section id="introduction">
@@ -130,7 +130,7 @@ <h2>Introduction<a class="headerlink" href="#introduction" title="Link to this h
   <hr/>
 
   <div role="contentinfo">
-    <p>&#169; Copyright 2024, authors.</p>
+    <p>&#169; Copyright 2025, Johannes Eichner, Florian Topf, Andreas Dräger, James T. Yurkovich, Michael Römer, Dóra V. Molnár, Michael Gaas.</p>
   </div>
 
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a

sphinx/_build/html/_sources/about.rst.txt

@@ -110,7 +110,7 @@ <h1 id="index">Index</h1>
   <hr/>
 
   <div role="contentinfo">
-    <p>&#169; Copyright 2024, authors.</p>
+    <p>&#169; Copyright 2025, Johannes Eichner, Florian Topf, Andreas Dräger, James T. Yurkovich, Michael Römer, Dóra V. Molnár, Michael Gaas.</p>
   </div>
 
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a

sphinx/_build/html/_sources/getting_started.rst.txt

@@ -104,11 +104,11 @@ <h1>Getting Started with TFpredict<a class="headerlink" href="#getting-started-w
 <p>This section will guide you through the installation, setup, and first steps to using TFpredict.</p>
 <section id="how-to-get-started">
 <h2>How to get started<a class="headerlink" href="#how-to-get-started" title="Link to this heading"></a></h2>
-<p>The stand-alone version of TFpredict is equipped with a command-line interface which can be used for the batch processing of multiple protein sequences given in FASTA format. For convenience, TFpredict uses the webservice version of InterproScan. Thus, installing the perl stand-alone version of InterProScan (approx. 40GB) is not required. To support applications, which require the processing of a large number of sequences (e.g., the genome-wide prediction of TFs in a specific organism) TFpredict can alternatively be used with a local installation of InterProScan.</p>
+<p>The stand-alone version of TFpredict is equipped with a command-line interface which can be used for the batch processing of multiple protein sequences given in FASTA format. For convenience, TFpredict uses the webservice version of InterproScan. Thus, installing the perl stand-alone version of InterProScan (approx. 40GB) is not required.</p>
 </section>
 <section id="installing-tfpredict">
 <h2>Installing TFpredict<a class="headerlink" href="#installing-tfpredict" title="Link to this heading"></a></h2>
-<p>Download the JAR file TFpredict from <a class="reference external" href="https://github.com/draeger-lab/TFpredict/releases">https://github.com/draeger-lab/TFpredict/releases</a> and also the example file test_seq.fasta.</p>
+<p>Download the JAR file TFpredict_1.4 from <a class="reference external" href="https://github.com/draeger-lab/TFpredict/releases">https://github.com/draeger-lab/TFpredict/releases</a> and also the example file test_seq.fasta.</p>
 <p>You can also clone this repository and build a new snapshot release using the ant script shipped with this project by executing the following command in the <code class="docutils literal notranslate"><span class="pre">dist</span></code> folder:</p>
 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>ant<span class="w"> </span>-f<span class="w"> </span>tfpredict_build.xml
 </pre></div>
@@ -158,7 +158,7 @@ <h2>Installation and configuration of BLAST<a class="headerlink" href="#installa
 </section>
 <section id="next-steps">
 <h2>Next Steps<a class="headerlink" href="#next-steps" title="Link to this heading"></a></h2>
-<p>Now that you have TFpredict set up, explore the detailed <a class="reference internal" href="use.html#how-to-use"><span class="std std-ref">How to Use TFpredict - The Manual</span></a>.!</p>
+<p>Now that you have TFpredict set up, explore the detailed <a class="reference internal" href="use.html#how-to-use"><span class="std std-ref">How to Use TFpredict - The Manual</span></a>!</p>
 <p>If you encounter any issues or need further assistance, please refer to other sections of this documentation or feel free to create an issue on our <a class="reference external" href="https://github.com/draeger-lab/TFpredict/issues">GitHub repository</a>.</p>
 </section>
 </section>
@@ -174,7 +174,7 @@ <h2>Next Steps<a class="headerlink" href="#next-steps" title="Link to this headi
   <hr/>
 
   <div role="contentinfo">
-    <p>&#169; Copyright 2024, authors.</p>
+    <p>&#169; Copyright 2025, Johannes Eichner, Florian Topf, Andreas Dräger, James T. Yurkovich, Michael Römer, Dóra V. Molnár, Michael Gaas.</p>
   </div>
 
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a

sphinx/_build/html/_sources/use.rst.txt

@@ -155,7 +155,7 @@ <h2>Citing TFpredict<a class="headerlink" href="#citing-tfpredict" title="Link t
   <hr/>
 
   <div role="contentinfo">
-    <p>&#169; Copyright 2024, authors.</p>
+    <p>&#169; Copyright 2025, Johannes Eichner, Florian Topf, Andreas Dräger, James T. Yurkovich, Michael Römer, Dóra V. Molnár, Michael Gaas.</p>
   </div>
 
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a

sphinx/_build/html/about.html

@@ -130,7 +130,7 @@ <h2>Contact<a class="headerlink" href="#contact" title="Link to this heading">
   <hr/>
 
   <div role="contentinfo">
-    <p>&#169; Copyright 2024, authors.</p>
+    <p>&#169; Copyright 2025, Johannes Eichner, Florian Topf, Andreas Dräger, James T. Yurkovich, Michael Römer, Dóra V. Molnár, Michael Gaas.</p>
   </div>
 
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a

sphinx/_build/html/genindex.html

@@ -118,7 +118,7 @@
   <hr/>
 
   <div role="contentinfo">
-    <p>&#169; Copyright 2024, authors.</p>
+    <p>&#169; Copyright 2025, Johannes Eichner, Florian Topf, Andreas Dräger, James T. Yurkovich, Michael Römer, Dóra V. Molnár, Michael Gaas.</p>
   </div>
 
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a