Repository: KohlbacherLab/epytope (language: python)

Issue:
Support multiple epitope prediction scores per tool
Most tools report multiple scores for each prediction. Currently the framework interfaces are affinity-centric, which is actually discouraged by most tool developers.

The epitope prediction method interface should support multiple scores and all scores produced by each method should be extracted from their outputs.
Notebooks + doc require porting to Python 3
The notebooks are still Python 2 and won't run with the ported lib. The docs probably also have some Python 2 specific examples.
Include interface of NetMHCII 2.3 and NetMHCIIpan 4.0
Two new NetMHC Family tools can be included into the repository
Current Class2 external tools don't predict CombinedAlleles
When I am trying to predict peptides with e.g. `NetMHCIIpan 3.0` with a `CombinedAllele` like `'HLA-DPA1*01:03-HLA-DPB1*01:01'` the output states, that the allele is not supported. However it is supported and you can observe it in the [supported_alleles](https://github.com/KohlbacherLab/epytope/blob/65fd57a77a4ad5a35e9b1f2e5ddb242ae3ccd05f/epytope/EpitopePrediction/External.py#L2254). When I change `'HLA-DPA1*01:03-HLA-DPB1*01:01'` to `'HLA-DPA1*01:03-DPB1*01:01'` in the `supported_alleles` it works. So I guess all the listed `CombinedAlleles` have an obsolete `HLA-` string in front of the beta chain

My input looked as follows in a Jupiter notebook:

```
peptides = [Peptide("SYFPEITHIFIASFS"),Peptide("FIASNGVKLSYFPEI")]
alleles = [Allele("HLA-DRB1*01:01"), Allele("HLA-DRB1*01:03"), CombinedAllele("HLA-DPA1*01:03-HLA-DPB1*01:01")]
predictor = EpitopePredictorFactory("netmhcIIpan", version="3.0")
results = predictor.predict(peptides, alleles=alleles, command='.path/to/netMHCIIpan-3.0/netMHCIIpan')
```


ANN predictor output returns peptide strings instead of peptide objects
I encountered a bug in `EpitopePrediction/ANN.py`. Analog to issue #38, the prediction result contained the string representation of peptides instead of the peptide objects. This output is not coherent with the output of the other predictors and needs to be fixed.


Discussion / hints:

Fix patch:
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 8e930f17..bc0fcd5a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -3,6 +3,22 @@
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## v3.1.0 - 2022-06-15
+
+### `Added`
+
+- [#58](https://github.com/KohlbacherLab/epytope/pull/58) - Add check for `BioMart` transcript sequence availability [#55](https://github.com/KohlbacherLab/epytope/issues/55)
+- [#59](https://github.com/KohlbacherLab/epytope/pull/59) - Add interface for `NetMHCpan 4.1` [#56](https://github.com/KohlbacherLab/epytope/issues/56)
+- [#66](https://github.com/KohlbacherLab/epytope/pull/66) - Add interface for `NetMHCIIpan 4.1` [#65](https://github.com/KohlbacherLab/epytope/issues/65)
+
+### `Changed`
+
+- [#62](https://github.com/KohlbacherLab/epytope/pull/62) - Update the supported alleles of `syfpeithi` [#60](https://github.com/KohlbacherLab/epytope/issues/60)
+
+### `Fixed`
+
+- [#53](https://github.com/KohlbacherLab/epytope/pull/53) - Fix `ANN` predictor results [#52](https://github.com/KohlbacherLab/epytope/issues/52)
+
 ## v3.0.0 - 2022-01-26
 
 Initial release of `epytope`. `epytope` is the successor project of [`FRED2`](https://github.com/FRED-2/Fred2), which was renamed to a more versioning friendly base name.
diff --git a/README.md b/README.md
index 3172b4fe..e2e4b870 100644
--- a/README.md
+++ b/README.md
@@ -3,16 +3,19 @@
 ![PyPi](https://github.com/KohlbacherLab/epytope/actions/workflows/pypi-publish.yml/badge.svg)
 ![Tests](https://github.com/KohlbacherLab/epytope/actions/workflows/python-test-conda.yml/badge.svg)
 ![Tests external](https://github.com/KohlbacherLab/epytope/actions/workflows/python-test-conda-external.yml/badge.svg)
+[![Anaconda-Server Badge](https://anaconda.org/bioconda/epytope/badges/version.svg)](https://anaconda.org/bioconda/epytope)
+[![Anaconda-Server Badge](https://anaconda.org/bioconda/epytope/badges/latest_release_date.svg)](https://anaconda.org/bioconda/epytope)
 [![License](https://img.shields.io/badge/License-BSD_3--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
-[![Anaconda-Server Badge](https://anaconda.org/bioconda/fred2/badges/installer/conda.svg)](https://conda.anaconda.org/bioconda)
+[![Anaconda-Server Badge](https://anaconda.org/bioconda/epytope/badges/installer/conda.svg)](https://conda.anaconda.org/bioconda)
+[![Anaconda-Server Badge](https://anaconda.org/bioconda/epytope/badges/downloads.svg)](https://anaconda.org/bioconda/epytope)
 
-Copyright 2014 by Benjamin Schuber,  Mathias Walzer, Philipp Brachvogel, Andras Szolek, Christopher Mohr, and Oliver Kohlbacher
+Copyright 2014 by Benjamin Schuber, Mathias Walzer, Philipp Brachvogel, Andras Szolek, Christopher Mohr, and Oliver Kohlbacher
 
 **epytope** is a framework for T-cell epitope detection, and vaccine design. It offers consistent, easy, and simultaneous access to well established prediction methods of computational immunology. **epytope** can handle polymorphic proteins and offers analysis tools to select, assemble, and design linker sequences for string-of-beads epitope-based vaccines. It is implemented in Python in a modular way and can easily be extended by user defined methods.
 
 ## Copyright
 
-epytope is released under the three clause BSD licence.
+epytope is released under the three clause BSD license.
 
 ## Installation
 
@@ -27,9 +30,10 @@ use the following commands:
 - pandas
 - pyomo>=4.0
 - svmlight
-- MySQL-python>=1.2.4
-- Biopython
+- PyMySQL
+- biopython
 - pyVCF
+- h5py<=2.10.0
 
 ### Third-Party Software (not installed through pip)
 
@@ -57,8 +61,8 @@ Currently **epytope** provides implementations of several prediction methods or
   - [MHCflurry](https://pubmed.ncbi.nlm.nih.gov/29960884/) 1.2.2, 1.4.3
   - [NetMHC](https://pubmed.ncbi.nlm.nih.gov/26515819/) 3.0, 3.4, 4.0
   - [NetMHCII](https://pubmed.ncbi.nlm.nih.gov/29315598/) 2.2, 2.3
-  - [NetMHCpan](https://pubmed.ncbi.nlm.nih.gov/28978689/) 2.4, 2.8, 3.0, 4.0
-  - [NetMHCIIpan](https://pubmed.ncbi.nlm.nih.gov/32406916/) 3.0, 3.1, 4.0
+  - [NetMHCpan](https://pubmed.ncbi.nlm.nih.gov/28978689/) 2.4, 2.8, 3.0, 4.0, 4.1
+  - [NetMHCIIpan](https://pubmed.ncbi.nlm.nih.gov/32406916/) 3.0, 3.1, 4.0, 4.1
   - [PickPocket](https://pubmed.ncbi.nlm.nih.gov/19297351/) 1.1
   - [NetCTLpan](https://pubmed.ncbi.nlm.nih.gov/20379710/) 1.1
 - Epitope Selection
@@ -71,7 +75,7 @@ Currently **epytope** provides implementations of several prediction methods or
 
 ## Getting Started
 
-Users and developers should start by reading our [wiki](https://github.com/KohlbacherLab/epytope/wiki) and [IPython tutorials](https://github.com/KohlbacherLab/epytope/tree/master/epytope/tutorials). A reference documentation is also available [online](http://fred2.readthedocs.org/en/latest/).
+Users and developers should start by reading our [wiki](https://github.com/KohlbacherLab/epytope/wiki) and [IPython tutorials](https://github.com/KohlbacherLab/epytope/tree/master/epytope/tutorials). A reference documentation is also available [online](http://epytope.readthedocs.org/en/latest/).
 
 ## How to Cite
 
diff --git a/epytope/Core/Generator.py b/epytope/Core/Generator.py
index 0fd83850..64549b74 100644
--- a/epytope/Core/Generator.py
+++ b/epytope/Core/Generator.py
@@ -12,6 +12,7 @@
 
 """
 
+import logging
 import warnings
 from itertools import chain
 
@@ -243,7 +244,7 @@ def _generate_combinations(tId, vs, seq, usedVs, offset, isReverse):
         #print tId
         query = dbadapter.get_transcript_information(tId, type=id_type, _db=db)
         if query is None:
-            warnings.warn("Transcript with ID %s not found in DB"%tId)
+            logging.warning("Transcript with ID %s not found in DB or sequence unavailable"%tId)
             continue
 
         tSeq = query[EAdapterFields.SEQ]
@@ -349,7 +350,7 @@ def _generate_combinations(tId, vs, seq, usedVs, offset, isReverse=False):
     for tId, vs in transToVar.items():
         query = dbadapter.get_transcript_information(tId, type=id_type, _db=db)
         if query is None:
-            warnings.warn("Transcript with ID %s not found in DB"%tId)
+            logging.warning("Transcript with ID %s not found in DB or sequence unavailable"%tId)
             continue
 
         tSeq = query[EAdapterFields.SEQ]
diff --git a/epytope/Data/pssms/syfpeithi/mat/A_0300_9.py b/epytope/Data/pssms/syfpeithi/mat/A_0300_9.py
deleted file mode 100644
index 3f3d87a3..00000000
--- a/epytope/Data/pssms/syfpeithi/mat/A_0300_9.py
+++ /dev/null
@@ -1,1 +0,0 @@
-A_0300_9 = {0: {'A': 4, 'C': 0, 'D': 4, 'E': 4, 'F': 0, 'G': 4, 'H': 0, 'I': 0, 'K': 4, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 4, 'S': 4, 'T': 4, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 1: {'A': 10, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 10, 'K': 0, 'L': 10, 'M': 10, 'N': 0, 'P': 0, 'Q': 10, 'R': 0, 'S': 10, 'T': 10, 'V': 10, 'W': 0, 'Y': 0, 'X': 0}, 2: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 3: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 4: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 5: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 6: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 7: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0, 'I': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 0, 'X': 0}, 8: {'A': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 10, 'G': 0, 'H': 10, 'I': 0, 'K': 10, 'L': 0, 'M': 0, 'N': 0, 'P': 0, 'Q': 0, 'R': 10, 'S': 0, 'T': 0, 'V': 0, 'W': 0, 'Y': 10, 'X': 0}}
\ No newline at end of file
diff --git a/epytope/EpitopePrediction/ANN.py b/epytope/EpitopePrediction/ANN.py
index b3b7ba1e..cc8e4030 100644
--- a/epytope/EpitopePrediction/ANN.py
+++ b/epytope/EpitopePrediction/ANN.py
@@ -249,7 +249,7 @@ def predict(self, peptides, alleles=None, binary=False, **kwargs):
 
             # create EpitopePredictionResult object. This is a multi-indexed DataFrame
             # with Allele, Method and Score type as multi-columns and peptides as rows
-            df_result = EpitopePredictionResult.from_dict(result, pep_groups, self.name)
+            df_result = EpitopePredictionResult.from_dict(result, peptide_objects.values(), self.name)
 
             return df_result
 
@@ -534,7 +534,7 @@ def predict(self, peptides, alleles=None, binary=False, **kwargs):
 
             # create EpitopePredictionResult object. This is a multi-indexed DataFrame
             # with Allele, Method and Score type as multi-columns and peptides as rows
-            df_result = EpitopePredictionResult.from_dict(result, pep_groups, self.name)
+            df_result = EpitopePredictionResult.from_dict(result, peptide_objects.values(), self.name)
             return df_result
 
 except BadSignatureException:
@@ -804,7 +804,7 @@ def predict(self, peptides, alleles=None, binary=False, **kwargs):
 
             # create EpitopePredictionResult object. This is a multi-indexed DataFrame
             # with Allele, Method and Score type as multi-columns and peptides as rows
-            df_result = EpitopePredictionResult.from_dict(result, pep_groups, self.name)
+            df_result = EpitopePredictionResult.from_dict(result, peptide_objects.values(), self.name)
             return df_result
 
 except BadSignatureException:
diff --git a/epytope/EpitopePrediction/External.py b/epytope/EpitopePrediction/External.py
index 8d93edcc..1049254c 100755
--- a/epytope/EpitopePrediction/External.py
+++ b/epytope/EpitopePrediction/External.py
@@ -1476,7 +1476,6 @@ def parse_external_result(self, file):
         return result
 
 
-
 class NetMHCpan_4_0(NetMHCpan_3_0):
     """
         Implements the NetMHC binding version 4.0
@@ -1517,6 +1516,47 @@ def parse_external_result(self, file):
 
 
 
+class NetMHCpan_4_1(NetMHCpan_4_0):
+    """
+        Implements the NetMHC binding version 4.1
+        Supported  MHC alleles currently only restricted to HLA alleles.
+    """
+    __version = "4.1"
+    __command = "netMHCpan -p {peptides} -a {alleles} {options} -xls -xlsfile {out}"
+    @property
+    def version(self):
+        return self.__version
+
+    @property
+    def command(self):
+        return self.__command
+
+    __alleles = 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+
+    def parse_external_result(self, file):
+        """
+        Parses external results and returns the result containing the predictors string representation
+        of alleles and peptides.
+
+        :param str file: The file path or the external prediction results
+        :return: A dictionary containing the prediction results
+        :rtype: dict
+        """
+        f = csv.reader(open(file, "r"), delimiter = '\t')
+        scores = defaultdict(defaultdict)
+        ranks = defaultdict(defaultdict)
+        alleles = [x for x in next(f) if x != ""]
+        next(f, None) # Avoid header column, only access raw and rank scores
+        for row in f:
+            pep_seq = row[PeptideIndex.NETMHCPAN_4_1]
+            for i, a in enumerate(alleles):
+                scores[a][pep_seq] = float(row[ScoreIndex.NETMHCPAN_4_1 + i * Offset.NETMHCPAN_4_1])
+                ranks[a][pep_seq] = float(row[RankIndex.NETMHCPAN_4_1 + i * Offset.NETMHCPAN_4_1])
+        # Create dictionary with hierarchy: {'Allele1': {'Score': {'Pep1': Score1, 'Pep2': Score2,..}, 'Rank': {'Pep1': RankScore1, 'Pep2': RankScore2,..}}, 'Allele2':...}
+        result = {allele: {metric:(list(scores.values())[j] if metric == "Score" else list(ranks.values())[j]) for metric in ["Score", "Rank"]} for j, allele in enumerate(alleles)}
+        return result
+
+
 class NetMHCstabpan_1_0(AExternalEpitopePrediction):
     """
     Implements a wrapper to NetMHCstabpan 1.0
@@ -7193,6 +7233,50 @@ def parse_external_result(self, file):
 
         return result
 
+class NetMHCIIpan_4_1(NetMHCIIpan_4_0):
+    """
+    Implementation of NetMHCIIpan 4.1 adapter.
+    """
+
+    __command = "netMHCIIpan -f {peptides} -inptype 1 -a {alleles} {options} -xls -xlsfile {out}"
+    __version = "4.1"
+
+    @property
+    def version(self):
+        """The version of the predictor"""
+        return self.__version
+
+    @property
+    def command(self):
+        """
+        Defines the commandline call for external tool
+        """
+        return self.__command 
+
+    def parse_external_result(self, file):
+        """
+        Parses external results and returns the result containing the predictors string representation
+        of alleles and peptides.
+
+        :param str file: The file path or the external prediction results
+        :return: A dictionary containing the prediction results
+        :rtype: dict
+        """
+        f = csv.reader(open(file, "r"), delimiter='\t')
+        scores = defaultdict(defaultdict)
+        ranks = defaultdict(defaultdict)
+        alleles = [x for x in set([x for x in next(f) if x != ""])]
+        next(f)
+        for row in f:
+            pep_seq = row[PeptideIndex.NETMHCIIPAN_4_1]
+            for i, a in enumerate(alleles):
+                scores[a][pep_seq] = float(row[ScoreIndex.NETMHCIIPAN_4_1 + i * Offset.NETMHCIIPAN_4_1])
+                ranks[a][pep_seq] = float(row[RankIndex.NETMHCIIPAN_4_1 + i * Offset.NETMHCIIPAN_4_1])
+                # Create dictionary with hierarchy: {'Allele1': {'Score': {'Pep1': Score1, 'Pep2': Score2,..}, 'Rank': {'Pep1': RankScore1, 'Pep2': RankScore2,..}}, 'Allele2':...}
+        result = {allele: {metric:(list(scores.values())[j] if metric == "Score" else list(ranks.values())[j]) for metric in ["Score", "Rank"]} for j, allele in enumerate(alleles)}
+
+        return result
+
 class PickPocket_1_1(AExternalEpitopePrediction):
     """
     Implementation of PickPocket adapter.
@@ -8394,12 +8478,14 @@ class PeptideIndex(IntEnum):
     NETMHCPAN_2_8 = 1
     NETMHCPAN_3_0 = 1
     NETMHCPAN_4_0 = 1
+    NETMHCPAN_4_1 = 1
     NETMHCSTABPAN_1_0 = 1
     NETMHCII_2_2 = 2
     NETMHCII_2_3 = 2
     NETMHCIIPAN_3_0 = 1
     NETMHCIIPAN_3_1 = 1
     NETMHCIIPAN_4_0 = 1
+    NETMHCIIPAN_4_1 = 1
     PICKPOCKET_1_1 = 2
     NETCTLPAN_1_1 = 3
 
@@ -8413,12 +8499,14 @@ class ScoreIndex(IntEnum):
     NETMHCPAN_2_8 = 3
     NETMHCPAN_3_0 = 4
     NETMHCPAN_4_0 = 5
+    NETMHCPAN_4_1 = 5
     NETMHCSTABPAN_1_0 = 6
     NETMHCII_2_2 = 4
     NETMHCII_2_3 = 5
     NETMHCIIPAN_3_0 = 3
     NETMHCIIPAN_3_1 = 3
-    NETMHCIIPAN_4_0 = 3
+    NETMHCIIPAN_4_0 = 4
+    NETMHCIIPAN_4_1 = 5
     PICKPOCKET_1_1 = 4
     NETCTLPAN_1_1 = 7
 
@@ -8429,11 +8517,13 @@ class RankIndex(IntEnum):
     NETMHCPAN_2_8 = 5
     NETMHCPAN_3_0 = 6
     NETMHCPAN_4_0 = 7
+    NETMHCPAN_4_1 = 6
     NETMHCSTABPAN_1_0 = 5
     NETMHCII_2_3 = 7
     NETMHCIIPAN_3_0 = 5
     NETMHCIIPAN_3_1 = 5
     NETMHCIIPAN_4_0 = 5
+    NETMHCIIPAN_4_1 = 6
 
 class Offset(IntEnum):
     """
@@ -8444,11 +8534,13 @@ class Offset(IntEnum):
     NETMHCPAN_2_8 = 3
     NETMHCPAN_3_0 = 4
     NETMHCPAN_4_0 = 5
+    NETMHCPAN_4_1 = 4
     NETMHCSTABPAN_1_0_W_SCORE = 8
     NETMHCSTABPAN_1_0_WO_SCORE = 3
     NETMHCIIPAN_3_0 = 3
     NETMHCIIPAN_3_1 = 3
-    NETMHCIIPAN_4_0 = 1
+    NETMHCIIPAN_4_0 = 0
+    NETMHCIIPAN_4_1 = 3
 
 class HLAIndex(IntEnum):
     """
diff --git a/epytope/EpitopePrediction/PSSM.py b/epytope/EpitopePrediction/PSSM.py
index 24a2df11..b6a2f9be 100644
--- a/epytope/EpitopePrediction/PSSM.py
+++ b/epytope/EpitopePrediction/PSSM.py
@@ -114,12 +114,8 @@ class Syfpeithi(APSSMEpitopePrediction):
         SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics, 50(3-4), 213-219.
     """
     __alleles = frozenset(
-        ['HLA-B*15:10', 'HLA-B*41:01', 'HLA-B*37:01', 'HLA-B*27:05', 'HLA-B*38:01', 'HLA-A*02:01', 'HLA-B*47:01',
-         'HLA-A*26:01', 'HLA-B*37:01', 'HLA-DRB1*11:01', 'HLA-B*50:01', 'HLA-B*07:02', 'HLA-A*68:01', 'HLA-A*24:02',
-         'HLA-DRB1*15:01', 'HLA-B*15:01', 'HLA-B*45:01', 'HLA-A*11:01', 'HLA-A*03:01', 'HLA-B*40:01', 'HLA-DRB1*03:01',
-         'HLA-B*39:01', 'HLA-DRB1*01:01', 'HLA-B*51:01', 'HLA-B*39:02', 'HLA-B*08:01', 'HLA-B*18:01', 'HLA-B*44:02',
-         'HLA-B*49:01', 'HLA-DRB1*07:01', 'HLA-B*14:02', 'HLA-A*01:01'])
-    __supported_length = frozenset([8, 9, 10, 11])
+        ['HLA-A*01:01','HLA-A*02:01','HLA-A*03:01','HLA-A*11:01','HLA-A*24:02','HLA-A*26:01','HLA-A*31:01','HLA-A*32:01','HLA-A*33:01','HLA-A*66:01','HLA-A*68:01','HLA-B*07:02','HLA-B*08:01','HLA-B*13:02','HLA-B*14:02','HLA-B*15:01','HLA-B*15:16','HLA-B*18:01','HLA-B*27:05','HLA-B*27:09','HLA-B*35:01','HLA-B*37:01','HLA-B*38:01','HLA-B*39:01','HLA-B*39:02','HLA-B*40:01','HLA-B*40:02','HLA-B*41:01','HLA-B*44:02','HLA-B*45:01','HLA-B*47:01','HLA-B*49:01','HLA-B*50:01','HLA-B*51:01','HLA-B*53:01','HLA-B*57:01','HLA-B*58:01','HLA-B*58:02','HLA-C*01:02','HLA-C*02:02','HLA-C*03:03','HLA-C*03:04','HLA-C*04:01','HLA-C*05:01','HLA-C*06:01','HLA-C*06:02','HLA-C*07:01','HLA-C*07:02','HLA-C*08:02','HLA-C*12:03','HLA-C*14:02','HLA-C*15:02','HLA-C*16:01','HLA-C*17:01','HLA-DRB1*01:01','HLA-DRB1*03:01','HLA-DRB1*07:01','HLA-DRB1*11:01','HLA-DRB1*15:01','HLA-G*01:01','H-2-Db','H-2-Kb','H-2-Kd','H-2-Ld'])
+    __supported_length = frozenset([8, 9, 10, 11, 12, 13])
     __name = "syfpeithi"
     __version = "1.0"
 
diff --git a/epytope/IO/MartsAdapter.py b/epytope/IO/MartsAdapter.py
index 47e34390..4f9f7969 100755
--- a/epytope/IO/MartsAdapter.py
+++ b/epytope/IO/MartsAdapter.py
@@ -100,13 +100,11 @@ def get_product_sequence(self, product_id, **kwargs):
             + self.biomart_attribute%("external_gene_name")  \
             + self.biomart_tail
 
-        # logging.warn(rq_n)
         tsvreader = csv.DictReader((urllib.request.urlopen(self.biomart_url +
                                                           urllib.parse.quote(rq_n))).read().decode('utf-8').splitlines(), dialect='excel-tab')
         tsvselect = [x for x in tsvreader]
         if not tsvselect:
             logging.warning("There seems to be no Proteinsequence for " + str(product_id))
-            #print self.biomart_url+rq_n
             return None
         self.sequence_proxy[product_id] = tsvselect[0]["Peptide"][:-1] if tsvselect[0]["Peptide"].endswith('*')\
             else tsvselect[0]["Peptide"]
@@ -157,8 +155,10 @@ def get_transcript_sequence(self, transcript_id, **kwargs):
                                                    urllib.parse.quote(rq_n))).read().decode('utf-8').splitlines(), dialect='excel-tab')
         tsvselect = [x for x in tsvreader]
         if not tsvselect:
-            logging.warning("There seems to be no transcript sequence for " + str(transcript_id))
-            #print self.biomart_url+rq_n
+            logging.warning("No transcript sequence available for " + str(transcript_id))
+            return None
+        elif 'Sequence unavailable' in tsvselect[0]['Coding sequence']:
+            logging.warning("No transcript sequence available for " + str(transcript_id))
             return None
 
         self.sequence_proxy[transcript_id] = tsvselect[0]['Coding sequence']
@@ -210,6 +210,9 @@ def get_transcript_information(self, transcript_id, **kwargs):
         if not tsvselect:
             logging.warning("No Information on transcript %s"%transcript_id)
             return None
+        elif 'Sequence unavailable' in tsvselect[0]['Coding sequence']:
+            logging.warning("No transcript sequence available for " + str(transcript_id))
+            return None
 
         self.ids_proxy[transcript_id] = {EAdapterFields.SEQ: tsvselect[0]['Coding sequence'],
                                                   EAdapterFields.GENE: tsvselect[0].get('Associated Gene Name', ""),
@@ -596,8 +599,6 @@ def get_variant_ids(self, **kwargs):
                 + self.biomart_attribute%("refseq_peptide")
         rq_n += self.biomart_attribute%("uniprot_swissprot") + self.biomart_tail
 
-        # logging.warning(rq_n)
-
         tsvreader = csv.DictReader((urllib.request.urlopen(self.biomart_url +
                                                            urllib.parse.quote(rq_n)).read()).decode('utf-8').splitlines(), dialect='excel-tab')
         if ensemble_only:
diff --git a/epytope/doc/conf.py b/epytope/doc/conf.py
index a0660037..6bc3568e 100644
--- a/epytope/doc/conf.py
+++ b/epytope/doc/conf.py
@@ -269,7 +269,7 @@ def __getattr__(cls, name):
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
 man_pages = [
-    (master_doc, 'fred2', 'epytope Documentation',
+    (master_doc, 'epytope', 'epytope Documentation',
      [author], 1)
 ]
 
diff --git a/epytope/tutorials/GeneratorUsage.ipynb b/epytope/tutorials/GeneratorUsage.ipynb
index 21ddecf1..f8fd135f 100644
--- a/epytope/tutorials/GeneratorUsage.ipynb
+++ b/epytope/tutorials/GeneratorUsage.ipynb
@@ -192,7 +192,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/antonia/PycharmProjects/Kfred/epytope/Core/Generator.py:57: UserWarning: For NM_001190266 bp does not match ref of assigned variant Variant(g.234183368A>G). Pos 645, var ref A, seq ref C \n",
+      "epytope/Core/Generator.py:57: UserWarning: For NM_001190266 bp does not match ref of assigned variant Variant(g.234183368A>G). Pos 645, var ref A, seq ref C \n",
       "  seq[pos]))\n"
      ]
     },
@@ -277,7 +277,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/antonia/opt/miniconda3/envs/epy/lib/python3.7/site-packages/Bio/Seq.py:2338: BiopythonWarning: Partial codon, len(sequence) not a multiple of three. Explicitly trim the sequence or add trailing N before translation. This may become an error in future.\n",
+      "/opt/miniconda3/envs/epy/lib/python3.7/site-packages/Bio/Seq.py:2338: BiopythonWarning: Partial codon, len(sequence) not a multiple of three. Explicitly trim the sequence or add trailing N before translation. This may become an error in future.\n",
       "  BiopythonWarning,\n"
      ]
     }
diff --git a/setup.py b/setup.py
index 1aa49bed..6a320345 100644
--- a/setup.py
+++ b/setup.py
@@ -6,33 +6,9 @@
 
 here = path.abspath(path.dirname(__file__))
 
-#d2s_src_dir = path.join(path.join('epytope', 'Distance2Self'), 'src')
-#d2s_module = Extension('epytope.d2s',
-#                       define_macros=[('MAJOR_VERSION', '1'),
-#                                      ('MINOR_VERSION', '0')],
-#                       include_dirs=[d2s_src_dir],
-#                       libraries=['boost_serialization', 'boost_python'],
-#                       #library_dirs = ['/usr/local/lib'],
-#                       depends=[path.join(d2s_src_dir, 'distance2self.hpp')],
-#                       sources=[path.join(d2s_src_dir, 'distance2self.cpp')])
-
-
-#data_files = list()
-# directories = glob.glob('epytope/Data/svms/*/')
-# for directory in directories:
-#     files = glob.glob(directory + '*')
-#     data_files.append((directory, files))
-#directories = glob.glob('epytope/Data/examples/')
-#for directory in directories:
-#    files = glob.glob(directory + '*')
-#    data_files.append((directory, files))
-#
-# d2s_files = glob.glob(d2s_dir + "src/" + '*')
-#data_files.append((d2s_dir + "src/", d2s_files))
-
 #for packaging files must be in a package (with init) and listed in package_data
 # package-externals can be included with data_files,
-# and there is a bug in patternmatching http://bugs.python.org/issue19286
+# and there is a bug in patter nmatching http://bugs.python.org/issue19286
 # install unclear for data_files
 
 # Read the contents of the README.md file for use as long_description
@@ -45,7 +21,7 @@
     name='epytope',
 
     # Version:
-    version='3.0.0',
+    version='3.1.0',
 
     description='A Framework for Epitope Detection and Vaccine Design',
     long_description=long_description,
@@ -89,7 +65,6 @@
     # Specify  packages via find_packages() and exclude the tests and 
     # documentation:
     packages=find_packages(),
-    #packages=find_packages(exclude=['epytope.test', 'epytope.doc', 'epytope.tutorials']),
 
     # If there are data files included in your packages that need to be
     # installed, specify them here.  If using Python 2.6 or less, then these
@@ -100,7 +75,6 @@
             'epytope.Data.svms.svmtap': ['*'],
             'epytope.Data.svms.svmhc': ['*'],
             'epytope.Data.svms.unitope': ['*'],
-            #'epytope.Distance2Self': ['src/*'],  #does not get installed, because the src folder is no package folder - compiles ok
     },
 
     data_files = [
@@ -124,9 +98,6 @@
     #    ],
     #},
 
-    #ext_modules=[helloworld_module],
-    #ext_modules=[d2s_module],
-
     # Run-time dependencies. (will be installed by pip when epytope is installed)
     # TODO: find alternative for SMVlight scikitlearn
     install_requires=[


Test patch:
diff --git a/.github/workflows/python-test-conda-external.yml b/.github/workflows/python-test-conda-external.yml
index fbc3b89c..9d269e80 100644
--- a/.github/workflows/python-test-conda-external.yml
+++ b/.github/workflows/python-test-conda-external.yml
@@ -40,7 +40,7 @@ jobs:
         echo "PATH=$PATH"
     - name: Set up Python ${{ matrix.python-version }}
       run: |
-        $CONDA/bin/conda create -p /tmp/condaenv python==${{ matrix.python-version }}'.*' setuptools"==52.0"
+        $CONDA/bin/conda create -p /tmp/condaenv python==${{ matrix.python-version }}'.*' setuptools"==52.0" protobuf"<=3.20.1"
     - name: Activate conda environment
       run: |
         echo "/tmp/condaenv/bin" >> $GITHUB_PATH
diff --git a/.github/workflows/python-test-conda.yml b/.github/workflows/python-test-conda.yml
index cadb590d..583990d0 100644
--- a/.github/workflows/python-test-conda.yml
+++ b/.github/workflows/python-test-conda.yml
@@ -22,7 +22,7 @@ jobs:
         echo "CONDA_PKGS_DIRS=/tmp/condapkgs" >> $GITHUB_ENV
     - name: Set up Python ${{ matrix.python-version }}
       run: |
-        $CONDA/bin/conda create -p /tmp/condaenv python==${{ matrix.python-version }}'.*' setuptools"==52.0"
+        $CONDA/bin/conda create -p /tmp/condaenv python==${{ matrix.python-version }}'.*' setuptools"==52.0" protobuf"<=3.20.1"
     - name: Activate conda environment
       run: |
         echo "/tmp/condaenv/bin" >> $GITHUB_PATH