diff --git a/docs/commandline_tools.rst b/docs/commandline_tools.rst index 20f7cbe56b36bcbbffc5037bb303ad7ce3ebb3ea..dc92a15c3c0bf39b9df44dde94dda9577dc0e2c5 100644 --- a/docs/commandline_tools.rst +++ b/docs/commandline_tools.rst @@ -18,4 +18,38 @@ See also the :ref:`tutorial <commandline_tutorial>`. .. autoprogram:: mhcflurry.downloads_command:parser :prog: mhcflurry-downloads +.. _mhcflurry-class1-train-allele-specific-models: + +.. autoprogram:: mhcflurry.train_allele_specific_models_command:parser + :prog: mhcflurry-class1-train-allele-specific-models + +.. _mhcflurry-class1-select-allele-specific-models: + +.. autoprogram:: mhcflurry.select_allele_specific_models_command:parser + :prog: mhcflurry-class1-select-allele-specific-models + +.. _mhcflurry-class1-train-pan-allele-models: + +.. autoprogram:: mhcflurry.train_pan_allele_models_command:parser + :prog: mhcflurry-class1-train-pan-allele-models + +.. _mhcflurry-class1-select-pan-allele-models: + +.. autoprogram:: mhcflurry.select_pan_allele_models_command:parser + :prog: mhcflurry-class1-select-pan-allele-models + +.. _mhcflurry-class1-train-processing-models: + +.. autoprogram:: mhcflurry.train_processing_models_command:parser + :prog: mhcflurry-class1-train-processing-models + +.. _mhcflurry-class1-select-processing-models: + +.. autoprogram:: mhcflurry.select_processing_models_command:parser + :prog: mhcflurry-class1-select-processing-models + +.. _mhcflurry-class1-train-presentation-models: + +.. autoprogram:: mhcflurry.train_presentation_models_command:parser + :prog: mhcflurry-class1-train-presentation-models diff --git a/docs/commandline_tutorial.rst b/docs/commandline_tutorial.rst index 2014ec5538b4f8800ead01bb59ca8f105233e661..874f68606fb29f138e966345c3f07105cd1ca991 100644 --- a/docs/commandline_tutorial.rst +++ b/docs/commandline_tutorial.rst @@ -33,7 +33,7 @@ as well as an antigen processing (AP) predictor. .. note:: The code we use for *generating* the downloads is in the - ``downloads_generation`` directory in the repository. + ``downloads_generation`` directory in the repository (https://github.com/openvax/mhcflurry/tree/master/downloads-generation) Generating predictions @@ -99,7 +99,7 @@ sequences: .. literalinclude:: /example.fasta Here's the ``mhcflurry-predict-scan`` invocation to scan the proteins for -binders to either of two MHC I genotypes: +binders to either of two MHC I genotypes (using a 100 nM threshold): .. command-output:: mhcflurry-predict-scan @@ -107,8 +107,8 @@ binders to either of two MHC I genotypes: --alleles HLA-A*02:01,HLA-A*03:01,HLA-B*57:01,HLA-B*45:01,HLA-C*02:02,HLA-C*07:02 HLA-A*01:01,HLA-A*02:06,HLA-B*44:02,HLA-B*07:02,HLA-C*01:02,HLA-C*03:01 - --results-filtered affinity_percentile - --threshold-affinity-percentile 1.0 + --results-filtered affinity + --threshold-affinity 100 :nostderr: See the :ref:`mhcflurry-predict-scan` docs for more options. diff --git a/docs/example.fasta b/docs/example.fasta index ea095115509e108927979079136d5ff5b358d864..aa8623454fdc8aff287b66500a4e233c6f044493 100644 --- a/docs/example.fasta +++ b/docs/example.fasta @@ -1,6 +1,4 @@ >protein1 -MDSKGSSQKGSRLLLLLVVSNLLLCQGVVSTPVCPNGPGNCQV -EMFNEFDKRYAQGKGFITMALNSCHTSSLPTPEDKEQAQQTHH +MSSSSTPVCPNGPGNCQV >protein2 -VTEVRGMKGAPDAILSRAIEIEEENKRLLEGMEMIFGQVIPGA -ARYSAFYNLLHCLRRDSSKIDTYLKLLNCRIIYNNNC +MVENKRLLEGMEMIFGQVIPGA diff --git a/docs/intro.rst b/docs/intro.rst index 5b5f3581e5ab2dbd80193dcdd75f7f2bff0a8fb4..e1ebba0ccbde730090d37b729b30113da39b7147 100644 --- a/docs/intro.rst +++ b/docs/intro.rst @@ -2,7 +2,7 @@ Introduction and setup ======================= MHCflurry is an open source package for peptide/MHC I binding affinity prediction. It -attempts to provide competitive accuracy with a fast and documented implementation. +aims to provide competitive accuracy with a fast and documented implementation. You can download pre-trained MHCflurry models fit to mass spec-identified MHC I ligands and peptide/MHC affinity measurements deposited in IEDB (plus a few other @@ -63,7 +63,7 @@ tensorflow. .. code-block:: shell - $ conda create -q -n mhcflurry-env python=3.6 tensorflow + $ conda create -q -n mhcflurry-env python=3.6 'tensorflow<2.0.0' $ source activate mhcflurry-env Then continue as above: