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-# How to create configs
-
-### The sample config
-
-The sample config should be in [__JSON__](http://www.json.org/) format
-
-- First field should have the key __"samples"__
-- Second field should contain the __"libraries"__
-- Third field contains __"R1" or "R2"__ or __"bam"__
-- The fastq input files can be provided zipped and un zipped
-
-#### Example sample config
-~~~
-    {  
-       "samples":{  
-          "Sample_ID1":{  
-             "libraries":{  
-                "MySeries_1":{  
-                   "R1":"Youre_R1.fastq.gz",
-                   "R2":"Youre_R2.fastq.gz"
-                }
-             }
-          }
-       }
-    }
-~~~
-
-- For BAM files as input one should use a config like this:
-  
-~~~
-    {
-       "samples":{  
-          "Sample_ID_1":{  
-             "libraries":{  
-                "Lib_ID_1":{  
-                   "bam":"MyFirst.bam"
-                },
-                "Lib_ID_2":{  
-                   "bam":"MySecond.bam"
-                }
-             }
-          }
-       }
-    }
-~~~
-
-
-Note that there is a tool called [SamplesTsvToJson](tools/SamplesTsvToJson.md) this enables a user to get the sample config without any chance of creating a wrongly formatted JSON file.
-
-
-### The settings config
-The settings config enables a user to alter the settings for almost all settings available in the tools used for a given pipeline.
-This config file should be written in JSON format. It can contain setup settings like references for the tools used,
-if the pipeline should use chunking or setting memory limits for certain programs almost everything can be adjusted trough this config file.
-One could set global variables containing settings for all tools used in the pipeline or set tool specific options one layer deeper into the JSON file.
-E.g. in the example below the settings for Picard tools are altered only for Picard and not global. 
-
-~~~
-"picard": { "validationstringency": "LENIENT" } 
-~~~
-
-Global setting examples are:
-~~~
-"java_gc_timelimit": 98,
-"numberchunks": 25,
-"chunking": true
-~~~
-
-
-----
-
-#### References
-Pipelines and tools that use references should now use the reference module. This gives some more fine-grained control over references.
-E.g. pipelines and tools that use a fasta references file should now set value `reference_fasta`.
-Additionally, we can set `reference_name` for the name to be used (e.g. `hg19`). If unset, Biopet will default to `unknown`.
-It is also possible to set the `species` flag. Again, we will default to `unknown` if unset.
-
-#### Example settings config
-~~~
-{
-        "reference_fasta": "/references/hg19_nohap/ucsc.hg19_nohap.fasta",
-        "reference_name": "hg19_nohap",
-        "species": "homo_sapiens",
-        "dbsnp": "/references/hg19_nohap/dbsnp_137.hg19_nohap.vcf",
-        "joint_variantcalling": false,
-        "haplotypecaller": { "scattercount": 100 },
-        "multisample": { "haplotypecaller": { "scattercount": 1000 } },
-        "picard": { "validationstringency": "LENIENT" },
-        "library_variantcalling_temp": true,
-        "target_bed_temp": "analysis/target.bed",
-        "min_dp": 5,
-        "bedtools": {"exe":"/BEDtools/bedtools-2.17.0/bin/bedtools"},
-        "bam_to_fastq": true,
-        "baserecalibrator": { "memory_limit": 8, "vmem":"16G" },
-        "samtofastq": {"memory_limit": 8, "vmem": "16G"},
-        "java_gc_timelimit": 98,
-        "numberchunks": 25,
-        "chunking": true,
-        "haplotypecaller": { "scattercount": 1000 }
-}
-~~~
-
-### JSON validation
-
-To check if the JSON file created is correct we can use multiple options the simplest way is using [this](http://jsonformatter.curiousconcept.com/)
-website. It is also possible to use Python or Scala for validating but this requires some more knowledge.