Admin Release Notes for gLeaves-package 3.7.x

Annotations and tools:

Datafile updates: replace the datafiles folder in the gLeaves worker configuration with the new version provided.

Exomedepth can now be used; this requires event annotation via annotSV, as is already the case for ClinSV or WisecondorX.

In the coming weeks, this new version will also allow gnomAD to be annotated during import rather than within the VCFs, in order to optimise storage and annotation times. We are currently finalising the public dataset conversion programme so that we can share it with you, allowing you to choose the version you prefer.

Metrics and worker operation:

You must add the following information:

• To the configuration of the import ( (settings_import.toml) and compute_rec (settings_compute-rec.toml) workers :

In the [email] section:

min_level = "error" # "off" | "debug" | "info" | "warn" | "error"

here, you can adjust the log level (via "off", "debug", "info", "warn", "error") at which you wish to receive an email regarding tasks processed by the various workers.

In a new section :

[metrics]
dest="monserveurgraphite:numerodeport"
prefix="gleaves.env.worker"

ensure you replace env and worker with the appropriate values (for example, prod and import, or preprod and compute-rec…)
and, in dest point towards a Graphite server.

• To the index worker configuration (settings_index.toml):

in the [email] section:

min_level = "error" # "off" | "debug" | "info" | "warn" | "error"

here, you can adjust the log level (via "off", "debug", "info", "warn", "error") at which you wish to receive an email regarding tasks processed by the various workers.

The [metrics] section, which should already exist, can be adapted if necessary in a similar way to those of the other workers.

New pipeline information supported by gLeaves :

New information can be reported by your pipelines to gLeaves via the import JSON (these are optional; if you do not use them, do not add them):

• Inferred sex via the following keys :

"clinsv": {
    "sample_id0": {
      "inferred_gender": "XY"
    },
    "sample_id1": {
      "inferred_gender": "XX"
    },
    "sample_id2": {
      "inferred_gender": "XY"
    }
  },

As with the BAMs, the objects contained within the clinsv object correspond in number and name to the samples in the SNV VCF.

• Callable loci in BED format via the following keys :

"callable_loci": {
    "sample_id0": {
      "data": "s3://path/vers/mon/echantillon/beds/callable_loci/sample_id0_callableloci_genome.bed"
    },
    "sample_id1": {
      "data": "s3://path/vers/mon/echantillon/beds/callable_loci/sample_id1_callableloci_genome.bed"
    },
    "sample_id2": {
      "data": "s3://path/vers/mon/echantillon/beds/callable_loci/sample_id2_callableloci_genome.bed"
    }
  },

As with the inferred sex above, the objects contained within the callable_loci object correspond in number and name to the samples in the SNV VCF.

• The following Quality Control (QC) values :

"qc_values_mr": {
    "sample_id0": {
      "%_bases_above_20": 95.33665606306415,
      "Mean_Coverage": 38.300855502541886,
      "PCT_Callable": 90.82306096253954,
      "Q30_bases": 121275161348
    },
    "sample_id1": {
      "%_bases_above_20": 94.01438829356556,
      "Mean_Coverage": 33.73580716474486,
      "PCT_Callable": 90.74747599385792,
      "Q30_bases": 107657509707
    },
    "sample_id2": {
      "%_bases_above_20": 94.54165589119985,
      "Mean_Coverage": 35.528030508552185,
      "PCT_Callable": 90.76747702674781,
      "Q30_bases": 113301643295
    }
  },

As with the inferred sex above, the objects contained within the qc_values_mr object correspond in number and name to the samples in the SNV VCF. They contain keys corresponding to the metrics typically reported by an analysis pipeline.