snv-indels module ================= The ``snv-indels`` module is responsible for aligning the reads to the reference, and calling variants. The bam and count files produced by this module are used in the fusion and gene expression modules. Tools ----- This module uses `STAR `_ to align the reads to the reference using two-pass mode. `VarDict `_ is used to call variants, which are annotated using ``VEP``. Variants are filtered based on the criteria defined in ``filter_criteria``, and annotated based on ``annotation_criteria``. The variants annotated by VEP are then filtered based on a number of different criteria: 1. Variants that are present on the ``blacklist`` are excluded. 2. Only variants that match at least one criteria in ``filter_criteria`` are included. 3. Variant that have a population frequency of more than 1% in the ``gnomADe`` population are excluded. Picard is used to generate various alignment statistics. Input ----- The input for this module is a single pair of FastQ files per sample, specified in a PEP configuration file, as is shown below. .. csv-table:: Example input for the snv-indels module :delim: , :file: ../../test/pep/targetted.csv Output ------ The output of this module are a JSON file with an overview of the most important results, as well as a number of other output files: * A .bam and .bai per sample, which contain the aligned reads. * The filtered VEP output file (``filter_vep``), which contains the final set of filtered and annotated variants. * The ``counts`` file produced by STAR, which contains the coverage per gene. Configuration ------------- You can automatically generate a configuration for the fusion module using the ``utilities/create-config.py`` script. Example ^^^^^^^ .. literalinclude:: ../../test/data/config/snv-indels.json :language: json Note that the ``vep-cache`` entry is missing for this example file, which means that VEP will be run with only the ``fasta`` and ``gtf`` files as input. For the best performance, please specify a ``vep-cache`` folder as well. Configuration options ^^^^^^^^^^^^^^^^^^^^^ .. list-table:: Configuration options :widths: 30 80 15 :header-rows: 1 * - Option - Description - Required * - genome_fasta - Reference genome, in FASTA format - yes * - genome_fai - .fai index file for the reference fasta - yes * - genome_dict - .dict index file for the reference fasta - yes * - star_index - STAR index database - yes * - ref_id_mapping - File of transcripts of interest - yes * - filter_criteria - Criteria file to filter variants - yes * - annotation_criteria - Criteria file to annotate variants - yes * - rrna_refflat - File of rRNA transcripts - yes * - gtf - GTF file with transcripts, used by STAR - yes * - annotation_refflat - File used to determine exon coverage - yes * - blacklist - File of blacklisted variants - no * - vep-cache - Folder containing the VEP cache - no * - variant_allele_frequency - Minimum variant allele frequency in the sample to call a variant (default=0.05) - no Filter and annotation criteria ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ HAMLET include the ability to specify separate filter criteria for every transcript, based on the position and the VEP consequence of the variant. The criteria are used both the filter which variants will be part of the output (``filter_criteria``), and also annotate the identified variants (``annotation_criteria``). The required columns are ``transcript_id``, ``consequence``, ``start`` and ``end``. For annotation variants, the ``annotation`` column is used. Every column except for ``transcript_id`` can be empty. .. csv-table:: Example ``filter_criteria`` file, from the HAMLET tests :delim: U+0009 :file: ../../test/data/config/filter_criteria.tsv .. csv-table:: Example ``annotation_criteria`` file, from the HAMLET tests :delim: U+0009 :file: ../../test/data/config/annotation_criteria.tsv