Skip to content

Tutorial

fgardos edited this page Dec 31, 2013 · 87 revisions

This section explains how to use main tasks for BiERapp:

Creating an account

User interface functionality

Upload & manage

The input is a VCF file: individual VCF file for only one sample or multisample VCF file for several samples (families or group of cases /controls). More information about Variant Calling Format.

How does BiERapp work?:

  • After uploading VCF file, BiERapp detects variants for all samples.
  • Initial results show the whole set of variants. This is a general first view of detected variants. Next step for each user is defining his own strategy of filtering according to his interests.

Filtering options:

There are several filters to define the best strategy of variant selection. It is possible to choose one or several filtering options at the same time:

  • Region. Several possibilities to define a region:

    -Only one chromosomal region: 1:1-10000000
    -Several regions (separated by comma): 1:1-10000000, 2:1-10000000
    -Some chromosomes: 4,5,8

  • Gene. Only variants for a group of genes. Example: BRCA2,PPL (separated by comma)

  • Stats. This filter shows several ways of selecting by allele frequency, genotype frequency, number of mendelian errors, presence of indel, % cases or control for dominant/recessive inheritance. BiERapp also manages efficiently missing values.

  • Samples. This intuitive filter that allows reproducing any familiar pedigree with any inheritance model. Also case-control or sporadic de novo mutational diseases can be analysed in this framework. We only have to select the possible genotypes for each sample:

  • Control. This filter is based on known population frequencies

  • Effect.

    • Predicted pathologic effect:
    • Consequence types:

BiERapp outputs:

  • Summary: global statistics and a graphical representation for consequence type.
  • Variants and effects: detected variants and its effects for all samples.
  • Genome viewer: selected variants can be visualized from this genome browser

Clone this wiki locally