Data Type & Analysis Selection๏ƒ

Important

This section should be included in SOPs where data is analysed or passes through a computational pipeline.

This section of an SOP should define the types of input the procedure is validated to process and explain how data characteristics determine the choice of analysis methods, tools, and parameters.

This section may include:

  • Data Format: Specify the format(s) of input data (e.g. FASTQ, BAM, VCF), sequencing technology (e.g. Illumina, Oxford Nanopore, PacBio), and any relevant characteristics (e.g. read length, paired-end vs single-end).

  • Sample suitability: Describe the types of samples or organisms the data is expected to represent (e.g. human clinical samples, bacterial isolates, viral genomes).

  • Analysis Selection: Describe how the data type influences the selection of analysis tools, algorithms, and parameters. For example, certain variant callers may be optimised for short reads versus long reads.

Example content:

๐Ÿงฌ Bioinformatics QC Procedure

Example content from a bioinformatics SOP outlining the procedure for assessing the quality of Illumina sequencing data prior to downstream bioinformatics analyses.

Data Type & Analysis Selection

This procedure is designed to process 150bp paired-end FASTQ files generated using Illumina sequencing platforms (e.g. MiSeq, NextSeq). Each sample should have two FASTQ files (.fastq or .fastq.gz) representing the forward and reverse reads.

The QC pipeline is specifically optimised and validated to process this data type and read length. Samples generated using other sequencing technologies (e.g. Oxford Nanopore, PacBio) or read lengths are not validated for analysis using this procedure.

The input data should be derived from microbial samples ; this procedure is not designed or validated for human sequencing datasets. Samples containing high levels of human derived reads will not pass QC thresholds. Analysis tools and pipeline parameters have been selected to align with the anticipated characteristics of microbial data.

๐Ÿ‘ฉโ€๐Ÿ”ฌ Staff Training Procedure

This section is not relevant for this example, as this procedure does not involve the analysis of specimen derived data.

๐ŸŒŒ Galaxy Training Procedure

This section is not relevant for this example, as this procedure does not involve the analysis of specimen derived data.

๐Ÿงช Laboratory Procedure

This section is not relevant for this example, as this procedure does not involve the analysis of specimen derived data.

๐Ÿ’ป Code Update & Review Procedure

This section is not relevant for a code update and review procedure, as it does not involve specific data types or analyses.

โœ… Validation Procedure