QIAseq miRNA Library Kits
Quality Control SummarysThis first summary table is a combination of the most important data points from the Quality control report. All the data can be seen in the context of related QC data below.
- Sample name: In all tables the fist column is the sample name as the data relates to each sample per row.
- Reads: The number of input reads in the sample data.
- Low numbers in any samples could indicate failed library prep.
- UMI Reads: Unique Molecular Indexes are used to join reads with the same amplification origin into UMI reads. This allows for better quantification of the miRNAs by eliminating any library amplification and sequencing bias.
- Avg Q Score, UMI Reads: The average quality score of the UMI reads.
- Numbers less than 30 indicate poor-quality library prep or instrument runs.
- UMI reads annotated: The number of UMI reads annotated with any of the databases involved in the analysis.
- Low percentage numbers could indicate sample prep issues or contamination.
- UMI reads annotated with miRbase: The number of UMI reads annotated with record from the miRBase database.
Creation of UMI reads
Detailed QC from the process of creating the UMI reads as single consensus reads, from reads that have the same Unique Molecular Index.
- Input reads: The number of input reads in the sample data. This is the same as the "Reads" column in the Summary.
- Low numbers in any samples could indicate failed library prep.
- Avg Q Score, input reads: The average quality score of the input data.
- Discarded reads: Reads where the common sequence (from the unique molecular index) is not found, or where the lengths of the small RNA or UMI do not fulfill the predefined criteria, are discarded.
- UMI groups: The resulting number of consensus reads (UMI reads). The UMI process identifies similar reads via the index and joins them in a group of reads.
- Merged UMI groups: Although indexed as different reads, some UMI reads may originate from the same biological read or fragment and have the same genetic code. In the UMI process, the reads with the same index are grouped as a UMI group. Indentical groups are then merged into a Merged UMI group. This final consensus is now the 'UMI read' used downstream in the analysis. This column is similar to 'UMI Reads' in the summary table, and the 'UMI reads' and 'UMI' terms are used interchangeably throughout tables in the remaining report.
- Avg Q score: UMI reads: The quality score of the resulting UMI reads.
- Numbers less than 30 indicate poor-quality library prep or instrument runs.
- Avg reads per UMI: How many reads are in each merged UMI group on average.
- Should be greater than one.
- UMIs with less than 9 reads: This and the next column highlights the extreme end of the UMI grouping distribution and should be seen as indications of potential problems in sequencing or library prep. For most applications, the ideal merged UMI group size will be around 2-4 reads. Larger UMI groups tend to have diminishing returns for the increased sequencing budget.
- A high percentage is preferable. If the percentage is lower than 90 a reevaluation of the sample prep may be needed.
- Max reads per UMI: This indicates the extreme end of the UMI grouping to highlight distribution and potential problems in sequencing.
Annotation Records Found
- miRBase (species of interest): 'Records in source' indicates the total number of Precursor miRNAs (pre-miRNAs) in the database used for annotating the features. Note that miRBase records are pre-miRNAs, whereas sample findings indicate the numbers of corresponding mature miRNAs. For each sample the number and percentage indicates how many of the database records were seen in the sample. See reference appendix for more information on miRbase version.
- piRNA (piRNAdb_species): 'Records in source' indicates the total number of records available in piRNAdb for the given species. For each sample the number and percentage indicates how many of the database records were seen in the sample. See reference appendix for more information on piRNA version.
Unique search sequences
For annotating the reads with database information, the analysis collapses the reads into unique search sequences. Collapsing identical reads into unique search sequences significantly reduces the number of miRNA reads in the subsequent annotation step and thereby saves computational time. The annotations are subsequently transferred to the UMI reads used in the expression analysis.
- Annotated (of total): Unique search sequences annotated with either database records.
- Annotated with miRBase (species) (of total): Unique search sequences annotated with the relevant miRbase database records.
- Annotated with piRNA (piRNAdb_species) (of total): Unique search sequences annotated with the piRNA database records.
- Additional databases can be listed here depeding on how the workflow has been set up.
- Unannotated (of total): Unique search sequences that did not match either database.
- Total (of total): The number of unique search sequences in the sample.
Reads
Distribution of UMI reads annotated with the selected databases, Annotations are transferred from the unique search sequences and onto the individual reads..
- Annotated (of total): Reads annotated with either database records.
- Annotated with miRBase (species) (of total): Reads annotated with the relevant miRbase database records.
- Annotated with piRNA (piRNAdb_species) (of total): Reads annotated with the piRNA database records.
- Additional databases can be listed here depeding on how the workflow has been set up.
- Unannotated (of total): Reads that did not match either database.
- Total (of total): The number of reads in the sample.
Spike-ins quality control
This section appears when the sample analysis started in the Align and Count dialog has checked the Spike-ins option.
- Spike-ins detected: The number of spike-ins detected relative to the spike-ins used.
- UMI reads mapped to spike-ins: The number of UMI reads that mapped to the detected spike-ins.
- % of total UMI reads: Percentage of UMI reads that mapped to spike-ins.