TABLE 1.
Self-reported knowledge across skill domains of genomic sequencing (n = 21 respondents).
| Knowledge domain | Pre-workshop scorea |
Post-workshop scorea |
Post-workshop gains |
|
| Median (IQR) | Median (IQR) | Median (IQR) | p-valueb | |
| NGS technology | 4 (3,5) | 7 (6,8) | 3 (2,3) | <0.001 |
| Illumina MiSeq sequencing chemistry | 4 (2,5) | 7 (6,8) | 3 (2,4) | <0.001 |
| NGS library preparation | 5 (2,6) | 8 (7,9) | 3 (2,4) | <0.001 |
| NGS library validation | 2 (1,5) | 8 (6,8) | 4 (3,4) | <0.001 |
| MiSeq run validation | 2 (1,3) | 6 (4,8) | 3 (2,4) | <0.001 |
| Experimental design for bioinformatics analysis | 2 (1,4) | 6 (5,8) | 3 (2,4) | <0.001 |
| FASTQ data cleaning and pre-processing | 2 (1,5) | 6 (5,8) | 4 (2,4) | <0.001 |
| Reference mapping | 3 (1,5) | 7 (6,9) | 4 (1,5) | <0.001 |
| Linux OS use and command line | 2 (1,5) | 5 (3,7) | 1 (0,3) | <0.001 |
| Consensus sequence calling and manual curation | 2 (1,3) | 6 (5,8) | 4 (2,5) | <0.001 |
NGS, next generation sequencing; OS, operating system. aMaximum possible score is 10. bDerived from Wilcoxon signed rank test.