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| @@ -220,78 +220,6 @@ Rscript | |||
| 原始数据质量和数据比对质量结果汇总（example） | |||
| ### 2. One_sample.csv | |||
| | Name | Description | Group | Value | Reference_value | Conclusion | | |||
| | ------------------------ | ------------------------------------------------------------ | ----- | ---------- | --------------- | ---------- | | |||
| | Detected_gene | This metric is used to estimate the detection abundance of one sample. | D5 | 25126.6667 | (**, 58,395] | | | |||
| | | | D6 | 25858.6667 | (**, 58,395] | | | |||
| | | | F7 | 26089.6667 | (**, 58,395] | | | |||
| | | | M8 | 26618 | (**, 58,395] | | | |||
| | Jacard Index | Detection JI is the ratio of number of the genes detected in both replicates than the number of the genes detected in either of the replicates. This metric is used to estimate the repeatability of one sample detected gene from different replicates. | D5 | 0.8756 | [0.8, 1] | Pass | | |||
| | | | D6 | 0.8752 | [0.8, 1] | Pass | | |||
| | | | F7 | 0.8675 | [0.8, 1] | Pass | | |||
| | | | M8 | 0.8804 | [0.8, 1] | Pass | | |||
| | CV | CV is calculated based on the normalized expression levels in all 3 replicates of one sample for each genes. This metric is used to estimate the repeatability of one sample expression level from different replicates. | D5 | 11.4836 | | | | |||
| | | | D6 | 10.8401 | | | | |||
| | | | F7 | 12.2976 | | | | |||
| | | | M8 | 10.8662 | | | | |||
| | CTR | CTR is calculated based on the correlation of one sample expression level from different replicates. | D5 | 0.9718 | [0.95, 1] | Pass | | |||
| | | | D6 | 0.9737 | [0.95, 1] | Pass | | |||
| | | | F7 | 0.9699 | [0.95, 1] | Pass | | |||
| | | | M8 | 0.9725 | [0.95, 1] | Pass | | |||
| | Sensitivity_of_detection | Sensitivity is the proportion of true detected genes from reference dataset which can be correctly detected by the test set. | D5 | 0.9788 | [0.96, 1] | Pass | | |||
| | | | D6 | 0.9794 | [0.96, 1] | Pass | | |||
| | | | F7 | 0.9774 | [0.96, 1] | Pass | | |||
| | | | M8 | 0.9818 | [0.96, 1] | Pass | | |||
| | Specificity_of_detection | Specificity is the proportion of true non-detected genes from reference dataset which can be correctly not detected by the test set. | D5 | 0.9727 | [0.94, 1] | Pass | | |||
| | | | D6 | 0.9713 | [0.94, 1] | Pass | | |||
| | | | F7 | 0.9694 | [0.94, 1] | Pass | | |||
| | | | M8 | 0.9677 | [0.94, 1] | Pass | | |||
| 一个种类样本层面数据表达质量（example） | |||
| ### 3. Two_sample.csv | |||
| | Name | Description | Group | Value | Reference_value | Conclusion | | |||
| | ---------------------------------------- | ------------------------------------------------------------ | ----- | ---------- | --------------- | ---------- | | |||
| | Consistency_ratio_of_relative_expression | Proportion of genes that falls into reference range (mean +-2 fold SD) in relative ratio (log2FC). | D6/D5 | 1 | [0.82, 1] | Pass | | |||
| | | | F7/D5 | 1 | [0.82, 1] | Pass | | |||
| | | | F7/D6 | 1 | [0.82, 1] | Pass | | |||
| | | | M8/D5 | 1 | [0.82, 1] | Pass | | |||
| | | | M8/D6 | 1 | [0.82, 1] | Pass | | |||
| | | | M8/F7 | 1 | [0.82, 1] | Pass | | |||
| | Correlation_of_relative_log2FC | Pearson correlation between mean value of reference relative ratio and test site. | D6/D5 | 0.98137614 | [0.96,1] | Pass | | |||
| | | | F7/D5 | 0.9725557 | [0.96,1] | Pass | | |||
| | | | F7/D6 | 0.96789651 | [0.96,1] | Pass | | |||
| | | | M8/D5 | 0.97951286 | [0.96,1] | Pass | | |||
| | | | M8/D6 | 0.97959193 | [0.96,1] | Pass | | |||
| | | | M8/F7 | 0.97736629 | [0.96,1] | Pass | | |||
| | Sensitivity_of_DEGs | Sensitivity is the proportion of true DEGs from reference dataset which can be correctly identified as DEG by the test set. | D6/D5 | 0.8344293 | [0.80, 1] | Pass | | |||
| | | | F7/D5 | 0.84870451 | [0.80, 1] | Pass | | |||
| | | | F7/D6 | 0.84516486 | [0.80, 1] | Pass | | |||
| | | | M8/D5 | 0.86227581 | [0.80, 1] | Pass | | |||
| | | | M8/D6 | 0.86363942 | [0.80, 1] | Pass | | |||
| | | | M8/F7 | 0.85718483 | [0.80, 1] | Pass | | |||
| | Specificity_of_DEGs | Specificity is the proportion of true not DEGs from reference dataset which can be can be correctly identified as non-DEG by the test set. | D6/D5 | 0.97680659 | [0.95, 1] | Pass | | |||
| | | | F7/D5 | 0.97056775 | [0.95, 1] | Pass | | |||
| | | | F7/D6 | 0.975892 | [0.95, 1] | Pass | | |||
| | | | M8/D5 | 0.96896379 | [0.95, 1] | Pass | | |||
| | | | M8/D6 | 0.97206349 | [0.95, 1] | Pass | | |||
| | | | M8/F7 | 0.96594245 | [0.95, 1] | Pass | | |||
| 两个种类样本层面数据表达质量（example） | |||
| ### 4. More_sample.csv | |||
| | Name | Description | n | Value | Refenence_value | Conclusion | | |||
| | ---- | ------------------------------------------------------------ | ----- | ----- | --------------- | ---------- | | |||
| | SNR | Signal is defined as the average distance between libraries from the different samples on PCA plots and noise are those form the same samples. SNR is used to assess the ability to distinguish technical replicates from different biological samples. | 23705 | 13.64 | [5, inf) | Pass | | |||
| 多个种类样本层面数据表达质量（example） | |||
| ## 结果解读 | |||
| ### 1.原始数据质量和数据比对质量 | |||
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