Overview
Sample info
| project_id | mLN |
| sample_id | mLN_S4 |
| puck_barcode_file_id | puck_collection |
| species | human |
| sequencing_date | unknown |
| investigator | unknown |
| experiment | unknown |
Run modes
This sample was processed using the following run modes, and run mode variables
|
Run modes
|
|
|---|---|
| openst | |
| clean_dge | FALSE |
| count_intronic_reads | TRUE |
| count_mm_reads | TRUE |
| detect_tissue | FALSE |
| mesh_data | TRUE |
| mesh_spot_diameter_um | 7 |
| mesh_spot_distance_um | 7 |
| mesh_type | hexagon |
| n_beads | 1e+05 |
| polyA_adapter_trimming | TRUE |
| spatial_barcode_min_matches | 0.1 |
| umi_cutoff | 100, 250, 500 |
Mapping statistics
The sample was mapped using polyA_adapter_trimmed reads. The mapping statistics are shown here for each method:
|
Mapping mode
|
|
|---|---|
| polyA_adapter_trimmed | |
| input_reads | 46.9 |
| uniq_mapped_reads | 35.91 (76.6%) |
| as.cds | 8.57 (18.3%) |
| as.utr | 13.72 (29.3%) |
| intronic | 2.53 (5.4%) |
| intergenic | 1.58 (3.4%) |
| ambiguous | 9.51 (20.3%) |
| avg_mapped_length | 105.21 |
| multi_mapped_reads | 7.02 (15%) |
| unmapped_too_short | 2.75 (5.9%) |
| mapped_to_rRNA | 3.08 (6.6%) |
| Note: | |
| All values, except avg_mapped_length, shown in millions |
Summarised metrics over beads
|
Run modes
|
|
|---|---|
| openst | |
| median_genes | 98 |
| median_pcr | 1.07423580786026 |
| median_reads | 126 |
| median_umis | 117 |
| n_beads | 156509 |
| sum_reads | 20.94 (1e6) |
QC plots
Each of the QC plots we show on a per run mode basis, to see if there are any downstream differences based on the run mode variable settings.
‘Knee’-plot
Below we plot a so called ‘Knee-plot’: on the y-axis is the Cummulative sum of reads, on the x-axis are the bead barcodes sorted by number of reads. For single-cell samples, this plot tells you roughly how many beads are in the sample.
#### openst
Umi-cutoff plots
Histogram of metrics over beads
Next we show mertics such as number of UMIs, genes, reads and pcr per physical spot. We further distinguish between each run mode, showing one histogram for each.
#### openst
Nucleotide distribution per beads
Next we bin the data based on reads into quartile. For each run_mode the data is divided into 4 beads, by reads. This means, that the first bin will contain beads which account 25% of the reads, the second will contain beads which account for the second 25% of reads and so on.
For each run mode we plot the nucleotide distribution per quartile.
You can pick the run_mode to be shown from the dropdown list
Only not-meshed run_mode(s) are shown
Shannon entropy and string compression
#### openst
Spatial QC
openst
