@font-face { font-family:'Barlow', sans-serif; src:url("'Barlow', sans-serif\\static\\'Barlow', sans-serif-Bold.ttf"); }
 
Sample information : $samplename



Estimated number of cells
The total number of barcodes identified as cells.
Median UMI counts per cell
Among barcodes identified as cells, the median number of UMI per cell.
Median genes per cell
The median number of genes per cell.
Mean reads per cell
The mean number of reads per cell.
$estm_Num_cell

Estimated number of cell

$median_UMI_per_c

Median UMI counts per cell

$median_genes_per_c

Median genes per cell

$mean_r_per_c

Mean reads per cell

Beads to cells


(left) Beads to cells plot
In library, different mRNAs from the same cell will carry the same cell barcode and random unique molecular identifiers (UMIs). However, some mRNA from dead cells mixed in reflection system was inevitability. This graph shows the distribution of UMI counts in each barcode. Barcodes can be determined to be cell-associated based on their UMI counts or by their expression profiles. Therefore, the graph contains both cell-associated (Colored Regions) and background-associated barcodes (Gray Regions).
(right) Histogram
Histograms of number of beads per droplet.
$plot1
$plot4
Summary


Estimated number of cells
The total number of barcodes identified as cells.
Mean reads per cell
The mean number of reads detected per cell.
Mean UMI counts per cell
The average number of UMI counts per cell. This item refers the average abundance of expression in each cell.
Median UMI counts per cell
The median number of UMI counts per cell.
Total genes detected
The total number of genes detected.
Mean genes per cell
The mean number of genes detected per cell. This item refers the activity of gene expression in each cell.
Median genes per cell
The median number of genes detected per cell.
Sequencing saturation
The fraction of UMI originating from an already-observed UMI.
Fraction reads in cells
The fraction of uniquely-mapped-to-transcriptome reads with cell-associated barcode.
Plot
The distribution of nFeature and nCount in violin.
Sample name
$samplename
Species
$species
Estimated number of cells
$estm_Num_cell
Mean reads per cell
$mean_r_per_c
Mean UMI count per cell
$mean_UMI_per_c
Median UMI counts per cell
$median_UMI_per_c
Total genes detected
$total_gene
Mean genes per cell
$mean_genes_per_c
Median genes per cell
$median_genes_per_c
Fraction reads in cells
$Fraction
Sequencing saturation
$saturation
$plot5
Sequencing


Number of reads
Number of raw off-machine reads obtained by this sequencing program.
Reads pass QC
Number of reads after quality control (QC) that can be used for downstream analysis. QC includes filtering low quality reads and invalid barcodes.
Reads with exactly matched barcodes
Number of reads with barcodes that match the barcode whitelist before correction.
Reads with failed barcodes
Number of reads with invalid barcodes that fail to match the barcode whitelist.
Reads filtered on low quality
Number of reads in low quality. The QC will filter the average base quality < Q20 or 2 bases < Q10 in the first 15 bases.
Q30 bases in cell barcode
Fraction of cell barcode bases with Q-score ≥ 30.
Q30 bases in UMI
Fraction of UMI bases with Q-score ≥ 30.
Q30 bases in reads
Fraction of RNA read bases with Q-score ≥ 30.
mRNA
Number of reads
$cDNA_num_frag
Reads pass QC
$cDNA_frag_pass_QC
Reads with exactly matched barcodes
$cDNA_frag_exact_bar
Reads with failed barcodes
$cDNA_frag_fail_bar
Reads filtered on low quality
$cDNA_frag_low_qual
Q30 bases in cell barcode
$cDNA_Q30_c_bar
Q30 bases in UMI
$cDNA_Q30_UMI
Q30 bases in reads
$cDNA_Q30_r
Droplet index
Number of reads
$index_num_frag
Reads pass QC
$index_frag_pass_QC
Reads with exactly matched barcodes
$index_frag_exact_bar
Reads with failed barcodes
$index_frag_fail_bar
Reads filtered on low quality
$index_frag_low_qual
Q30 bases in cell barcode
$index_Q30_c_bar
Q30 bases in reads
$index_Q30_r
Mapping & Annotation


Reads pass QC
Number of reads after quality control (QC) that can be used for downstream analysis. QC includes filtering low quality reads and invalid barcodes.
Reads mapped to genome
Fraction of reads that mapped to the genome.
Plus strand
The number of reads in plus strand.
Minus strand
The number of reads in minus strand.
Mitochondria ratio
The fraction of reads mapped to mitochondria.
Mapping quality corrected reads
The number of reads that align to a single exonic locus but also align to 1 or more non-exonic loci.
Reads mapped to exonic regionse
Fraction of reads that mapped to an exonic region of genome.
Reads mapped to intronic regions
Fraction of reads that mapped to an intronic region of genome.
Reads mapped antisense to gene
Fraction of reads mapped to transcriptome, but on the opposite strand of their annotated gene. This part of reads will be filtered out cause them are opposite to theoretical direction.
Reads mapped to intergenic regions
Fraction of reads that mapped to intergenic regions of genome.
Reads pass QC
$raw_r
Reads mapped to genome
$r_m_geno
Plus strand
$plus_strd
Minus strand
$minus_strd
Mitochondria ratio
$mito_ratio
Mapping quality corrected reads
$map_qual_corrt_r
Reads mapped to exonic regions
$r_m_ex
Reads mapped to intronic regions
$r_m_intro
Reads mapped antisense to gene
$r_m_anti
Reads mapped to intergenic regions
$r_m_inter
Include introns
$intron_boolean
Cluster


Left
This plot shows that the total UMI counts for each cell-barcode. Two-dimensional horizontal and vertical coordinates of each dot are obtained using the uniform manifold approximation and projection (UMAP) algorithm. Each dot represents a cell and is colored according to UMI counts. Cells with greater UMI counts likely have higher RNA content than cells with fewer ones.
Right
The figure is automated clustering each cell-barcode by UMAP algorithm. The cells clustered into the same group have similar expression profiles. Each dot represents a cell, and is colored according to different cluster.
$plot2
$plot3
Marker


Table
The table shows the top 30 differentially expressed genes for each cluster. Here a differential expression test was performed between each cluster and the rest of the sample for each gene. The p-value is a measure of the statistical significance of the expression difference, the smaller the P value, the closer to the theoretical value. Avg_log2FC is log fold-chage of the average expression between the markers for every cluster compared to all remaining cells.
$table
Saturation


Left
The plot shows the Sequencing Saturation metric as a function of downsampled sequencing depth in mean reads per cell, up to the observed sequencing depth. Sequencing Saturation is a measure of the observed library complexity, and approaches 1.0 (100%) when all converted mRNA transcripts have been sequenced. The slope of the curve near the endpoint can be interpreted as an upper bound to the benefit to be gained from increasing the sequencing depth beyond this point.
Right
The plot shows the Median Genes per Cell as a function of downsampled sequencing depth in mean reads per cell, up to the observed sequencing depth. The slope of the curve near the endpoint can be interpreted as an upper bound to the benefit to be gained from increasing the sequencing depth beyond this point.
$plot6
$plot7