Library preparation and sequencing data analysis report
Project name (ID): AMP0003
Overview
Library preparation summary
Library name
Number of samples
SP_L030626DEMO1_01
96
SP_L030626DEMO2_01
96
SP_L030626DEMO3_01
96
SP_L030626DEMO4_01
96
SP_L030626DEMO5_01
96
SP_L030626DEMO6_01
96
Library sequencing summary
PASSWARNING
Library? FASTQ name of the BRB-seq library
PF_reads? The total number of reads
Avg. nb. reads/sample? Defined as the number of demultiplexed reads / used samples
q30 R1? Rate of bases in Read 1 (BC+UMI) with Q >= 30
q30 R2? Rate of bases in Read 2 (genomic) with Q >= 30
SP_L030626DEMO1_01
1029256656
10,660,020
0.955355
0.955888
SP_L030626DEMO2_01
1095945034
11,362,059
0.956001
0.949295
SP_L030626DEMO3_01
1025395935
10,622,907
0.9535
0.955272
SP_L030626DEMO4_01
949256467
9,831,339
0.953651
0.950745
SP_L030626DEMO5_01
924905534
9,585,703
0.955617
0.950615
SP_L030626DEMO6_01
963212588
9,968,497
0.951027
0.944454
Library alignment summary
PASSWARNING
Library? FASTQ name of the BRB-seq library
Genome assembly? Reference genome used for alignment
Nb. Mapped? Total number of reads mapped against the genome
% Mapped? % of the reads mapped against the genome
Nb. Mapped to exons? Total number of quantified reads
% Exons? Total % of quantified counts
Nb. genes? Average number of detected genes across used samples
Nb. transcripts? Average number of detected transcripts across used samples
Nb. ERCC? Total number of reads mapped to ERCC spike-ins
% ERCC? Total % of reads mapped to ERCC spike-ins
SP_L030626DEMO1_01
homo_sapiens GRCh38 104
831,645,426
81.27
642,531,007
62.79
16338.56
47471.60
19,742,772
2.02
SP_L030626DEMO2_01
homo_sapiens GRCh38 104
853,133,861
78.21
682,855,162
62.6
15751.80
43698.11
27,106,992
2.59
SP_L030626DEMO3_01
homo_sapiens GRCh38 104
821,871,190
80.59
654,186,740
64.15
16148.97
46104.16
21,930,427
2.26
SP_L030626DEMO4_01
homo_sapiens GRCh38 104
747,944,092
79.25
600,291,125
63.6
15403.17
41897.66
29,783,075
3.39
SP_L030626DEMO5_01
homo_sapiens GRCh38 104
717,561,730
77.98
586,254,035
63.71
15851.47
43958.96
28,123,803
3.21
SP_L030626DEMO6_01
homo_sapiens GRCh38 104
757,321,978
79.14
612,143,568
63.97
13934.41
33663.70
28,286,062
3.09
SP_L030626DEMO1_01
Number of sequencing reads, per sample - SP_L030626DEMO1_01? Per sample identification statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of RNA spike-ins reads, per sample - SP_L030626DEMO1_01? Per-sample ERCC (RNA spike-in) statistics are displayed in both bar plot and plate view. The sample order in the bar plot can be adjusted to default, row-wise, or column-wise.
Hover for detailed sample information.
Spike-ins concentration ? This plot shows the theoretical ERCC concentrations from the Thermo Fisher Scientific Mix 1 spike-in list, alongside the observed ERCC expression levels, enabling a comparison between expected and actual RNA spike-in performance.
Spike-ins identification ? This plot compares the number of reads per sample with the percentage of identified ERCC, showing both theoretical and observed traces. The theoretical ERCC percentage is calculated by averaging ERCC counts across samples and dividing this constant by each sample’s sequencing depth, then multiplying by 100%.
Sample identification compared to spike-ins ? The plot shows the comparison of variability between total reads per sample and identified spike-ins, where lower ERCC variability suggests minimal technical noise.
Spike-ins clisters ? The PCA plot clusters samples based on normalized ERCC expression values. Samples that cluster closely together exhibit similar ERCC expression, suggesting consistent technical performance across those samples.
Alignment statistics, per sample - SP_L030626DEMO1_01? Per sample total alignment statistics perfomed by STARsolo, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected genes, per sample - SP_L030626DEMO1_01? Per sample gene detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected transcripts, per sample - SP_L030626DEMO1_01? Per sample transcript detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Compare sample-wise statistics - SP_L030626DEMO1_01? This scatter plot enables comparison of various individual statistics, such as the number of reads, genes, alignment percentage, and ERCC counts per sample. Both the x and y axes can be customized using drop-down menus to explore relationships between these metrics.
Hover for detailed sample information.
Principle Component Analysis - SP_L030626DEMO1_01? The PCA plot displays the general expression profiles of all samples, with dots sized according to read counts. It helps identify patterns and clusters in gene expression, showing how samples with similar or differing profiles group together based on their overall expression patterns.
This plot was generated using truncated PCA (irlba).
Hover for detailed sample information.
Top-10 most expressed genes across samples - SP_L030626DEMO1_01? The pie chart shows the top 10 most highly expressed genes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Top-10 most expressed biotypes across samples - SP_L030626DEMO1_01? The pie chart shows the top 10 most highly expressed gene biotypes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
SP_L030626DEMO2_01
Number of sequencing reads, per sample - SP_L030626DEMO2_01? Per sample identification statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of RNA spike-ins reads, per sample - SP_L030626DEMO2_01? Per-sample ERCC (RNA spike-in) statistics are displayed in both bar plot and plate view. The sample order in the bar plot can be adjusted to default, row-wise, or column-wise.
Hover for detailed sample information.
Spike-ins concentration ? This plot shows the theoretical ERCC concentrations from the Thermo Fisher Scientific Mix 1 spike-in list, alongside the observed ERCC expression levels, enabling a comparison between expected and actual RNA spike-in performance.
Spike-ins identification ? This plot compares the number of reads per sample with the percentage of identified ERCC, showing both theoretical and observed traces. The theoretical ERCC percentage is calculated by averaging ERCC counts across samples and dividing this constant by each sample’s sequencing depth, then multiplying by 100%.
Sample identification compared to spike-ins ? The plot shows the comparison of variability between total reads per sample and identified spike-ins, where lower ERCC variability suggests minimal technical noise.
Spike-ins clisters ? The PCA plot clusters samples based on normalized ERCC expression values. Samples that cluster closely together exhibit similar ERCC expression, suggesting consistent technical performance across those samples.
Alignment statistics, per sample - SP_L030626DEMO2_01? Per sample total alignment statistics perfomed by STARsolo, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected genes, per sample - SP_L030626DEMO2_01? Per sample gene detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected transcripts, per sample - SP_L030626DEMO2_01? Per sample transcript detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Compare sample-wise statistics - SP_L030626DEMO2_01? This scatter plot enables comparison of various individual statistics, such as the number of reads, genes, alignment percentage, and ERCC counts per sample. Both the x and y axes can be customized using drop-down menus to explore relationships between these metrics.
Hover for detailed sample information.
Principle Component Analysis - SP_L030626DEMO2_01? The PCA plot displays the general expression profiles of all samples, with dots sized according to read counts. It helps identify patterns and clusters in gene expression, showing how samples with similar or differing profiles group together based on their overall expression patterns.
This plot was generated using truncated PCA (irlba).
Hover for detailed sample information.
Top-10 most expressed genes across samples - SP_L030626DEMO2_01? The pie chart shows the top 10 most highly expressed genes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Top-10 most expressed biotypes across samples - SP_L030626DEMO2_01? The pie chart shows the top 10 most highly expressed gene biotypes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
SP_L030626DEMO3_01
Number of sequencing reads, per sample - SP_L030626DEMO3_01? Per sample identification statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of RNA spike-ins reads, per sample - SP_L030626DEMO3_01? Per-sample ERCC (RNA spike-in) statistics are displayed in both bar plot and plate view. The sample order in the bar plot can be adjusted to default, row-wise, or column-wise.
Hover for detailed sample information.
Spike-ins concentration ? This plot shows the theoretical ERCC concentrations from the Thermo Fisher Scientific Mix 1 spike-in list, alongside the observed ERCC expression levels, enabling a comparison between expected and actual RNA spike-in performance.
Spike-ins identification ? This plot compares the number of reads per sample with the percentage of identified ERCC, showing both theoretical and observed traces. The theoretical ERCC percentage is calculated by averaging ERCC counts across samples and dividing this constant by each sample’s sequencing depth, then multiplying by 100%.
Sample identification compared to spike-ins ? The plot shows the comparison of variability between total reads per sample and identified spike-ins, where lower ERCC variability suggests minimal technical noise.
Spike-ins clisters ? The PCA plot clusters samples based on normalized ERCC expression values. Samples that cluster closely together exhibit similar ERCC expression, suggesting consistent technical performance across those samples.
Alignment statistics, per sample - SP_L030626DEMO3_01? Per sample total alignment statistics perfomed by STARsolo, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected genes, per sample - SP_L030626DEMO3_01? Per sample gene detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected transcripts, per sample - SP_L030626DEMO3_01? Per sample transcript detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Compare sample-wise statistics - SP_L030626DEMO3_01? This scatter plot enables comparison of various individual statistics, such as the number of reads, genes, alignment percentage, and ERCC counts per sample. Both the x and y axes can be customized using drop-down menus to explore relationships between these metrics.
Hover for detailed sample information.
Principle Component Analysis - SP_L030626DEMO3_01? The PCA plot displays the general expression profiles of all samples, with dots sized according to read counts. It helps identify patterns and clusters in gene expression, showing how samples with similar or differing profiles group together based on their overall expression patterns.
This plot was generated using truncated PCA (irlba).
Hover for detailed sample information.
Top-10 most expressed genes across samples - SP_L030626DEMO3_01? The pie chart shows the top 10 most highly expressed genes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Top-10 most expressed biotypes across samples - SP_L030626DEMO3_01? The pie chart shows the top 10 most highly expressed gene biotypes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
SP_L030626DEMO4_01
Number of sequencing reads, per sample - SP_L030626DEMO4_01? Per sample identification statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of RNA spike-ins reads, per sample - SP_L030626DEMO4_01? Per-sample ERCC (RNA spike-in) statistics are displayed in both bar plot and plate view. The sample order in the bar plot can be adjusted to default, row-wise, or column-wise.
Hover for detailed sample information.
Spike-ins concentration ? This plot shows the theoretical ERCC concentrations from the Thermo Fisher Scientific Mix 1 spike-in list, alongside the observed ERCC expression levels, enabling a comparison between expected and actual RNA spike-in performance.
Spike-ins identification ? This plot compares the number of reads per sample with the percentage of identified ERCC, showing both theoretical and observed traces. The theoretical ERCC percentage is calculated by averaging ERCC counts across samples and dividing this constant by each sample’s sequencing depth, then multiplying by 100%.
Sample identification compared to spike-ins ? The plot shows the comparison of variability between total reads per sample and identified spike-ins, where lower ERCC variability suggests minimal technical noise.
Spike-ins clisters ? The PCA plot clusters samples based on normalized ERCC expression values. Samples that cluster closely together exhibit similar ERCC expression, suggesting consistent technical performance across those samples.
Alignment statistics, per sample - SP_L030626DEMO4_01? Per sample total alignment statistics perfomed by STARsolo, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected genes, per sample - SP_L030626DEMO4_01? Per sample gene detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected transcripts, per sample - SP_L030626DEMO4_01? Per sample transcript detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Compare sample-wise statistics - SP_L030626DEMO4_01? This scatter plot enables comparison of various individual statistics, such as the number of reads, genes, alignment percentage, and ERCC counts per sample. Both the x and y axes can be customized using drop-down menus to explore relationships between these metrics.
Hover for detailed sample information.
Principle Component Analysis - SP_L030626DEMO4_01? The PCA plot displays the general expression profiles of all samples, with dots sized according to read counts. It helps identify patterns and clusters in gene expression, showing how samples with similar or differing profiles group together based on their overall expression patterns.
This plot was generated using truncated PCA (irlba).
Hover for detailed sample information.
Top-10 most expressed genes across samples - SP_L030626DEMO4_01? The pie chart shows the top 10 most highly expressed genes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Top-10 most expressed biotypes across samples - SP_L030626DEMO4_01? The pie chart shows the top 10 most highly expressed gene biotypes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
SP_L030626DEMO5_01
Number of sequencing reads, per sample - SP_L030626DEMO5_01? Per sample identification statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of RNA spike-ins reads, per sample - SP_L030626DEMO5_01? Per-sample ERCC (RNA spike-in) statistics are displayed in both bar plot and plate view. The sample order in the bar plot can be adjusted to default, row-wise, or column-wise.
Hover for detailed sample information.
Spike-ins concentration ? This plot shows the theoretical ERCC concentrations from the Thermo Fisher Scientific Mix 1 spike-in list, alongside the observed ERCC expression levels, enabling a comparison between expected and actual RNA spike-in performance.
Spike-ins identification ? This plot compares the number of reads per sample with the percentage of identified ERCC, showing both theoretical and observed traces. The theoretical ERCC percentage is calculated by averaging ERCC counts across samples and dividing this constant by each sample’s sequencing depth, then multiplying by 100%.
Sample identification compared to spike-ins ? The plot shows the comparison of variability between total reads per sample and identified spike-ins, where lower ERCC variability suggests minimal technical noise.
Spike-ins clisters ? The PCA plot clusters samples based on normalized ERCC expression values. Samples that cluster closely together exhibit similar ERCC expression, suggesting consistent technical performance across those samples.
Alignment statistics, per sample - SP_L030626DEMO5_01? Per sample total alignment statistics perfomed by STARsolo, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected genes, per sample - SP_L030626DEMO5_01? Per sample gene detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected transcripts, per sample - SP_L030626DEMO5_01? Per sample transcript detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Compare sample-wise statistics - SP_L030626DEMO5_01? This scatter plot enables comparison of various individual statistics, such as the number of reads, genes, alignment percentage, and ERCC counts per sample. Both the x and y axes can be customized using drop-down menus to explore relationships between these metrics.
Hover for detailed sample information.
Principle Component Analysis - SP_L030626DEMO5_01? The PCA plot displays the general expression profiles of all samples, with dots sized according to read counts. It helps identify patterns and clusters in gene expression, showing how samples with similar or differing profiles group together based on their overall expression patterns.
This plot was generated using truncated PCA (irlba).
Hover for detailed sample information.
Top-10 most expressed genes across samples - SP_L030626DEMO5_01? The pie chart shows the top 10 most highly expressed genes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Top-10 most expressed biotypes across samples - SP_L030626DEMO5_01? The pie chart shows the top 10 most highly expressed gene biotypes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
SP_L030626DEMO6_01
Number of sequencing reads, per sample - SP_L030626DEMO6_01? Per sample identification statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of RNA spike-ins reads, per sample - SP_L030626DEMO6_01? Per-sample ERCC (RNA spike-in) statistics are displayed in both bar plot and plate view. The sample order in the bar plot can be adjusted to default, row-wise, or column-wise.
Hover for detailed sample information.
Spike-ins concentration ? This plot shows the theoretical ERCC concentrations from the Thermo Fisher Scientific Mix 1 spike-in list, alongside the observed ERCC expression levels, enabling a comparison between expected and actual RNA spike-in performance.
Spike-ins identification ? This plot compares the number of reads per sample with the percentage of identified ERCC, showing both theoretical and observed traces. The theoretical ERCC percentage is calculated by averaging ERCC counts across samples and dividing this constant by each sample’s sequencing depth, then multiplying by 100%.
Sample identification compared to spike-ins ? The plot shows the comparison of variability between total reads per sample and identified spike-ins, where lower ERCC variability suggests minimal technical noise.
Spike-ins clisters ? The PCA plot clusters samples based on normalized ERCC expression values. Samples that cluster closely together exhibit similar ERCC expression, suggesting consistent technical performance across those samples.
Alignment statistics, per sample - SP_L030626DEMO6_01? Per sample total alignment statistics perfomed by STARsolo, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected genes, per sample - SP_L030626DEMO6_01? Per sample gene detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Number of detected transcripts, per sample - SP_L030626DEMO6_01? Per sample transcript detection statistics, presented in barplot and plate view. The order of samples in barplot can be changed to default, row-wise and column-wise.
Hover for detailed sample information.
Compare sample-wise statistics - SP_L030626DEMO6_01? This scatter plot enables comparison of various individual statistics, such as the number of reads, genes, alignment percentage, and ERCC counts per sample. Both the x and y axes can be customized using drop-down menus to explore relationships between these metrics.
Hover for detailed sample information.
Principle Component Analysis - SP_L030626DEMO6_01? The PCA plot displays the general expression profiles of all samples, with dots sized according to read counts. It helps identify patterns and clusters in gene expression, showing how samples with similar or differing profiles group together based on their overall expression patterns.
This plot was generated using truncated PCA (irlba).
Hover for detailed sample information.
Top-10 most expressed genes across samples - SP_L030626DEMO6_01? The pie chart shows the top 10 most highly expressed genes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Top-10 most expressed biotypes across samples - SP_L030626DEMO6_01? The pie chart shows the top 10 most highly expressed gene biotypes, with each slice representing their percentage of total gene expression.
Hover for detailed sample information.
Gene Body Coverage
Advanced QC: Full Length BRBseq Gene Body Coverage
