Nasap report

Basic info

Basic info--1.Basic sample information

Measure	Value
Read1 name	{{ Read1_name }}
Read2 name	{{ Read2_name }}
Read1 num	{{ Read1_num }}
Read2 num	{{ Read2_num }}
Read1 size	{{ Read1_size }}
Read2 size	{{ Read2_size }}
Clean read1	{{ clean_read1 }}
Clean read2	{{ clean_read2 }}
Original sam	{{ original_sam }}
Unmapped sam	{{ unmapped_sam }}
Uniquemapped sam	{{ uniquemapped_sam }}
Forward bw	{{ forward_bw }}
Reverse bw	{{ reverse_bw }}

Assessment

Assessment--1.adapter ratio

Measure	Value	Recommend
Reads with adapter	{{ Reads_with_adapter }}	-
Uninformative adapter reads	{{ Uninformative_adapter_reads }}	-
Percent of uninformative adapter reads	{{ Pct_uninformative_adapter_reads }}%	<5%
Peak adapter insertion size	{{ Peak_adapter_insertion_size }}	-
Adapter loss rate	{{ Adapter_loss_rate }}%	<5%

Assessment--2.RNA intergrity

Measure	Value	Recommend
Degradation ratio	{{ Degradation_ratio }}%	<1

RNA insert sizes distribution plot

Insert sizes below 20 nucleotides in the read length distribution indicates bad quality samples with degraded or poor RNA quality reads. The plot assessed the RNA intergrity with RNA insert sizes distribution.

Reads length distribution plot

The plot provides a detailed description of the nascent RNA reads length distribution in each preprocess steps.

Preprocess summary stack plot

The plot summarises the nascent RNA reads length distribution in each preprocess steps.

Assessment--3.Library complexity

Measure	Value	Recommend
NRF	{{ NRF }}	0.5 < NRF < 0.8
PBC1	{{ PBC1 }}	0.5 < PBC1 < 0.8
PBC2	{{ PBC2 }}	1 < PBC2 < 3

Non-Redundant Fraction (NRF) – Number of distinct uniquely mapping reads (i.e. after removing duplicates) / Total number of reads.

PCR Bottlenecking Coefficient 1 (PBC1) - number of genomic locations where exactly one read maps uniquely / number of distinct genomic locations to which some read maps uniquely

PCR Bottlenecking Coefficient 2 (PBC2) - number of genomic locations where only one read maps uniquely / number of genomic locations where two reads map uniquely

Assessment--4.QC trend

Sequencing quality score plot

Sequencing quality is evaluated with the percentage of bases with the quality score greater than 20 (Q20) and greater than 30 (Q30). The plot compares the nascent RNA reads quality scores in each preprocess steps.

Assessment--5.Nascent RNA purity

Measure	Value	Recommend
reads assign known genes	{{ assign_mapped }}	-
reads mapped to chrM	{{ chrM_mapped }}	-
mRNA contamination	{{ mRNA_contamination }}	1 < value < 1.8

File	Directory
Exon intro ratio	{{ exon_intron_ratio_csv }}

exon to intron read density ratio plot

The plot evaluate mRNA contamination with the exon to intron read density ratio.

Assessment--6.Other preprocess metric

Measure	Value
Trimmed reads	{{ Trimmed_reads }}
Trim loss rate	{{ Trim_loss_rate }}%
Reads with polyX	{{ Reads_with_polyX }}
Uninformative polyX reads	{{ Uninformative_polyX_reads }}

Mapping ratio plot

The plot evaluate mapping ratio generated by bowtie2 and bwa.

For bigwig files, we only provide exon/intron ratio as assessment. For more QC information, please use our python package nasap (https://pypi.org/project/nasap/). Thanks so much.

File	Directory
Exon intro ratio	{{ exon_intron_ratio_csv }}

exon to intron read density ratio plot

The plot evaluate mRNA contamination with the exon to intron read density ratio.

Quantitative analysis

Quantitative analysis--1.Expression output files

File	Directory
all feature attrs	{{ all_feature_attrs_csv }}
lincRNA count	{{ lincRNA_baseCount_csv }}
lincRNA gene body count	{{ lincRNA_gb_count_csv }}
lincRNA proximal promoter count	{{ lincRNA_pp_count_csv }}
lincRNA rpkm	{{ lincRNA_rpkm_csv }}
lincRNA rpm	{{ lincRNA_rpm_csv }}
protein coding count	{{ protein_coding_baseCount_csv }}
protein coding gb count	{{ protein_coding_gb_count_csv }}
protein coding pp count	{{ protein_coding_pp_count_csv }}
protein coding rpkm	{{ protein_coding_rpkm_csv }}
protein coding rpm	{{ protein_coding_rpm_csv }}
enhancer RNA log density	{{ erna_quant_csv }}

Quantitative analysis--2. Abundance estimate

expressed genes pie plot

The plot stats lincRNA and protein-coding RNA expressed genes.

expressed RNA distribution plot

The relative abundance of different RNA molecules are evaluted in the plot

Quantitative analysis--3.Gene expression on different chromosomes

chromosomal distribution plot

The expressed gene are distributed across chromosomes can be visualized with chromosomal distribution plot.

Pausing analysis

Pausing analysis--1.pausing index and escaping index

File	Directory
lincRNA ei	{{ lincRNA_ei_csv }}	-
lincRNA pi	{{ lincRNA_pi_csv }}	-
protein coding ei	{{ protein_coding_ei_csv }}	-
protein coding pi	{{ protein_coding_pi_csv }}	-

Pausing analysis--2.proximal pausing sites

File	Directory
proximal pausing sites	{{ proximal_pausing_site_bed }}	-

proximal pausing distribution plot

The proximal pausing sites are counted and visualized with proximal pausing distribution plot.

Pausing analysis--3.global pausing sites

File	Directory
global pausing sites	{{ pausing_sites_bed }}

global pausing distribution plot

The pausing sites are distributed in whole genome.

Gene regulatory network

Gene regulatory network--1 Network measurement

Measure	Value
nodes num	{{ nodes_num }}
edges num	{{ edges_num }}
mean degree	{{ mean_degree }}
assortativity coefficient	{{ assortativity_coefficient }}
correlation coefficient	{{ correlation_coefficient }}
transitivity	{{ transitivity }}
density	{{ density }}

Gene regulatory network--2 Degree distribution

Degree distribution plot

The statistical distribution of node degrees in a network.

Gene regulatory network--3 Motif distribution

Motif distribution plot

The plot count the numbers of occurrences of the triadic motif profiles in networks.

Gene regulatory network--4 Community analysis

All identifying communities can be found at txt directory

{{ community_name }} interactive html