Run Browser : Browse : Sequence Read Archive : NCBI/NLM/NIH

Run	Spots	Bases	Size	GC content	Published	Access Type
SRR787291	15.7M	3.2Gbp	2.2G	48.4%	2013-12-18	public

Quality graph (bigger)(smaller)

241

Phred quality score

This run has 2 reads per spot:

L=101, 100%

Legend

		Technical read
		Application Read
L=4, 100%		Length is 4, 100% spots contain this read
̅L=165, σ=92.8, 66%		Average length is 165, standard deviation is 92.8, 66% spots contain this read

Experiment	Library Name	Platform	Strategy	Source	Selection	Layout	Action
SRX252526	Physco_light	Illumina	RNA-Seq	TRANSCRIPTOMIC	cDNA	PAIRED

Show designHide design

MID-mRNA sequencing was carried out as suggested by Illumina, Inc. The method was adopted from mRNA-seq library prep protocol with addition of MID barcodes to the ds cDNA fragments and volume adjustment. Using the mRNA-seq kit, poly-A RNA were purified from 10-15 ?g of total RNA by oligo-dT beads and subjected to cation-catalyzed fragmentation for four minutes at 94°C. The mRNA fragments were then converted into ds cDNA by random priming, and the ends were repaired and A-tailed. Multiplexing barcodes were then added to the DNA fragment ends with modifications from the paired-end gDNA library prep kit (Illumina, USA). The ligation products were size-selected on agarose gel (200-400 bp), subjected to 18 cycles of PCR and cleaned up by Ampure beads (Beckman Agencourt, USA). The libraries were quantified fluorometrically by Qubit (Invitrogen, USA) and BioAnalyzer High Sensitivity DNA chip (Agilent, USA). Mixing of the differentially barcoded samples for each lane was based on qPCR-derived relative concentration for amplifiable fraction of each library.

Biosample	Sample Description	Organism
SAMN01942529 (SRS402930)	Spores were germinated on solid Knop's medium supplemented with 10 mM CaCl2 and overlaid with cellophane for 14-16 days. Plants were cultured at 25 °C under continuous white light (80–100 μmol m−2 s−1).	Physcomitrella patens

Bioproject	SRA Study	Title
PRJNA192876	SRP019809	Physcomitrella patens Transcriptome or Gene expression

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We used heat shock (HS) treatments and high-throughput mRNA sequencing to obtain HS transcriptomes in the moss Physcomitrella patens. Besides revealing differential gene expression at the transcriptional level, a transcriptome survey identified abundant AS events in the single-cell–type, undifferentiated, moss protonemal cell.

SRA archive data

SRA archive data is normalized by the SRA load process and used by the SRA Toolkit to read and produce formats like FASTQ, SAM, etc. The default toolkit configuration enables it to find and retrieve SRA runs by accession.

Public SRA files are now available from GCP and AWS cloud platforms as well as from NCBI. Access to most data in the cloud requires a user account with the cloud service provider. The user’s account will incur costs for cloud compute or to copy data outside of the specified cloud service region.

Type	Size	Location	Name	Free Egress	Access Type
SRA Normalized	2,102,744 Kb	AWS	https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR787291/SRR787291	worldwide	anonymous
SRA Lite	809,030 Kb	NCBI	https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos5/sra-pub-zq-11/SRR000/787/SRR787291/SRR787291.sralite.1	worldwide	anonymous
		AWS	s3://sra-pub-zq-8/SRR787291/SRR787291.sralite.1	s3.us-east-1	aws identity
		GCP	gs://sra-pub-zq-107/SRR787291/SRR787291.zq.1	gs.us-east1	gcp identity

Egress and Access: what does it mean?

Egressterm used by cloud providers to describe cost (charged to the user) of moving data outside of the storage region

Free Egress column indicates where the data can be accessed without an egress charge:

worldwide can be downloaded from anywhere for free
s3.us-east-1 is free to access from machines running in Amazon's us-east-1 region, access from other regions or transport outside of AWS will require paying egress charges
gs.US is free to access from machines running in Google’s gs.US region, access from other regions or transport outside of GCP will require paying egress charges

Access Typedescribes whether a cloud service user account is necessary for data access. "anonymous" access means general public access

Namecolumn provides either a link to free download location at NCBI or a URL for the cloud provider storage location. Either s3:// for Amazon or gs:// for Google storage

Why is SRA data in the cloud?

In order to support large scale (hyper parallel) data analyses SRA data is now available at GCP and AWS with few caveats:

SRA data is copied to the cloud from NCBI. There may be a lag between availability from NCBI and from CSP (cloud service providers)
To access public data user account with the cloud service provider is required. Your account will incur costs for cloud compute and/or to copy data (either archival or results of your comute) outside of the specified cloud service region
Distribution of protected data is signed by NIH account and requires user to operate in the same region as the data

SRA has also begun to provide access to originally submitted source files:

not all files have been validated by SRA
not all files have been copied to cloud locations (recovering it from NCBI tape system takes time ).
the volume of this type of data a much larger and it is not used as often so we will keep most of it on tape or "cold" storage in cloud. As a result the data may not be available instantly and restore requests will be served on first-come first-served basis and cost of resore may be charged to your user account.

What is "Cloud Data Delivery"?: Please visit SRA Data Delivery service to request Sequence Read Archive (SRA) data to be delivered to an Amazon Web Services (AWS) or Google Cloud Platform (GCP) bucket of your choice.

Taxonomy Analysis

Unidentified reads: 11.92%
Identified reads: 88.08%

View in Krona

Strong signals

SuperKingdom	Organism	Rank	%%	Kbp	Coverage
Eukaryota	Physcomitrella patens	species	87.9	2,789,149
Bacteria	Mesorhizobium	genus	0.1	3,825
Bacteria	Methylobacteriaceae	family	0.0	411
	unknown		0.0	11	10908.0

How to read results?: Results show distribution of reads mapping to specific taxonomy nodes as a percentage of total reads within the analyzed run. In cases where a read maps to more than one related taxonomy node, the read is reported as originating from the lowest shared taxonomic node. So when a read maps to two species belonging to the same genus, it is assigned at the genus level. Sequence reads from a single organism will map to several taxonomy nodes spanning the organism’s lineage. The number of reads mapping to higher level nodes will typically be greater than those that map to terminal nodes.

STAT results are proportional to the size of sequenced genomes. Given a mixed sample containing several organisms at equal copy number, proportionally more reads originate from the larger genomes. This means that the percentages reported by STAT will reflect genome size and must be considered against the genomic complexity of the sequenced sample.

How can I query this analysis data?: Please take a look at NCBI SRA Cloud-based Taxonomy Analysis Table

How taxonomy analysis is done?: A fast, scalable, MinHash-based k-mer tool to assess Sequence Read Archive next generation sequence submissions

mRNA-sequenciing for detection of light-regulated alternative splicing(SRR787291)

SRA archive data

Taxonomy Analysis

Strong signals

Intensity graph

	View: biological readstechnical readsquality scoresadvanced options Hide Reads base space color space show separated reads quality score with bases show clipped show 4 channel quality scorewith bases Intensity graph Signals table
	Intensity graph