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

Run	Spots	Bases	Size	GC content	Published	Access Type
SRR3928347	110.8k	54.8Mbp	132.4M	61.4%	2017-09-16	public

Quality graph (bigger)(smaller)

040

Phred quality score

This run has 2 reads per spot:

L=4, 100%

̅L=491, σ=120.3, 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
SRX1958038		LS454	EST	TRANSCRIPTOMIC	other	SINGLE

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Total RNA was extracted from whole brain tissue for each individual of the four phenotypes. Samples were transferred to 1 ml of QIAzol lysis reagent (Qiagen) and the tissue homogenized (on ice) with a sonicator (Sonopuls HD 2070; Bandelin, Berlin, Germany) during 30 s at 20-30% power. RNA was then extracted using the RNeasy Lipid Tissue Mini Kit (Qiagen) following manufacturer’s protocol. RNA quality and concentration for each sample were determined using a NanoDrop 1000 spectrophotometer (Thermo Scientific). Equal amounts of RNA from each individual were used to prepare the RNA pools corresponding to the high and low GSI libraries for each phenotype. For expression analysis, preparation and sequencing of the eight pooled RNA libraries was performed by The Genome Analysis Centre (Norwich, United Kingdom). Upon arrival, samples’ RNA integrity was first verified on Agilent 2100 Bioanalyzer. Libraries were prepared from polyA+ RNA and sequenced in two lanes on the Illumina HiSeq 2000 as paired-end 100 bp reads with an approximate insert size of 341 bp. Each library was sequenced at a high depth in order to detect transcripts that can become under-represented when analysing whole brain tissue expression. To improve the de novo assembly, four additional pooled libraries, one for each phenotype, were also prepared using RNA from the previous collection, and sequenced using Roche’s 454 technology. Library preparation and single-end sequencing on a GS-FLX System were performed at Max Planck Institute (Berlin, Germany) using the manufacturer's protocol.

Biosample	Sample Description	Organism
SAMN05390605 (SRS1568498)		Salaria pavo

Bioproject	SRA Study	Title
PRJNA329073	SRP078494	Salaria pavo brain transcriptome assembly and gene expression

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De novo transcriptome assembly and gene expression analysis for whole brain tissue of females and male morphotypes (nest-holder, transitional and sneaker) of the peacock blenny Salaria pavo. Samples were collected during reproductive season.

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	129,292 Kb	AWS	https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR3928347/SRR3928347	worldwide	anonymous
SRA Lite	106,236 Kb	NCBI	https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos5/sra-pub-zq-11/SRR003/928/SRR3928347/SRR3928347.lite.1	worldwide	anonymous
		AWS	s3://sra-pub-zq-2/SRR3928347/SRR3928347.lite.1	s3.us-east-1	aws identity
		GCP	gs://sra-pub-zq-109/SRR3928347/SRR3928347.lite.1	gs.us-east1	gcp identity

Original format

The original files submitted to SRA. These files may require specific software to open, read and interpret data.

Type	Size	Location	Name	Free Egress	Access Type
sff	339,779 Kb	AWS	s3://sra-pub-src-4/SRR3928347/0043_Pavo_SBrain_01.sff	-	Use Cloud Data Delivery

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: 24.14%
Identified reads: 75.86%

View in Krona

Strong signals

SuperKingdom	Organism	Rank	%%	Kbp	Coverage
	cellular organisms		NaN	NaN	NaN

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

Salaria pavo transcriptome assembly and gene expression(SRR3928347)

SRA archive data

Original format

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