| Run | Spots | Bases | Size | GC content | Published | Access Type |
|---|---|---|---|---|---|---|
SRR3423349 |
40.7M | 7.3Gbp | 4.7G | 44.1% | 2017-02-14 | public |
This run has 2 reads per spot:
| L=90, 100% | L=90, 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 |
|---|---|---|---|---|---|---|---|
| SRX1722038 | Illumina | RNA-Seq | TRANSCRIPTOMIC | cDNA | PAIRED |
| Biosample | Sample Description | Organism | Links |
|---|---|---|---|
| SAMN04887240 (SRS1409457) | Hevea brasiliensis | PRJNA319415 |
| Bioproject | SRA Study | Title |
|---|---|---|
| PRJNA319415 | SRP073752 | Transcriptome of inner bark in Hevea brasiliensis |
We report transcriptome data of four kinds of bark samples from the Hevea brasiliensis clone CATAS7-33-97 by use of next-generation massively parallel sequencing technologies and de novo transcriptome assembly. The output of sequenced data showed that a total of 323,842,182 clean reads with average length of 90 nt were generated in four samples. Totally 67,873 uingenes with an average length of 750 nt and a N50 of 1,222 nt were assembled through transcriptome de novo assembly. The all assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. The comparative analysis of the transcriptome data performed with the criteria of FDR = 0.001 and |log2 Ratio| = 1. As a result, 15,780 different expression unigenes (8,646 up and 7,134 down ) were detected in early libraries (Control-A versus COR-A) upon coronatine treatment, and 19,824 different expression unigenes (7,711 up and 12,113 down) were detected in late libraries (Control-B versus COR-B) upon coronatine treatment. Functional analysis of different expression unigenes showed that mass of unigenes were annotated in multiple signaling pathways. Comparative transcriptome analysis of inner bark in response to coronatine reveals a new insight into the signal networks for the secondary laticifer differentiation from vascular cambia in rubber tree. Overall design: The transcriptome of bark in response to coronatine in Hevea brasiliensis
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 Lite | 1,796,607 Kb | NCBI | https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos5/sra-pub-zq-14/SRR003/423/SRR3423349.sralite.1 | worldwide | anonymous |
| AWS | s3://sra-pub-zq-1/SRR3423349/SRR3423349.sralite.1 | s3.us-east-1 | aws identity | ||
| GCP | gs://sra-pub-zq-104/SRR3423349/SRR3423349.zq.1 | gs.us-east1 | gcp identity | ||
| SRA Normalized | 4,542,751 Kb | AWS | https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR3423349/SRR3423349 | worldwide | anonymous |
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 |
|---|---|---|---|---|---|
| fastq | 2,970,079 Kb | AWS | s3://sra-pub-src-4/SRR3423349/COR-A_l1_2.fq.gz | - | Use Cloud Data Delivery |
| fastq | 2,923,957 Kb | AWS | s3://sra-pub-src-8/SRR3423349/COR-A_l1_1.fq.gz | - | Use Cloud Data Delivery |
- Egress and Access: what does it mean?
-
Egress
term used by cloud providers to describe cost (charged to the user) of moving data outside of the storage region Free Egresscolumn 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.