| Run | Spots | Bases | Size | GC content | Published | Access Type |
|---|---|---|---|---|---|---|
SRR388222 |
29.6M | 4.3Gbp | 2.5G | 47.6% | 2013-01-01 | public |
This run has 2 reads per spot:
| L=72, 100% | L=72, 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 |
|---|---|---|---|---|---|---|---|
| SRX110652 | East Coast | Illumina | RNA-Seq | TRANSCRIPTOMIC | RANDOM | PAIRED |
| Biosample | Sample Description | Organism |
|---|---|---|
| SAMN00764094 (SRS281907) | Two individuals from Chennai: 13° 04' N & 80° 17' E; two from Tuticorin: 8° 48' N & 78° 11' E; and three from Vishakhapatnam: 17° 44' N & 83° 23' E. Shrimp were dissected under sterile conditions and fresh tissue samples (hepatopancreas, muscle, nervous tissue, intestinal tract, heart, gonad, gill, pleopod and lymphoid organ) were collected and stored in 1.5 ml microtubes. Microtubes were filled with RNAlater (Qiagen) to immerse the entire tissue. Subsequently, tubes were topped up to the brim with RNAlater, capped and stored at room temperature for two hours, 4 oC overnight and -80 oC until further use. RNA was extracted (TRIzol® Plus RNA Purification, Invitrogen) according to manufacturer’s instructions. Tissue was ground in liquid nitrogen and 1.5 ml of TRIzol was added. RNA was further purified by chloroform extraction followed by precipitation using isopropanol and one wash with 70% ethanol. RNA was resuspended in 25 µl of RNase-free water. Only samples with optimal purity (OD260/280 >1.8 and <2.2; OD260/230>1.0 and <2.4) and concentration (>50 ng/µl and <2500 ng/µl), estimated using UV spectrophotometry (Nanodrop) and capillary electrophoresis (Agilent Bioanalyser), were utilized for sequencing. Samples were prepared using the Illumina protocol outlined in “Preparing Samples for Sequencing of mRNA” (Part# 1004898 Rev. A September 2008). | Penaeus monodon |
| Bioproject | SRA Study | Title |
|---|---|---|
| PRJNA77663 | SRP009653 | Penaeus monodon Transcriptome or Gene expression |
A strategy using mRNA-seq was used to identify polymorphisms in transcribed genes that could be used to scan the Penaeus monodon genome for markers associated with resistance to white-spot syndrome virus Whispovirus sp. Shrimp were sampled from among four landing centres around the east Indian coastline (EC), survivors of a severe WSSV infection during pond culture (SUR) and the Andaman Islands (AI). Hepatopancreas, muscle, nervous tissue, intestinal tract, heart, gonad, gills, pleopod and lymphoid organs were dissected. Equal quantities of purified RNA from tissue homogenates were combined to create AI, EC and SUR RNA pools for sequencing using the mRNA-seq protocol on the Illumina Genome Analyzer II sequencing platform.
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 | 2,448,731 Kb | AWS | https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR388222/SRR388222 | worldwide | anonymous |
| SRA Lite | 1,092,211 Kb | NCBI | https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos5/sra-pub-zq-11/SRR000/388/SRR388222/SRR388222.sralite.1 | worldwide | anonymous |
| AWS | s3://sra-pub-zq-8/SRR388222/SRR388222.sralite.1 | s3.us-east-1 | aws identity | ||
| GCP | gs://sra-pub-zq-105/SRR388222/SRR388222.noqual.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 |
|---|---|---|---|---|---|
| fastq | 6,548,689 Kb | AWS | s3://sra-pub-src-9/SRR388222/s_7_1_sequence.txt | - | Use Cloud Data Delivery |
| fastq | 6,548,689 Kb | AWS | s3://sra-pub-src-14/SRR388222/s_7_2_sequence.txt | - | 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.
Taxonomy Analysis
- Unidentified reads: 92.29%
- Identified reads: 7.71%
Strong signals
| SuperKingdom | Organism | Rank | %% | Kbp | Coverage |
|---|---|---|---|---|---|
| Eukaryota | Penaeus monodon | species | 5.9 | 250,923 | |
| Eukaryota | Rhinopithecus roxellana | species | 1.0 | 44,641 | |
| Eukaryota | Endopterygota | infraclass | 0.3 | 11,298 | |
| Eukaryota | Glires | 0.1 | 6,345 | ||
| Eukaryota | Euteleosteomorpha | 0.1 | 5,486 | ||
| Eukaryota | Sauropsida | 0.1 | 3,485 | ||
| Bacteria | Methylobacterium extorquens | species | 0.1 | 3,027 | 0.5 |
| Eukaryota | Laurasiatheria | superorder | 0.1 | 2,948 | |
| Viruses | Penaeus monodon nudivirus | species | 0.0 | 783 |
- 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