| Run | Spots | Bases | Size | GC content | Published | Access Type |
|---|---|---|---|---|---|---|
SRR11085591 |
10.2M | 1.3Gbp | 578.5M | 41.7% | 2020-03-19 | public |
This run has 1 read per spot:
| L=125, 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 |
|---|---|---|---|---|---|---|---|
| SRX7724667 | lab_R5.S30.T1_rep3_lane3 | Illumina | RNA-Seq | TRANSCRIPTOMIC | RANDOM | SINGLE |
Design:
| Biosample | Sample Description | Organism | Links |
|---|---|---|---|
| SAMN14101945 (SRS6146463) | Manduca sexta 5th instar larvae from the UNC lab colony sampled at 30 degrees at time point 1 after exposure to fluctuations of 30 plus and minus 5 degrees during development. RNAseq data is provided from three biological replicates (each biological replicate contained RNA from three pooled individuals), each run on three sequencing lanes. | Manduca sexta | PRJNA605267 |
| Bioproject | SRA Study | Title |
|---|---|---|
| PRJNA605267 | SRP249473 | Interactive Effects of Previous and Current Thermal Conditions on Gene Expression in Manduca sexta |
This study performed RNA sequencing of fat body tissue from two populations of the tobacco hornworm caterpillar (Manduca sexta): a UNC-maintain laboratory colony and field population collected from eastern NC. The objective of this investigation was to evaluate the effects of diurnal temperature fluctuations (of 30 plus and minus 0, 5, or 10 degrees C) throughout development on larval gene expression both independently and in conjunction with subsequent thermal exposure (of 30, 35, or 40 degrees C). Results from differential expression analyses of these data highlight large differences in overall gene expression patterns between these two populations (across all temperature treatments) as well as population-specific transcriptomic responses to temperature. Exposure to fluctuating temperatures during rearing did alter gene expression during later heat stress in some cases, but this effect depended upon both the population and the specific temperature conditions. This research contributes to increased knowledge of molecular mechanisms underlying physiological responses of organisms to temperature, particularly with respect to thermal plasticity and adaptation in populations with different evolutionary histories.
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 | 564,942 Kb | AWS | https://sra-pub-run-odp.s3.amazonaws.com/sra/SRR11085591/SRR11085591 | worldwide | anonymous |
| SRA Lite | 334,464 Kb | NCBI | https://sra-downloadb.be-md.ncbi.nlm.nih.gov/sos3/sra-pub-zq-22/SRR011/085/SRR11085591.sralite.1 | worldwide | anonymous |
| AWS | s3://sra-pub-zq-7/SRR11085591/SRR11085591.sralite.1 | s3.us-east-1 | aws identity | ||
| GCP | gs://sra-pub-zq-103/SRR11085591/SRR11085591.zq.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 | 834,851 Kb | AWS | s3://sra-pub-src-5/SRR11085591/R2_L3_S47_L007_R1_001.fastq.gz.1 | - | 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: 19.98%
- Identified reads: 80.02%
Strong signals
| SuperKingdom | Organism | Rank | %% | Kbp | Coverage |
|---|---|---|---|---|---|
| Eukaryota | Manduca sexta | species | 79.8 | 1,016,487 | |
| Bacteria | Gammaproteobacteria | class | 0.2 | 2,885 | |
| Viruses | Helicoverpa armigera iflavirus | species | 0.0 | 12 |
- 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