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| Status |
Public on Sep 12, 2024 |
| Title |
Female_Young_3_Section3_1_interaction |
| Sample type |
SRA |
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| Source name |
Mouse Brain
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| Organism |
Mus musculus |
| Characteristics |
tissue: Mouse Brain
genotype: C57BL/6
treatment: Female_Aged
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| Extracted molecule |
other |
| Extraction protocol |
10 um thick mouse brains were cryosectioned, and RNA was hybridized to a barcoded hydrogel bead based array
Barcoded beads have a PCR handle, and Template Switching Oligo was utilized to amplify bound nucleic acid molecules.
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| Library strategy |
OTHER |
| Library source |
other |
| Library selection |
other |
| Instrument model |
Illumina NovaSeq 6000 |
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| Data processing |
cDNA data processing:
Initial Data Preparation: After the sequencing process, the data is obtained in the form of two sets of FASTQ files: R1 and R2. R1 FASTQ files contain the barcode sequences for receiver bead along with their associated Unique Molecular Identifiers (UMIs). R2 FASTQ files contain the tagmented cDNA sequences.
Barcode Mapping and Tagging: The barcode sequences from R1 are mapped to a whitelist of bead barcodes with a tolerance of 1 base pair error. The identified bead barcode is then added as an identifier (ID) for the corresponding sequences in R2.
Read2 File Generation and PolyA Trimming: New Read2 files are generated where the name of each sequence in R2 contains the corresponding Read1 barcode. Additionally, any PolyA tails present at the end of the sequences are trimmed to ensure accurate mapping and analysis.
Read Mapping to Genome: The filtered and trimmed reads are then mapped to the reference genome using a tool such as STAR(25) (Spliced Transcripts Alignment to a Reference). This step involves aligning the sequences from R2 to the genomic sequences to identify their locations and potential splice sites.
Duplicate Removal: After mapping, duplicate reads are identified and removed to eliminate redundant data and ensure accuracy in downstream analysis. This process generates new SAM (Sequence Alignment/Map) files containing the mapped reads with duplicates removed.
Gene Count Matrices Generation: From the processed SAM files, gene count matrices are generated for each associated receiver bead. This involves counting the number of reads aligned to each gene for every receiver bead, providing quantitative information about gene expression levels.
Beads Connections processing
Initial Data Preparation: Following the sequencing process, data from two beads, namely receiver bead and sending beads, are obtained. Each bead connection includes unique molecular identifiers (UMIs) which help in identifying and quantifying individual connection molecules. Additionally, there are two types of reads: R1, which contains the barcode for receiver beads, and R2, which contains the barcodes for receiver beads. The reads are mapped to a whitelist of barcodes with 1 base pair error, including the UMI sequence. Duplicated reads are then filtered, and a csv file is generated with receiver bead, UMI, and sending bead barcode, where each line represents a unique molecular connection between receiver and sending beads.
Assembly: STAR_hg19_mm10_RNAseq
Supplementary files format and content: Please check below. Annotation column has content description as well.
Library strategy: Spatial Transcriptomics
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| Submission date |
Jun 20, 2024 |
| Last update date |
Sep 12, 2024 |
| Contact name |
Abdulraouf Abdulraouf |
| Organization name |
Rockefeller University
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| Street address |
1230 York Ave
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| City |
New York |
| State/province |
NY |
| ZIP/Postal code |
10065 |
| Country |
USA |
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| Platform ID |
GPL24247 |
| Series (1) |
| GSE270383 |
Spatial Mapping of Mouse Brain Aging through Indexed Sequencing |
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| Relations |
| BioSample |
SAMN41940311 |
| SRA |
SRX24992352 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM8341589_20231221_FY3_4_connection.spatial.csv.gz |
790.7 Mb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Raw data are available in SRA |
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