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DU145 oeSOAT1
Analysis type
De Novo Assembly
OEZ014550
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DU145 sphere
Analysis type
De Novo Assembly
OEZ014548
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22Rv1 sphere
Analysis type
De Novo Assembly
OEZ014549
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OEZ_wenyan_2312251121
Analysis type
Other
OEZ014547
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Processed_CUT&Tag-seq data
Description
To process raw data, reads containing adapter or ploy-N were removed to generate clean reads. Further filtration according to the calculated Q20, Q30 and GC content resulted in high-quality clean reads, which were then aligned to reference human genome GRCh38 using the BWA program (version 0.7.15). The MACS2 package(version 2.2.9.1)was used for peak-calling from the BAM files with q-value < 0.05. HOMER (version 4.11) was applied to the generated peak file and the genome fasta for motif analysis. Peaks were annotated using the annotatePeaks.pl function. For defining differentially accessible peaks, peak files of each sample were first merged using BEDTools (version 2.28.0). The counts of the reads over the bed were then determined for each sample using the multicov function from BEDTools. Finally, differentially accessible peaks were assessed using DESeq2 (version v1.42.0).
Analysis typeOther
OEZ014525
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Processed spatial transcriptomics data at bin50-level
Description
The raw reads were decoded by ST_BarcodeMap (version 0.0.1), filtered adapter sequence by Fastp, and then aligned to the reference genome GRCh38.p12(Human) via STAR. Mapped reads were annotated, then calculated by HandleBam(version 1.0.0). The raw matrix was converted into the bin50-level matrix (i.e., 25*25um) by the Seurat R package(version 4.2.0). For quality control, the median number of gene types per bin50 for all chips should be over 500.
Analysis typeOther
OEZ013918
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Processed single-cell spatial transcriptomics
Description
The raw reads were decoded by ST_BarcodeMap (version 0.0.1), filtered adapter sequence by Fastp, and then aligned to the reference genome GRCh38.p12(Human) via STAR. Mapped reads were annotated, then calculated by HandleBamz(version 1.0.0). Single-cell segmentation of Stereo-seq data is performed by a self-written algorithm.
Analysis typeOther
OEZ013917
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Processed_snATAC-seq
Description
Data were aligned to the human genome (hg38), and the fragment files were achieved using the default parameters of DNBelab C4 snATAC-seq (version v3.0, BGI). Doublet removal, iterative latent semantic indexing (LSI) dimensionality reduction, initial clustering, and snATAC-se-snRNA-seq data integration were performed using ArchR(v1.0).
Analysis typeOther
OEZ013916
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Processed shotgun proteomic profiles
Description
Missing quantitative values were imputed using the K-nearest neighbor (KNN) algorithm in the DreamAI R package (v0.1.0).
Analysis typeOther
OEZ013907
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Whole genome sequecing analysis of IRD families
Description
A total of 271 unresolved IRD patients and their available family members (n=646) were screened using WGS technology to identify pathogenic SVs and intronic variants in 792 known ocular disease genes. The pathogenicity of all identified variants was evaluated through a combination of factors including allele frequencies (AFs) in the general population, functional annotation, and inheritance pattern analysis.
Analysis typeDe Novo Assembly
OEZ014524