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| Status |
Public on May 23, 2022 |
| Title |
Selex-Scr-16mer-R1 |
| Sample type |
SRA |
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| Source name |
synthetic DNA
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| Organism |
synthetic construct |
| Characteristics |
genotype: N/A
chip antibody: N/A
genome build: N/A
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| Growth protocol |
Drosophila larvae were grown on standard cornmeal or molasses food at 25°C.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
R0 DNA was from the Klenow product of the original synthetic random library, and R1 DNA was purified bound DNA fraction from the gel-free Selex experiments.
Selex-seq libraries were prepared by PCR amplification, followed by column purification
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| Library strategy |
OTHER |
| Library source |
genomic |
| Library selection |
other |
| Instrument model |
NextSeq 550 |
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| Data processing |
Library strategy: Selex-seq
For ChIP-seq and ATAC-seq, mapping was done against dm3 with the “Map with Bowtie for Illumina” tool on usegalaxy.org, and only uniquely mapped reads were kept.
ChIP-seq peak calling was performed using the galaxy version of MACS2 (“MACS2 callpeak” on usegalaxy.org), with the following setting: --nomodel –extsize 200, and all other parameters were default
ATAC-seq peak calling was also performed with the galaxy version of MACS2, with the following setting: --nomodel –extsize 200 - -shift -100.
For RNA-seq, the cutadaptor tool on usegalaxy.eu was used to trim reads and remove reads shorter than 100bp. The filtered reads were then mapped to the genome build dm6 using the RNA STAR tool with the following parameters: --sjdbOverhang 149. The featurecount tool was used to obtain the transcript count tables.
Selex-seq data were processed using the NRLB algorithm
When analysing the Selex-seq raw data, the algorithm we used took the R0 and R1 data, and output the motifs enriched in the R1 data. This is somewhat similar to de novo motif search. The algorithm didn't output any intermediate quantitative data, and the motif logos were the only data it generated.
Genome_build: dm3 for ChIP-seq and ATAC-seq, dm6 for RNA-seq
Supplementary_files_format_and_content: bigwig (ChIP-seq and ATAC-seq) and count table (RNA-seq)
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| Submission date |
Sep 20, 2021 |
| Last update date |
May 23, 2022 |
| Contact name |
Siqian Feng |
| E-mail(s) |
sf2607@columbia.edu
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| Organization name |
Columbia University
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| Street address |
625 W. 130th Street
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| City |
New York |
| State/province |
New York |
| ZIP/Postal code |
10027 |
| Country |
USA |
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| Platform ID |
GPL27609 |
| Series (1) |
| GSE184454 |
Transcription factor paralogs orchestrate alternative gene regulatory networks by context-dependent cooperation with multiple cofactors |
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| Relations |
| BioSample |
SAMN21523678 |
| SRA |
SRX12261361 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM5589258_model-Scr.pdf |
11.5 Kb |
(ftp)(http) |
PDF |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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