Project description:Chromatin immuno-precipitation using anti-Flag (Sigma) antibodies in a U2OS stable cell line. Paired-end R1 and R2 reads are provided, but the processed (mapped) reads are from a single-end (R1 read only) mapping.
Project description:Sequencing libraries were generated from total RNA samples following the mRNAseq protocol for the generation of single end (16-36 hpf, 5 day larvae, adult head and adult tail) or paired end (24 hpf) libraries (Illumina). Single end reads of 36 nucleotides and paired end reads (2 x 76 nucleotides) were obtained with a GAIIx (Illumina). Gene expression at the different stages/tissu was assessed by cufflinks and HTseq.
2013-07-27 | GSE39703 | GEO
Project description:RADSeq paired end reads of Pleoticus muelleri
Project description:ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of protein–DNA interactions in-vivo in the genome. In general, current algorithms for ChIP-seq reads employ artificial estimation of the average length of DNA fragments for peak finding, leading to uncertain prediction of DNA-protein binding sites. Here, we present SIPeS (Site Identification from Paired-end Sequencing), a novel algorithm for precise identification of binding sites from short reads generated from paired-end Solexa ChIP-Seq technology. SIPeS uses a dynamic baseline directly via ‘piling up’ the corresponding fragments defined by the paired reads to efficiently find peaks corresponding to binding sites. The performance of SIPeS is demonstrated by analyzing the ChIP-Seq data of the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS). The robustness of SIPeS was demonstrated in higher sensitivity and spatial resolution in peak finding compared to three existing peak detection algorithms. Keywords: transcription factors (protein-DNA interactions)
Project description:For ATAC-seq data processing, we used the ENCODE ATAC-seq pipeline (https://www.encodeproject.org/atac-seq/). In detail, for each sample, ATAC-seq reads were first checked for adaptor contamination. Then, adaptor trimmed reads were aligned to hg19 using Bowtie2 under paired-end mode with parameter “-X2000”, which permits 2000 bp for the maximum allowable insert size between two paired ends of each read. Using the ENCODE ATAC-seq pipeline, duplicated reads were properly filtered out. ATAC-seq enriched peaks were called using MACS2 (Zhang et al., 2008) based on remaining unique reads with parameters “-f BAMPE -q 0.05 --nomodel”. In total, we collected 45,569 peaks for the ARID1AWT sample and 27,480 peaks for the ARID1AKO sample.