Dataset Information

I-ATAC: interactive pipeline for the management and pre-processing of ATAC-seq samples.

ABSTRACT: Assay for Transposase Accessible Chromatin (ATAC-seq) is an open chromatin profiling assay that is adapted to interrogate chromatin accessibility from small cell numbers. ATAC-seq surmounted a major technical barrier and enabled epigenome profiling of clinical samples. With this advancement in technology, we are now accumulating ATAC-seq samples from clinical samples at an unprecedented rate. These epigenomic profiles hold the key to uncovering how transcriptional programs are established in diverse human cells and are disrupted by genetic or environmental factors. Thus, the barrier to deriving important clinical insights from clinical epigenomic samples is no longer one of data generation but of data analysis. Specifically, we are still missing easy-to-use software tools that will enable non-computational scientists to analyze their own ATAC-seq samples. To facilitate systematic pre-processing and management of ATAC-seq samples, we developed an interactive, cross-platform, user-friendly and customized desktop application: interactive-ATAC (I-ATAC). I-ATAC integrates command-line data processing tools (FASTQC, Trimmomatic, BWA, Picard, ATAC_BAM_shiftrt_gappedAlign.pl, Bedtools and Macs2) into an easy-to-use platform with user interface to automatically pre-process ATAC-seq samples with parallelized and customizable pipelines. Its performance has been tested using public ATAC-seq datasets in GM12878 and CD4+T cells and a feature-based comparison is performed with some available interactive LIMS (Galaxy, SMITH, SeqBench, Wasp, NG6, openBIS). I-ATAC is designed to empower non-computational scientists to process their own datasets and to break to exclusivity of data analyses to computational scientists. Additionally, I-ATAC is capable of processing WGS and ChIP-seq samples, and can be customized by the user for one-independent or multiple-sequential operations.

SUBMITTER: Ahmed Z

PROVIDER: S-EPMC5702251 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

I-ATAC: interactive pipeline for the management and pre-processing of ATAC-seq samples.

Ahmed Zeeshan Z Ucar Duygu D

PeerJ 20171122

Assay for Transposase Accessible Chromatin (ATAC-seq) is an open chromatin profiling assay that is adapted to interrogate chromatin accessibility from small cell numbers. ATAC-seq surmounted a major technical barrier and enabled epigenome profiling of clinical samples. With this advancement in technology, we are now accumulating ATAC-seq samples from clinical samples at an unprecedented rate. These epigenomic profiles hold the key to uncovering how transcriptional programs are established in div ...[more]

PMID: 29181276

Similar Datasets

Project description:BackgroundSingle-cell RNA sequencing (scRNA-seq) has quickly become one of the most dominant techniques in modern transcriptome assessment. In particular, 10X Genomics' Chromium system, with its high throughput approach, turn key and thorough user guide made this cutting-edge technique accessible to many laboratories using diverse animal models. However, standard pre-processing, including the alignment and cell filtering pipelines might not be ideal for every organism or tissue. Here we applied an alternative strategy, based on the pseudoaligner kallisto, on twenty-two publicly available single cell sequencing datasets from a wide range of tissues of eight organisms and compared the results with the standard 10X Genomics' Cell Ranger pipeline.ResultsIn most of the tested samples, kallisto produced higher sequencing read alignment rates and total gene detection rates in comparison to Cell Ranger. Although datasets processed with Cell Ranger had higher cell counts, outside of human and mouse datasets, these additional cells were routinely of low quality, containing low gene detection rates. Thorough downstream analysis of one kallisto processed dataset, obtained from the zebrafish pineal gland, revealed clearer clustering, allowing the identification of an additional photoreceptor cell type that previously went undetected. The finding of the new cluster suggests that the photoreceptive pineal gland is essentially a bi-chromatic tissue containing both green and red cone-like photoreceptors and implies that the alignment and pre-processing pipeline can affect the discovery of biologically-relevant cell types.ConclusionWhile Cell Ranger favors higher cell numbers, using kallisto results in datasets with higher median gene detection per cell. We could demonstrate that cell type identification was not hampered by the lower cell count, but in fact improved as a result of the high gene detection rate and the more stringent filtering. Depending on the acquired dataset, it can be beneficial to favor high quality cells and accept a lower cell count, leading to an improved classification of cell types.

Dataset Information

I-ATAC: interactive pipeline for the management and pre-processing of ATAC-seq samples.

Publications

I-ATAC: interactive pipeline for the management and pre-processing of ATAC-seq samples.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets