Dataset Information

SeQuiLa-cov: A fast and scalable library for depth of coverage calculations.

ABSTRACT:

Background

Depth of coverage calculation is an important and computationally intensive preprocessing step in a variety of next-generation sequencing pipelines, including the analysis of RNA-sequencing data, detection of copy number variants, or quality control procedures.

Results

Building upon big data technologies, we have developed SeQuiLa-cov, an extension to the recently released SeQuiLa platform, which provides efficient depth of coverage calculations, reaching >100× speedup over the state-of-the-art tools. The performance and scalability of our solution allow for exome and genome-wide calculations running locally or on a cluster while hiding the complexity of the distributed computing with Structured Query Language Application Programming Interface.

Conclusions

SeQuiLa-cov provides significant performance gain in depth of coverage calculations streamlining the widely used bioinformatic processing pipelines.

SUBMITTER: Wiewiorka M

PROVIDER: S-EPMC6680061 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

SeQuiLa-cov: A fast and scalable library for depth of coverage calculations.

Wiewiórka Marek M Szmurło Agnieszka A Kuśmirek Wiktor W Gambin Tomasz T

GigaScience 20190801 8

<h4>Background</h4>Depth of coverage calculation is an important and computationally intensive preprocessing step in a variety of next-generation sequencing pipelines, including the analysis of RNA-sequencing data, detection of copy number variants, or quality control procedures.<h4>Results</h4>Building upon big data technologies, we have developed SeQuiLa-cov, an extension to the recently released SeQuiLa platform, which provides efficient depth of coverage calculations, reaching >100× speedup ...[more]

PMID: 31378808

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Project description:Smart-seq3xpress was carefully optimized and >1,000 conditions were evaluated. This data submission is organized in 15 datasets that each contain fastq files, unmapped bam files, read count tables, UMI count tables and a barcode annotation file. The barcode_annotation.txt files contain the exact factors/variables tested. Below a short description of each set of experiments: K562_lowvolume: Evaluation of scaling volumes of Smart-seq3 (indicated volume refers to total volume in PCR), whether overlay was used and if cDNA was bead-cleaned or diluted prior to tagmentation. Cell input was K562 cells. The columns \\"treatment\\", \\"volume\\" and \\"VL\\" indicate the experimental parameters. HEK_lowvolume: Evaluation of scaling volumes of Smart-seq3 (indicated volume refers to total volume in PCR), whether overlay was used and if cDNA was bead-cleaned or diluted prior to tagmentation. Cell input was HEK293FT cells. The columns \\"treatment\\", \\"volume\\" and \\"VL\\" indicate the experimental parameters. overlays: Evaluation of the effect of various overlays when generating HEK293FT libraries in 1 uL total volume. The column \\"condition\\" indicates the applied overlay. tagmentations: Evaluation of input cDNA vs Tn5 amount during tagmentation. Purified cDNA from one 384-well plate was used as input into various conditions of tagmentations. The experiments contain evaluation of cDNA amount with fixed Tn5 amount or varying Tn5 amount while keeping the default volume (2 uL) of the tagmentation reaction or scaling the reaction volume. The column \\"condition\\" contains a string indicating reaction volume, cDNA input and Tn5 ATM enzyme amount. If no volume is indicated, reaction was performed in 2 uL. HomeTn5: Evaluation of tagmentation using in-house produced Tn5 enzyme (Picelli et al., 2015) when tagmenting cDNA generated from HEK293FT cells in 1 uL total volume. The column \\"Tn5concentration\\" indicates the Tn5 reaction concentration at 2 uL reaction volume. cycles_cleanups: Optimization of Smart-seq3xpress (column \\"experiment\\" shows \\"direct_tag\\") in regards to clean-ups after cDNA synthesis (column \\"condition\\": noclean, Exo+FastAP, ExoSAP) and dilution volume (9 or 19 uL); PCR cycle numbers (column \\"pcr_input\\") and ATM Tn5 enzyme amount (column \\"ATM\\"). Cell input was HEK293FT cells. PreAmp_Polymerase: Evaluation of various PCR polymerases during initial cDNA amplification. The polymerases are indicated in column \\"polymerase\\". We also evaluated several TSO concentrations (concentration in RT is given) and fwd/rev PCR primers (concentration given in PCR reaction). Cell input was HEK293FT cells. TDE1: Large optimization of tagmentation conditions using the TDE1 Tn5 enzyme. We varied reactions by changing PCR polymerase (KAPA / SeqAmp), PCR extension time and the number of PCR cycles during cDNA amplification. During tagmentation, we varied the amount of TDE1 enzyme, the amount of DMF in the tagmentation reaction buffer and the presence of Tween-20 in the final post-tagmentation PCR. Cell input was HEK293FT cells. TSOs_RT_v1-7: Large scale evaluation of conditions relating to RT and PCR, with a focus on new template-switching oligo (TSO) designs. In total, >20,000 cells and >500 conditions are contained in these datasets. The barcode annotation file contains precise information on the reaction conditions of Lysis, RT, PCR as well as utilized TSO designs. Data was generated from HEK293FT cells and hPBMC (Lonza).

Dataset Information

SeQuiLa-cov: A fast and scalable library for depth of coverage calculations.

Background

Results

Conclusions

Publications

SeQuiLa-cov: A fast and scalable library for depth of coverage calculations.

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