CleanSeq: A Pipeline for Contamination Detection, Cleanup, and Mutation Verifications from Microbial Genome Sequencing Data  
[PERSON]  
1 School of Software Engineering, East China Normal University, Shanghai 200062, China; [EMAIL_ADDRESS] (C.W.J. ); [EMAIL_ADDRESS] (C.K.) [PERSON]  
2 Laboratory of Biology and Information Science, School of Life Sciences, East China Normal University, Shanghai 20002, China; [EMAIL_ADDRESS] (Y.X. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (N.L. ); [EMAIL_ADDRESS] (D.T.J. ); [EMAIL_ADDRESS] (H.L. ); [EMAIL_ADDRESS] (F.H.) [PERSON]  
2 Laboratory of Biology and Information Science, School of Life Sciences, East China Normal University, Shanghai 20002, China; [EMAIL_ADDRESS] (Y.X. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (N.L. ); [EMAIL_ADDRESS] (D.T.J. ); [EMAIL_ADDRESS] (H.L. ); [EMAIL_ADDRESS] (F.H.) [PERSON]  
1 School of Software Engineering, East China Normal University, Shanghai 200062, China; [EMAIL_ADDRESS] (C.W.J. ); [EMAIL_ADDRESS] (C.K.) [PERSON]  
2 Laboratory of Biology and Information Science, School of Life Sciences, East China Normal University, Shanghai 20002, China; [EMAIL_ADDRESS] (Y.X. ); [EMAIL_ADDRESS] (Y.L. ); [EMAIL_ADDRESS] (N.L. ); [EMAIL_ADDRESS]  
the sequencing technology and the quality of most sequencing data have been improved significantly, computational and bioinformatical approaches for contamination and decontamination verification have become a challenge for biologists and bioinformaticians [6]. For most biologists, available experiments like PCR or sequencing of PCR products have been routinely employed to identify contaminants or mutations from genomic samples [7]. Decontaminated genomic sequencing data with clean reads are the only desirable source for detecting possible variants correctly. Thus, it is beneficial to have such bioinformatical tools containing functions in the discrimination and removal of contaminating reads and improving variant calling from clean reads. For bioinformatics, on the other hand, there have already been some tools or pipelines developed for distinguishing contaminated reads in microbial whole genomic sequencing (WGS) samples [5]. To avoid drawing false conclusions, one of the main tasks of quality check (QC) for raw reads is to perform taxonomic classification, based on which the possible contaminated species could be identified for further bioinformatical analysis [8]. Based on the Basic Local Alignment Search Tool (BLAST) [9], Burrows-Wheeler Aligner (BWA) [10], Sequence Alignment/Map (SAMtools) [11], or the Genome Analysis Toolkit (GATK) [12], integrated tools and pipelines, including CheckM [13], Kraken [14], ConFindr [15], FastQ Screen [16], MutScan [17], DecontaMiner [18], and microDecon [19] have been developed for contamination detection or cleanup. ConFindr [15] is a Python-based pipeline that could detect contaminant species automatically and demonstrates a better sensitivity for detecting intraspecies contamination. microDecon [19] is an R package that claims a high cleanup rate (98.1%) in simulated samples and could effectively remove contamination across a broad range of situations. DecontaMiner [18], DeconSeq [20], and FastQ Screen are all written in Perl, and DecontaMiner is mainly designed to deal with unmapped reads for a contamination screening [18]. DeconSeq [20] could be used to remove contaminated reads from metagenomic data based on the BWA-SW algorithm, which supports a web interface. FastQ Screen validates the origin of DNA samples by quantifying the proportion of reads mapping to multiply reference genomes. FastQ Screen generates reports for the source of all predictable contaminated reads and runs BLAST if there is no match for specific reads [16]. MutScan is a C++ algorithm that could detect and visualize target mutations by directly scanning FASTQ raw data. Multiple tools can be used continuously for complete contamination data processing and analysis [17].