I am new to analyze for micro biome data. I am trying to use mothur for my analysis. I have MiSeq paired (fastq) microbiome data. After using contigs and summary.seqs command i need to screen the sequences from my reads. The sumary file look like this:
This point i need to select my minimum and maximum length in order to run screen.seqs but seeing summary output i am confused to select these lengths due to i read that microbiome reads supposed to have 250-300 bp and here i am seeing maximum length is about 600bp.
please help.
The sequencing was done using V3-V4 (for bacteria and archaea - Takahashi et al. 2014). Here i like to ask one more thing. As sequenced was done using forward and reverse primers so i need to clip these adapters using such as cutadpat program and then use mothur or i should not bother about trimming adapters before mothur?
Did you use custom sequencing primers (al.la Kozich/Caporasso) or illumina standard? Custom primers generally mean that pcr primers aren’t sequenced, standard primers mean pcr primers are sequenced.
Thank you for your kind reply i would go with your suggestion and take only maximum length for screen.seqs. Moreover please take a look of my second question regarding primers/adpater triiming, i have just updated.
Thanks once again and looking forward for your answer/view regarding trimming apadters along with quality (>20) prior using mothur.
Note: the idea was found in this paper:
“The V4-V5 Illumina datasets were initially demultiplexed using MiSeq Reporter v2.0. The sequences corresponding to the forward and reverse primers were trimmed from the demultiplexed reads using cutadapt (http://code.google.com/p/cutadapt/) using similar stringency settings to those used for the 454 sequences. The trimmed read pairs were then merged into single contigs using SeqPrep (https://github.com/jstjohn/SeqPrep) followed by a length-filtering step prior to analysis with QIIME. The Illumina V4 read pairs were merged and length filtered in a similar manner as the V4-V5 reads to form single contigs prior to being demultiplexed with QIIME. Reads from all datasets were quality filtered using a Q20 minimum value during demultiplexing.”