Sam:LabNotes/Microbiome-new/2010-12-10
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Data analysis- HC-MDA-Ecoli-SAGs-Ind1to8(SE - down-sampled reads) - Coverage-vs-input reads plot
Background
- Construct Genome coverage-vs-input reads plot using unique mappable reads.
- Y-axis is total genomic regions covered (bps)
- X-axis is the total amount of sequences generated (or mapped).
- An example of this plot could be found in Rax's paper
In order to compare the amplification bias between short-amplified and long amplified MDA, we can compare genome-coverage to assess amplification bias.
- Hypothesis: Given a same number of unique mappable reads, the higher genome coverage means less (position)bias.
- We need to use the ratio of unique mappable read/total reads to decided how much total read we should down-sample to get
- The number of unique mappable reads was decided on 1,000,000 reads (since the lowest number of unique mappable reads is 1,192,051 in ID-4 library.
- The required total reads for getting 1,000,000 unique mappable reads:
File:Sam120810-number of need to downsampled reads.jpg
- Using the down-sampling script to get desired number of raw reads that meet 1,000,000 unique mappable reads).
- Script: Data-sampler.pl (= randomizor by CW)
- Data resource: HC-MDA-Ecoli-SAGs-Ind1to8 (FASTQ format)
- NOTE: Actually this script only split the data from the beginning but not randomly sampling.
- Data output:
/media/disk-2/samchiang/Raw-Read-backup/101123_HL083/HC-MDA-Ecoli-SAGs-Ind1to8/ s_4_ID1_cut_2262955.txt s_4_ID2_cut_1929385.txt s_4_ID3_cut_1150351.txt s_4_ID4_cut_1478415.txt s_4_ID5_cut_2042067.txt s_4_ID6_cut_1680672.txt s_4_ID7_cut_1898254.txt s_4_ID8_cut_1422273.txt
- Perform down-sampled reads alignment using Bowtie, followed by genome coverage calculation.
- Script: Read2coverage-kz-3
- Data resource: down-sampled raw reads (meet 1,000,000 unique mappalbe reads)
- Template:E.coli-k12-mg1655 template
- Bowtie setting: -k 1 -l 28 -n 2 -m 1 --best --best --phred64-quals
- Downstream: Data was used for genome coverage calculation.
Results
File:Sam121410-genome coverage on down-sampled reads-3.jpg
Discussion
- Under a fair comparison using same number of unique mappable reads, short-amplified SAGs showed higher (2~3 fold) genome coverage than their long-amplified SAG mates (ID1 vs ID3, ID2 vs ID4, ID5 vs ID7, ID6 vs ID8).
- Higher genome coverage suggested a less overlapped of sequencing reads, which also suggested a less amplification bias in short-amplified MDA products.