@@ -29,17 +29,22 @@ The mapped fragments are given to a script that filters ambiguously
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mapped fragments:
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```
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./filterAlnScoreAndQual.py -i mapped_smurf_reads.sam \
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- -o unambig_smurf_frags.sam -s 120 -q 1
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+ -o unambig_smurf_frags.sam -s 120 -q 1
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```
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+ The input file ` mapped_smurf_reads.sam ` is just the mapped reads
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+ (e.g. with BWA). The output file ` unambig_smurf_frags.sam `
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+ contains mapped fragments with mapping quality greater than or equal
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+ to 1.
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+
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Then the remaining fragments are given to a script that obtains
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the counts of reads in bins:
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```
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./getBinCounts.py -i unambig_smurf_frags.sam -c hg19.chrom.sizes \
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-b bins_5k_hg19.bed -o bin_counts.bed -s bin_stats.txt
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```
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- The input file ` mapped_smurf_reads .sam` is just the mapped reads
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- (e.g. with BWA). The file ` hg19.chrom.size ` is the size of all chroms
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+ The input file ` unambig_smurf_frags .sam` is the same as described above.
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+ The file ` hg19.chrom.size ` is the size of all chroms
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in the reference genome. This file for the hg19 reference is supplied
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in the ` data ` directory in this repo, and was obtained from the UCSC
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Genome Browser's database. The pre-defined bins file ` bins_5k_hg19.bed `
@@ -164,7 +169,7 @@ well it recovers the known mapping locations. The steps are as follows.
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` bedtools ` (we used v2.26.0). We also require the ` deadzones `
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program from ` http://github.com/smithlabcode/utils ` but this could
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be substituted for any means of excluding unmappable regions.
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- In our CNV analysis, we used ` bwa ` (version... ).
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+ In our CNV analysis, we used ` bwa ` (0.7.17 ).
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## Contacts and Bug Reports
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