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ShareScore release 0.9.0
Dataset results
10 results for “mappable”
Mappability tracks for human assemblies (hg19 and GRCh38)
<p>They were created by using the GEM mapper aligner (Derrien et al., 2012) allowing up to two mismatches and considering sliding windows of 100-mer. They are exploited by the EXCAVATOR2 tool for reducing technical biases of Read Count measure in WES/TS experiments.</p>
Mappability of the mouse and human genomes and methylomes with Umap and Bismap
<p>This dataset consists of single-read mappability (Bed files) and multi-read mappability (Wiggle files) of human and mouse genomes and methylomes (bisulfite-converted genome). We provide mappability information for the two most recent assemblies of each organism, and for four different read lengths (24 bp, 36 bp, 50 bp, and 100 bp).</p> <p> </p>
30-mer mappable regions in the human hg19 genome
<p>Knowing where reads can uniquely map in the genome is useful for nascent RNA assays, both in statistical calculations and to make predictions.</p> <p>The dataset was created using the bowtie 1 aligner. The genome was windows at 30 basepair genomic intervals and mapped back to the genome. If the read maps to more than one place, the read is thrown away. Therefore the regions captured in the dataset are regions that any read at least 30 basepairs long will map to uniquely. The shell script originally used to create this dataset has been lost.</p>
Mappability .bigwig reference files for hg38/hg19; various read lengths
<p>This dataset contains reference mappability .bigwig files for the reference genomes hg38 and hg19, for various read lengths. The files were generated with the GEM library (https://sourceforge.net/projects/gemlibrary/files/gem-library/Binary%20pre-release%203/GEM-binaries-Linux-x86_64-core_i3-20130406-045632.tbz2) using <a href="https://raw.githubusercontent.com/epigen/LIQUORICE/master/liquorice/create_mappability_bigwigs.sh">this</a> script (based on <a href="https://evodify.com/gem-mappability/">this</a> work).</p> <p>The files can be used as input for LIQUORICE (<a href="https://liquorice.readthedocs.io">https://liquorice.readthedocs.io</a>) - just select the file that matches your sequencing protocol (i.e. read length) and the reference genome of your mapped .bam files.</p>
DOHH2 hg38 CTCF ChIP-seq Dataset filtered for Unique Multiread Mappability
<p>hg38 DOHH2 CTCF ChIP-seq Dataset filtered for Unique Multiread Mappability at a threshold of .75 using Umap</p>
DOHH2 hg38 H3K27ac ChIP-seq Dataset filtered for Unique Multiread Mappability
<p>hg38 DOHH2 H3K27ac ChIP-seq Dataset filtered for Unique Multiread Mappability at a threshold of .75 using Umap</p>
DOHH2 hg38 H3K4me3 ChIP-seq Dataset filtered for Unique Multiread Mappability
<p>hg38 DOHH2 H3K4me3 ChIP-seq Dataset filtered for Unique Multiread Mappability at a threshold of .75 using Umap</p>
DOHH2 hg38 H3K27me3 ChIP-seq Dataset filtered for Unique Multiread Mappability
<p>hg38 DOHH2 H3K27me3 ChIP-seq Dataset filtered for Unique Multiread Mappability at a threshold of .75 using Umap</p>
DOHH2 hg38 H3K4me1 ChIP-seq Dataset filtered for Unique Multiread Mappability
<p>DOHH2 hg38 H3K4me1 ChIP-seq Dataset filtered for Unique Multiread Mappability</p>
JG2.1.0 Gene mappability
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