Comments (5)
Define "abnormally low". Have you spot-checked a few regions to see if they're correct. There's no a priori reason this shouldn't work.
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The boxplot indicates average methylation levels in each bin (100kb bin for rice and 1Mb for the large genome organism).
In the case of rice, both methylation callers show very similar patterns. Meanwhile, only bismark seemed to work normally.
methylation_caller.pdf
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Hmm, OK, that does look odd. I'll look into this.
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Can you suggest any public dataset or other data source I can use for debugging this?
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Sorry for taking a time to find appropriate datasets.
For your informatin, following the current analysis environments.
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 1_gnu conda-forge
alsa-lib 1.2.3 h516909a_0 conda-forge
bismark 0.23.1 hdfd78af_0 bioconda
bowtie 1.3.0 py36hf1ae8f4_1 bioconda
bowtie2 2.4.1 py36h5202f60_3 bioconda
bwa 0.7.17 h5bf99c6_8 bioconda
bwameth 0.2.3 pyh5e36f6f_0 bioconda
bz2file 0.98 py_0 conda-forge
bzip2 1.0.8 h516909a_3 conda-forge
c-ares 1.18.1 h7f8727e_0
ca-certificates 2021.10.26 h06a4308_2
cairo 1.16.0 h3fc0475_1005 conda-forge
certifi 2021.5.30 py36h06a4308_0
curl 7.80.0 h7f8727e_0
cutadapt 1.18 py36h14c3975_1 bioconda
fontconfig 2.13.1 h1056068_1002 conda-forge
freetype 2.10.2 he06d7ca_0 conda-forge
gettext 0.19.8.1 hc5be6a0_1002 conda-forge
giflib 5.2.1 h516909a_2 conda-forge
glib 2.66.1 he1b5a44_1 conda-forge
graphite2 1.3.13 he1b5a44_1001 conda-forge
gsl 2.5 h294904e_1 conda-forge
harfbuzz 2.7.2 hee91db6_0 conda-forge
hisat2 2.2.1 h1b792b2_3 bioconda
htslib 1.14 h9093b5e_0 bioconda
icu 67.1 he1b5a44_0 conda-forge
jpeg 9d h516909a_0 conda-forge
k8 0.2.5 he513fc3_0 bioconda
krb5 1.19.2 hac12032_0
lcms2 2.11 hbd6801e_0 conda-forge
ld_impl_linux-64 2.34 hc38a660_9 conda-forge
libblas 3.8.0 17_openblas conda-forge
libcblas 3.8.0 17_openblas conda-forge
libcurl 7.80.0 h0b77cf5_0
libdeflate 1.7 h27cfd23_5
libedit 3.1.20210714 h7f8727e_0
libev 4.33 h516909a_0 conda-forge
libffi 3.2.1 he1b5a44_1007 conda-forge
libgcc 7.2.0 h69d50b8_2 conda-forge
libgcc-ng 11.2.0 h1d223b6_12 conda-forge
libgfortran-ng 7.5.0 hdf63c60_16 conda-forge
libglib 2.66.1 h0dae87d_1 conda-forge
libgomp 11.2.0 h1d223b6_12 conda-forge
libiconv 1.16 h516909a_0 conda-forge
liblapack 3.8.0 17_openblas conda-forge
libnghttp2 1.46.0 hce63b2e_0
libopenblas 0.3.10 pthreads_hb3c22a3_4 conda-forge
libpng 1.6.37 hed695b0_2 conda-forge
libssh2 1.9.0 hab1572f_5 conda-forge
libstdcxx-ng 9.3.0 hdf63c60_16 conda-forge
libtiff 4.1.0 hc7e4089_6 conda-forge
libuuid 2.32.1 h14c3975_1000 conda-forge
libwebp-base 1.1.0 h516909a_3 conda-forge
libxcb 1.13 h14c3975_1002 conda-forge
libxml2 2.9.10 h68273f3_2 conda-forge
libzlib 1.2.11 h36c2ea0_1013 conda-forge
lz4-c 1.9.2 he1b5a44_3 conda-forge
methyldackel 0.6.1 h29dff0a_1 bioconda
methylpy 1.4.3 py36h41a55b7_0 bioconda
minimap2 2.17 hed695b0_3 bioconda
mysql-connector-c 6.1.6 2 bioconda
ncurses 6.2 he1b5a44_1 conda-forge
numpy 1.19.1 py36h3849536_2 conda-forge
openjdk 11.0.8 hacce0ff_0 conda-forge
openssl 1.1.1m h7f8727e_0
pcre 8.44 he1b5a44_0 conda-forge
perl 5.30.3 h516909a_0 conda-forge
picard 2.18.29 0 bioconda
pigz 2.3.4 hed695b0_1 conda-forge
pip 20.2.2 py_0 conda-forge
pixman 0.38.0 h516909a_1003 conda-forge
pthread-stubs 0.4 h14c3975_1001 conda-forge
pysam 0.17.0 py36h61e5637_0 bioconda
python 3.6.11 h4d41432_2_cpython conda-forge
python_abi 3.6 1_cp36m conda-forge
readline 8.0 he28a2e2_2 conda-forge
samtools 1.14 hb421002_0 bioconda
scipy 1.5.2 py36h3a855aa_0 conda-forge
setuptools 50.0.0 py36h9f0ad1d_0 conda-forge
sqlite 3.33.0 h4cf870e_0 conda-forge
tbb 2020.1 hc9558a2_0 conda-forge
tk 8.6.10 hed695b0_0 conda-forge
toolshed 0.4.6 pyh864c0ab_3 bioconda
ucsc-bigwigtowig 357 1 bioconda
ucsc-fatotwobit 357 1 bioconda
ucsc-twobitinfo 357 1 bioconda
ucsc-wigtobigwig 357 1 bioconda
wheel 0.35.1 pyh9f0ad1d_0 conda-forge
xopen 0.7.3 py_0 bioconda
xorg-fixesproto 5.0 h14c3975_1002 conda-forge
xorg-inputproto 2.3.2 h14c3975_1002 conda-forge
xorg-kbproto 1.0.7 h14c3975_1002 conda-forge
xorg-libice 1.0.10 h516909a_0 conda-forge
xorg-libsm 1.2.3 h84519dc_1000 conda-forge
xorg-libx11 1.6.12 h516909a_0 conda-forge
xorg-libxau 1.0.9 h14c3975_0 conda-forge
xorg-libxdmcp 1.1.3 h516909a_0 conda-forge
xorg-libxext 1.3.4 h516909a_0 conda-forge
xorg-libxfixes 5.0.3 h516909a_1004 conda-forge
xorg-libxi 1.7.10 h516909a_0 conda-forge
xorg-libxrender 0.9.10 h516909a_1002 conda-forge
xorg-libxtst 1.2.3 h516909a_1002 conda-forge
xorg-recordproto 1.14.2 h516909a_1002 conda-forge
xorg-renderproto 0.11.1 h14c3975_1002 conda-forge
xorg-xextproto 7.3.0 h14c3975_1002 conda-forge
xorg-xproto 7.0.31 h14c3975_1007 conda-forge
xz 5.2.5 h516909a_1 conda-forge
zlib 1.2.11 h36c2ea0_1013 conda-forge
zstd 1.4.5 h6597ccf_2 conda-forge
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Related Issues (20)
- Understanding --minConversionEfficiency argument HOT 1
- Genome browsing from MethylDackel bedGraphCpG file
- per-fragment methylation HOT 2
- mbias result is different between bismark and bwameth output HOT 1
- CURL_OPENSSL conflict with samtools HOT 3
- Installation failure: "bigWig.h: No such file or directory" HOT 1
- Clarification on definition of "unmethylated C" HOT 1
- Coverage of C sites HOT 1
- mbias HOT 1
- Does indel effect the methylation calling or C context determination HOT 1
- Positions in cytosine_report did not match the regions in providing bed file
- about M-bias HOT 1
- Could not repeat a CpG extraction with the same reference file and its index HOT 1
- Mixed up reads within bam file
- How to index genome file for MethylDackel? HOT 1
- Confused regarding CTOT, CTOB. Are there suggested values? HOT 3
- Issue running MethylDackel extract in parallel mode using minConversionEfficiency
- Question about minimum coverage
- Different CpG calls when using different regions of inclusion for Methyldackel extract
- Alignment trimming for Soft Clip reads?
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