From 5b81c05bf0dca9dc0ce79f3e7cf55ba3674fa9e0 Mon Sep 17 00:00:00 2001 From: Art Rand Date: Thu, 19 Sep 2024 13:03:11 -0700 Subject: [PATCH] [docs] add docs pages that were missed. --- docs/evaluate_motif.html | 251 +++++++++++++++++++++ docs/images/modkit_localise_ctcf_5mC.png | Bin 0 -> 271102 bytes docs/intro_localize.html | 255 ++++++++++++++++++++++ docs/intro_motif.html | 239 ++++++++++++++++++++ docs/intro_stats.html | 265 +++++++++++++++++++++++ 5 files changed, 1010 insertions(+) create mode 100644 docs/evaluate_motif.html create mode 100644 docs/images/modkit_localise_ctcf_5mC.png create mode 100644 docs/intro_localize.html create mode 100644 docs/intro_motif.html create mode 100644 docs/intro_stats.html diff --git a/docs/evaluate_motif.html b/docs/evaluate_motif.html new file mode 100644 index 0000000..54fe57a --- /dev/null +++ b/docs/evaluate_motif.html @@ -0,0 +1,251 @@ + + + + + + Evaluate and refine a table of known motifs - Modkit + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Evaluate a table of known motifs

+

The modkit search command has an option to provide any number of known motifs with --know-motif. +If you already have a list of candidate motifs (e.f. from a previous run of modkit motif search) you can check these motifs quickly against a bedMethyl table with modkit motif evaluate.

+
modkit motif evaluate -i ${bedmethyl} --known-motifs-table motifs.tsv -r ${ref}
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+

Similarly, the search algorithm can be run using known motifs as seeds:

+
modkit motif refine -i ${bedmethyl} --known-motifs-table motifs.tsv -r ${ref}
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+

The output tables to both of these commands have the same schema:

+
+ + + + + + + + +
columnnamedescriptiontype
1mod_codecode specifying the modification found in the motifstr
2motifsequence of identified motif using IUPAC codesstr
3offset0-based offset into the motif sequence of the modified baseint
4frac_modfraction of time this sequence is found in the high modified set col-5 / (col-5 + col-6)float
5high_countnumber of occurances of this sequence in the high-modified setint
6low_countnumber of occurances of this sequence in the low-modified setint
7mid_countnumber of occurances of this sequence in the mid-modified setint
8log_oddslog2 odds of the motif being in the high-modified setint
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+

In the human-readable table columns (1) and (2) are merged to show the modification code in the motif sequence context, the rest of the columns are the same as the machine-readable table.

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qyxoIT#GkcmYyHMefrbqTsJ=RTZ!su?!Uv@{S*TOx{<) z*%xQV|MT^TDTw*;ssVw_k9Dro&r$pg*K4p;r({TnCE>6$=PB3+vRqtzMA23D5#~Ac zrUyovo&Nq<@~)7h5!;^LN|l`df%nrR4_ED2j*c(j>NM}LxFn`$kV13WhJ5?2RP*Wm z!)psnqIkmB(U{n)E0`6nsWQN)^dU~so;Zq_w$ zrK1d!>P;v0Z#*5G>S%#pDLVFg#C9`f;`%bo$DRno6+G);L|jLMCz)%m-x(vkTYxwN zPURIE{Q%kYc_wTRdC#f)moz_;p3xn>8!gmpDqSo>muMfk3kW2g#dVL|8&$0GA5M$C z^x6vUkD{tp@OZ&?Uv|hgJUFNyntFuFYq4r^bY1{`2~p6&prqg%Yz)jyVe8%+gMM+Z zX*|z(SOSRou=4GZ{|;L;cM5T`?TA{FOV8NaLdosW37?FDdEuRh&jTs8(2n6&XL`RD z`rZ9GR6sMfD0+>rs%d6{NgzhbM!o1^Et!oB5&tu~F{@jnPh(^HFG$px7&xq2FM>@- zUIVa*2)bFTjou`&=KUhGoA~xj*Deu4FE{>Or?iWdHP61j;aWhn_x^rR_yW2QUJ&&- zIPYA%rE3)BvxIs=Pi~+yL%taR*K_kCbhWD@7j=);o%o^Yib@0V>%2fsQ>ajy-sZKj z9o}82<~LBi73%g+`sclUYLZq|sua;w7meA5)fYrTHcJ<-f$H0etMZ5cH*qTKV0ay?1H8Jva+#x>&yPm8h+N+0V1SXy~Q|fb!S3jkg-U3UA z1Uy0kOtq(q!z!)5Ix({y#?tjH^7(i9-l-T>DLUU-FXTKF8iIz-^wL-1i3R2z8Be}`0FsEz3k(Y;r zQRiv1secq4XMdbTI(tw1UbV_e@`6EmZ7|GckIC$=_Z&Bv;-~oXI=4|MZv2q7-OaU% zwk3EPW$lTz39g(>zZp_H5Pt{zjLeY>%%KI#7|9lNej%c<&um%l%tO)!nhb&hsNP1&Mu(2(RRG4uUn!VI_g)pd$>+d?6ZOa zPw%U^(m+NV42je>)pPT2Lt_hu&dXbpTPrMaXGnWhro@7?W2OBlK$$sjtwSqA6JvQk zpBbro2x#JAs`MDyO@?_idbWHI%2u)#L-I2HX!h;ReKz_~;mAO3VB%|dy@De6G&EHE zbL!Ef8^m0&Lio%8vVkztz?kH$3CaG*UE58`Th0a2!Qp%SmkmDh6`e79YH+gike&mo zbq8Fbka@=5S~xq;8@|#Gqwi~vu9)9%IVzV{5&7TZ$30#gQ5n3&>M)|oM#5rh#=NoE zb6cdMET5K?_uB58GtHlACT>sLi$CHKRKsE34_@}w61koYEGW7n+t{2`N}sotT}f?t zYPXBntERk2Dmt?*PjXO%Wvf|T1XUu&ks^%0FIJBI(A@9wGvynxj~kES^{7wTvl4ao z4Q(eR4&~~EGHRx{gqOKqi!V!H4i>U$jGe{2oPAVF&90qx!Km}$i|PAU?wmLqx!O;7 zW>&Wet^CF(E=Bh>FbN5e2?+wN>C49?ZpPar1tR}rCL`Lu5h*MmisNHC5sSe~KAL?W zwXRitw|#cY%(E0W>_M<-3`9c4%X;J&88GZIzcJc?9H&pOSoy-CE_UT}4q5y=7yR|z zup7HK!FL+50~kq>1H&}c`C}p_9|yOHdW7Oc2REM2>{QQi=bu0O2%8eJ z<~mcL@mmR|->ssHQ}HF~EnBWZHNCi}A?du92yg301#9hKS|y6?4WPQ)R-jgd9#RM4 zk`MeMj8E+pVh^^fJNuX>LuUbcIdUKRbniuxlT;W!Y-Q>ehjxdTN`}~3#wA$_ahPG= ze+zQ*HMO_7+K(NyEN%u17@Tct*cN+NDQp(h>gxyUuAn}cSTBYh8J-7<*E=!;g z$WZ?EOuE+Hm(vaC-s7qJW5}jQUmze+A~G8EL2t`1gLADoSLNpJxklumETOOs8Ayb@>z@>g{a42tp+2k};M)l#MS^y~ik zm^KZaGpJS@J-a(A8gQy+&?{_MBq4+#iT+A(7=5BuBu{~|h!HKav4xPdL`*@8WSrdTb1 z-F5ELGPx!JJS%&wub+!N+>m?pELWUVt%JVHi(br^mB;epz?kNmX>O&ZoJJCmLA8N; za+07!s%)>8=-;#b5yKn)7Pp|+359=O_WwUR3L>L}79Bbgxc(zgdXz-vHcPfc9x{JG z!=!@iZ=wFjCRPxQtT~!?zcBv&FXet%^pTqFTmWYv=y6F$ndHnGqT)^R-*M&N$Kue3 zVcKTrL;m~(@MyY4Q>kY#btFCD(|p>C)tb4(o<(5h_W{=bdZ`?=JACda9hD3TEK8(^ OkD{#Vt5RvBp#KMWnZ + + + + + Investigating patterns with localise - Modkit + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+ + diff --git a/docs/intro_motif.html b/docs/intro_motif.html new file mode 100644 index 0000000..050a6a9 --- /dev/null +++ b/docs/intro_motif.html @@ -0,0 +1,239 @@ + + + + + + Working with sequence motifs - Modkit + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + + + + + + + + + + + + + + + + +
+ +
+ + + + + + + + +
+
+

Working with sequence motifs

+

The modkit motif suite contains tools for discovery and exploration of short degenerate sequences (motifs) that may be enriched in a sample. +A common use case is to discover the motifs enriched for modification in a native bacterial sample which can give indication of methyltransferase enzymes present in the genomes present in the sample.

+

The following tools are available:

+
    +
  1. Find enriched motifs de novo from a bedMethyl with search.
  2. +
  3. evaluate or refine a table of known motifs
  4. +
  5. Making a motif BED file with motif bed
  6. +
+ +
+ + +
+
+ + + +
+ + + + + + + + + + + + + + + + + + +
+ + diff --git a/docs/intro_stats.html b/docs/intro_stats.html new file mode 100644 index 0000000..f04e043 --- /dev/null +++ b/docs/intro_stats.html @@ -0,0 +1,265 @@ + + + + + + Calculating modification statistics in regions - Modkit + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + + + + + + + + + + + + + + + + +
+ +
+ + + + + + + + +
+
+

Calculating modification statistics in regions

+

There are many analysis operations available in modkit once you've generated a bedMethyl table. +One such operation is to calculate aggregation statistics on specific regions, for example in CpG islands or gene promoters. +The modkit stats command is designed for this purpose.

+
# these files can be found in the modkit repository
+cpgs=tests/resources/cpg_chr20_with_orig_names_selection.bed
+sample=tests/resources/lung_00733-m_adjacent-normal_5mc-5hmc_chr20_cpg_pileup.bed.gz
+modkit stats ${sample} --regions ${cpgs} -o ./stats.tsv [--mod-codes "h,m"]
+
+
+

Note that the argument --mod-codes can alternatively be passed multiple times, e.g. this is equivalent:
+--mod-codes c --mod-codes h

+
+

The output TSV has the following schema:

+
+ + + + + + + + +
columnNameDescriptiontype
1chromname of reference sequence from BAM headerstr
2start position0-based start positionint
3end position0-based exclusive end positionint
4namename of the region from input BED (. if not provided)str
5strandStrand (+, -, .) from the input BED (. assumed for when not provided)str
6+count_xtotal number of x base modification codes in the regionint
7+count_valid_xtotal valid calls for the primary base modified by code xint
8+percent_xcount_x / count_vali_x * 100float
+
+

Columns 6, 7, and 8 are repeated for each modification code found in the bedMethyl file or provided with --mod-codes argument.

+

An example output:

+
chrom  start     end       name     strand   count_h        count_valid_h  percent_h   count_m        count_valid_m  percent_m
+chr20  9838623   9839213   CpG: 47  .        12             1777           0.6752954   45             1777           2.532358
+chr20  10034962  10035266  CpG: 35  .        7              1513           0.46265697  0              1513           0
+chr20  10172120  10172545  CpG: 35  .        15             1229           1.2205045   28             1229           2.278275
+chr20  10217487  10218336  CpG: 59  .        29             2339           1.2398461   108            2339           4.617358
+chr20  10433628  10434345  CpG: 71  .        29             2750           1.0545455   2              2750           0.07272727
+chr20  10671925  10674963  CpG: 255 .        43             9461           0.45449743  24             9461           0.25367296
+
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+ + + + + + + + + + + + + + + + + + + +
+ +
+ + + + + + + + +
+
+

Investigating patterns with localise

+

One a bedMethyl table has been created, modkit localise will use the pileup and calculate per-base modification aggregate information around genomic features of interest. +For example, we can investigate base modification patterns around CTCF binding sites.

+

+ 5mC patterns at CTCF sites +

+

The input requirements to modkit localise are simple:

+
    +
  1. BedMethyl table that has been bgzf-compressed and tabix-indexed
  2. +
  3. Regions file in BED format (plaintext).
  4. +
  5. Genome sizes tab-separated file: <chrom>\t<size_in_bp>
  6. +
+

an example command:

+
modkit localise ${bedmethyl} --regions ${ctcf} --genome-sizes ${sizes}
+
+

The output table has the following schema:

+
+ + + + + +
columnNameDescriptiontype
1mod codemodification code as present in the bedmethylstr
2offsetdistance in base pairs from the center of the genome features, negative values reflect towards the 5' of the genomeint
3n_validnumber of valid calls at this offset for this modification codeint
4n_modnumber of calls for this modification code at this offsetint
5percent_modifiedn_mod / n_valid * 100float
+
+

Optionally the --chart argument can be used to create HTML charts of the modification patterns.

+ +
+ + +
+
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