bicycle (bisulfite-based methylcytosine caller) is a next-generation sequencing bioinformatics pipeline able to perform a full DNA methylation level analysis
Home Page: http://www.sing-group.org/bicycle
License: GNU Lesser General Public License v3.0
Hi there,
I manage to get perform the differential methylation analysis along with the bed file. However, when I get the results of q-value its the same across the whole methylated regions unlike p-value.
Example
`
| #region | sequence | start | stop | T3 (treatment) | T3R (treatment) | T1 (control) | T1R (control) | treatment average | control average | log2FC(treament/control) | p-value | q-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| chr1_217308838-217309329 | chr1 | 2.17E+08 | 2.17E+08 | 139/882 | 213/1379 | 67/1191 | 24/734 | 0.155683 | 0.047273 | 1.719534 | 4.85E-04 | 0.80766 |
| chr4_174443205-174444459 | chr4 | 1.74E+08 | 1.74E+08 | 426/1676 | 479/1942 | 393/2444 | 305/1989 | 0.250138 | 0.157455 | 0.667782 | 4.96E-04 | 0.80766 |
| chr11_123172361-123173273 | chr11 | 1.23E+08 | 1.23E+08 | 251/1162 | 349/1695 | 570/1828 | 508/1495 | 0.210011 | 0.324406 | -0.62734 | 5.33E-04 | 0.80766 |
| chr3_61548855-61549505 | chr3 | 61548855 | 61549505 | 162/343 | 223/468 | 326/474 | 424/633 | 0.474723 | 0.677507 | -0.51315 | 8.71E-04 | 0.80766 |
| chr17_40575129-40575502 | chr17 | 40575129 | 40575502 | 16/276 | 22/279 | 55/233 | 73/234 | 0.068468 | 0.27409 | -2.00114 | 8.93E-04 | 0.80766 |
| ` |
This same happened with different comparison of samples. but with different fixed value.
the command I used
bicycle analyze-differential-methylation -p /mnt/BAM/Group5/Table5 -c 9269E,9270E,9272E -t 9271E,9362E,9363E,9364E -b /mnt/reference/hg19/truseq-methyl-capture-epic-manifest-file.bed
Any suggestion ?
Update: it does change but another fixed value, so in each analysis I will have 2 or 3 q-value. Just wanted to know if this is normal/correct.
It should at least allow .fasta and maybe .fna. The worst part is that it just silently does nothing instead of at least issuing a warning.
I am new to bicycle and have downloaded sample data from the bicycle website (Data for E.Coli)
After the project creation, we ran the following command:
java -jar /home/admin1/Downloads/bicycle-1.8.2/bicycle-1.8.2.jar reference-bisulfitation -p data/myproject/
We get errors that the location is not accessible or not available though we have created the directory previously. Is this an error anyone has faced?
SEVERE: Error during execution
java.lang.IllegalArgumentException: Cannot find /run/user/1000/gvfs/smb-share or it is not a directory, or it is not accessible
at es.cnio.bioinfo.bicycle.Sample.buildSamples(Sample.java:122)
at es.cnio.bioinfo.bicycle.Project.readFromDirectory(Project.java:268)
at es.cnio.bioinfo.bicycle.cli.ProjectCommand.execute(ProjectCommand.java:50)
at es.cnio.bioinfo.bicycle.cli.CLIApplication.run(CLIApplication.java:86)
at es.cnio.bioinfo.bicycle.cli.Main.main(Main.java:27)
I am attaching a screen shot of the error.
Please help with this error.
Hi there,
thanks for your efforts to make my analysis easy along with lengthy explanation page. I am looking at the final differential methylation results using BED file and I have a question regarding headers and what do they mean:
#region sequence start stop SRR2052492 (treatment) SRR2052493 (treatment) SRR2052494 (treatment) SRR2052495 (treatment) SRR2052496 (treatment) SRR2052487 (control) SRR2052488 (control) SRR2052489 (control) SRR2052490 (control) SRR2052491 (control) treatment average control average log2FC(treament/control) p-value q-value MEG3 chr14 101291953 101292257 1455768/2043201 1636631/3258147 1497615/2643988 1278819/2677687 1699837/1958100 960649/2260743 1655354/3623531 1234101/2867390 1729232/3490690 2112253/4771083 0.6015893811705044 0.45208907524094044 0.4121720465419593 0.032485239405786 0.054142065676310004 CDKN1A chr6 36645463 36645696 106164/169351 67574/108667 39848/111440 70332/114278 56000/82614 184466/257701 135047/184961 153820/212228 90107/139840 97084/153940 0.5797185981069327 0.6962631895179566 -0.264279982267956 0.06970890125229327 0.0871361265653666 IRS1 chr2 227659612 227659781 471/1525 493/1510 556/2015 240/861 534/2047 326/818 325/1045 455/1336 680/1600 607/2070 0.2882633827594873 0.34837676517688165 -0.27326082007437236 0.031291095111098274 0.054142065676310004 INS chr11 2182552 2182775 133094/209138 291969/567402 119026/425194 152310/651761 177366/278973 80460/481158 165062/765934 174273/633564 169227/724203 288122/1036615 0.40974354597583645 0.2408760847942344 0.7664300613080263 0.022056895484407948 0.054142065676310004 PDE7B chr6 136172766 136172917 358560/2258785 151970/1578967 368147/2086541 104049/1062921 506169/2399992 119657/960632 197487/1205221 168450/1002387 197266/1376956 112174/1444852 0.15860896202767896 0.1327258145510687 0.2570252958195374 0.6929437289294518 0.6929437289294518
For example (i am using the results output from the manual section) i am not sure if i understand what is written beneath each sample at a certain target region
SRR2052492 (treatment) column at MEG3 region its says 1455768/2043201 what does that mean ? number of cytosine levels / total depth ?
also log2FC(treament/control) column the values ranges from -1 to 1 what does it mean to have a negative and a positive value in terms of methylation ? for example if the value is -0.3 what does that mean ? and if its 0.8 what does that mean in terms of methylation?
Thanks
Hello to everyone,
in my new lab I have been given some files from a bisulphite targeted sequencing, with only a few genes. I am new to analysing this kind of results and I am trying to do it with BICYCLE, but I am having some problems. I have four ".FASTQ" sequences with these names:
Undetermined_S0_L001_R1_001.fastq 1_S1_L001_R1_001.fastq
Undetermined_S0_L001_R1_001.fastq 1_S1_L001_R2_001.fastq
1_S1_L001_R1_001.fastq 1_S1_L001_R1_001.fastq
1_S1_L001_R1_001.fastq 1_S1_L001_R2_001.fastq
I don't really know what the "Undetermined" sequences are, but they take up about 15 GB, while the other two are quite small, about 7 MB uncompressed. I know that I have to use these and that they are paired, hence the "R1" and "R2" and that I need a reference genome, for which I downloaded this one:.
With this, I have simply tried to combine the information from the "Quick start" tutorial, with the "Case study" tutorial to do my analysis, I have been able to complete without problems. So with my samples I was also able to complete the following steps: Create project, Create bisulphite version of the genome, Create reference index and Align reads; but when I get to the methylation analysis, I get the following error:
[INFO] MethylationAnalysis: GATK: ##### ERROR ------------------------------------------------------------------------------------------
[INFO] MethylationAnalysis: GATK: ##### ERROR A USER ERROR has occurred (version 1.3):
[INFO] MethylationAnalysis: GATK: ##### ERROR The invalid arguments or inputs must be corrected before the GATK can proceed
[INFO] MethylationAnalysis: GATK: ##### ERROR Please do not post this error to the GATK forum
[INFO] MethylationAnalysis: GATK: ##### ERROR
[INFO] MethylationAnalysis: GATK: ##### ERROR See the documentation (rerun with -h) for this tool to view allowable command-line arguments.
[INFO] MethylationAnalysis: GATK: ##### ERROR Visit our wiki for extensive documentation http://www.broadinstitute.org/gsa/wiki
[INFO] MethylationAnalysis: GATK: ##### ERROR Visit our forum to view answers to commonly asked questions http://getsatisfaction.com/gsa
[INFO] MethylationAnalysis: GATK: ##### ERROR
[INFO] MethylationAnalysis: GATK: ##### ERROR MESSAGE: Input files reads and reference have incompatible contigs: No overlapping contigs found.
[INFO] MethylationAnalysis: GATK: ##### ERROR reads contigs = [1_dna:chromosome_chromosome:GRCh38:1:1:248956422:1_REF, 10_dna:chromosome_chromosome:GRCh38:10:1:133797422:1_REF, 11_dna:chromosome_chromosome:GRCh38:11:1:135086622:1_REF, 12_dna:chromosome_chromosome:GRCh38:12:1:133275309:1_REF, 13_dna:chromosome_chromosome:GRCh38:13:1:114364328:1_REF, 14_dna:chromosome_chromosome:GRCh38:14:1:107043718:1_REF, 15_dna:chromosome_chromosome:GRCh38:15:1:101991189:1_REF, 16_dna:chromosome_chromosome:GRCh38:16:1:90338345:1_REF, 17_dna:chromosome_chromosome:GRCh38:17:1:83257441:1_REF, 18_dna:chromosome_chromosome:GRCh38:18:1:80373285:1_REF, 19_dna:chromosome_chromosome:GRCh38:19:1:58617616:1_REF, 2_dna:chromosome_chromosome:GRCh38:2:1:242193529:1_REF, 20_dna:chromosome_chromosome:GRCh38:20:1:64444167:1_REF, 21_dna:chromosome_chromosome:GRCh38:21:1:46709983:1_REF, 22_dna:chromosome_chromosome:GRCh38:22:1:50818468:1_REF, 3_dna:chromosome_chromosome:GRCh38:3:1:198295559:1_REF, 4_dna:chromosome_chromosome:GRCh38:4:1:190214555:1_REF, 5_dna:chromosome_chromosome:GRCh38:5:1:181538259:1_REF, 6_dna:chromosome_chromosome:GRCh38:6:1:170805979:1_REF, 7_dna:chromosome_chromosome:GRCh38:7:1:159345973:1_REF, 8_dna:chromosome_chromosome:GRCh38:8:1:145138636:1_REF, 9_dna:chromosome_chromosome:GRCh38:9:1:138394717:1_REF, MT_dna:chromosome_chromosome:GRCh38:MT:1:16569:1_REF, X_dna:chromosome_chromosome:GRCh38:X:1:156040895:1_REF, Y_dna:chromosome_chromosome:GRCh38:Y:2781480:56887902:1_REF, KI270728.1_dna:scaffold_scaffold:GRCh38:KI270728.1:1:1872759:1_REF, KI270727.1_dna:scaffold_scaffold:GRCh38:KI270727.1:1:448248:1_REF, KI270442.1_dna:scaffold_scaffold:GRCh38:KI270442.1:1:392061:1_REF, KI270729.1_dna:scaffold_scaffold:GRCh38:KI270729.1:1:280839:1_REF, GL000225.1_dna:scaffold_scaffold:GRCh38:GL000225.1:1:211173:1_REF, KI270743.1_dna:scaffold_scaffold:GRCh38:KI270743.1:1:210658:1_REF, GL000008.2_dna:scaffold_scaffold:GRCh38:GL000008.2:1:209709:1_REF, GL000009.2_dna:scaffold_scaffold:GRCh38:GL000009.2:1:201709:1_REF, KI270747.1_dna:scaffold_scaffold:GRCh38:KI270747.1:1:198735:1_REF, KI270722.1_dna:scaffold_scaffold:GRCh38:KI270722.1:1:194050:1_REF, GL000194.1_dna:scaffold_scaffold:GRCh38:GL000194.1:1:191469:1_REF, KI270742.1_dna:scaffold_scaffold:GRCh38:KI270742.1:1:186739:1_REF, GL000205.2_dna:scaffold_scaffold:GRCh38:GL000205.2:1:185591:1_REF, GL000195.1_dna:scaffold_scaffold:GRCh38:GL000195.1:1:182896:1_REF, KI270736.1_dna:scaffold_scaffold:GRCh38:KI270736.1:1:181920:1_REF, KI270733.1_dna:scaffold_scaffold:GRCh38:KI270733.1:1:179772:1_REF, GL000224.1_dna:scaffold_scaffold:GRCh38:GL000224.1:1:179693:1_REF, GL000219.1_dna:scaffold_scaffold:GRCh38:GL000219.1:1:179198:1_REF, KI270719.1_dna:scaffold_scaffold:GRCh38:KI270719.1:1:176845:1_REF, GL000216.2_dna:scaffold_scaffold:GRCh38:GL000216.2:1:176608:1_REF, KI270712.1_dna:scaffold_scaffold:GRCh38:KI270712.1:1:176043:1_REF, KI270706.1_dna:scaffold_scaffold:GRCh38:KI270706.1:1:175055:1_REF, KI270725.1_dna:scaffold_scaffold:GRCh38:KI270725.1:1:172810:1_REF, KI270744.1_dna:scaffold_scaffold:GRCh38:KI270744.1:1:168472:1_REF, KI270734.1_dna:scaffold_scaffold:GRCh38:KI270734.1:1:165050:1_REF, GL000213.1_dna:scaffold_scaffold:GRCh38:GL000213.1:1:164239:1_REF, GL000220.1_dna:scaffold_scaffold:GRCh38:GL000220.1:1:161802:1_REF, KI270715.1_dna:scaffold_scaffold:GRCh38:KI270715.1:1:161471:1_REF, GL000218.1_dna:scaffold_scaffold:GRCh38:GL000218.1:1:161147:1_REF, KI270749.1_dna:scaffold_scaffold:GRCh38:KI270749.1:1:158759:1_REF, KI270741.1_dna:scaffold_scaffold:GRCh38:KI270741.1:1:157432:1_REF, GL000221.1_dna:scaffold_scaffold:GRCh38:GL000221.1:1:155397:1_REF, KI270716.1_dna:scaffold_scaffold:GRCh38:KI270716.1:1:153799:1_REF, KI270731.1_dna:scaffold_scaffold:GRCh38:KI270731.1:1:150754:1_REF, KI270751.1_dna:scaffold_scaffold:GRCh38:KI270751.1:1:150742:1_REF, KI270750.1_dna:scaffold_scaffold:GRCh38:KI270750.1:1:148850:1_REF, KI270519.1_dna:scaffold_scaffold:GRCh38:KI270519.1:1:138126:1_REF, GL000214.1_dna:scaffold_scaffold:GRCh38:GL000214.1:1:137718:1_REF,
KI270708.1_dna:scaffold_scaffold:GRCh38:KI270708.1:1:127682:1_REF, KI270730.1_dna:scaffold_scaffold:GRCh38:KI270730.1:1:112551:1_REF, KI270438.1_dna:scaffold_scaffold:GRCh38:KI270438.1:1:112505:1_REF, KI270737.1_dna:scaffold_scaffold:GRCh38:KI270737.1:1:103838:1_REF, KI270721.1_dna:scaffold_scaffold:GRCh38:KI270721.1:1:100316:1_REF, KI270738.1_dna:scaffold_scaffold:GRCh38:KI270738.1:1:99375:1_REF, KI270748.1_dna:scaffold_scaffold:GRCh38:KI270748.1:1:93321:1_REF, KI270435.1_dna:scaffold_scaffold:GRCh38:KI270435.1:1:92983:1_REF, GL000208.1_dna:scaffold_scaffold:GRCh38:GL000208.1:1:92689:1_REF, KI270538.1_dna:scaffold_scaffold:GRCh38:KI270538.1:1:91309:1_REF, KI270756.1_dna:scaffold_scaffold:GRCh38:KI270756.1:1:79590:1_REF, KI270739.1_dna:scaffold_scaffold:GRCh38:KI270739.1:1:73985:1_REF, KI270757.1_dna:scaffold_scaffold:GRCh38:KI270757.1:1:71251:1_REF, KI270709.1_dna:scaffold_scaffold:GRCh38:KI270709.1:1:66860:1_REF, KI270746.1_dna:scaffold_scaffold:GRCh38:KI270746.1:1:66486:1_REF, KI270753.1_dna:scaffold_scaffold:GRCh38:KI270753.1:1:62944:1_REF, KI270589.1_dna:scaffold_scaffold:GRCh38:KI270589.1:1:44474:1_REF, KI270726.1_dna:scaffold_scaffold:GRCh38:KI270726.1:1:43739:1_REF, KI270735.1_dna:scaffold_scaffold:GRCh38:KI270735.1:1:42811:1_REF, KI270711.1_dna:scaffold_scaffold:GRCh38:KI270711.1:1:42210:1_REF, KI270745.1_dna:scaffold_scaffold:GRCh38:KI270745.1:1:41891:1_REF, KI270714.1_dna:scaffold_scaffold:GRCh38:KI270714.1:1:41717:1_REF, KI270732.1_dna:scaffold_scaffold:GRCh38:KI270732.1:1:41543:1_REF, KI270713.1_dna:scaffold_scaffold:GRCh38:KI270713.1:1:40745:1_REF, KI270754.1_dna:scaffold_scaffold:GRCh38:KI270754.1:1:40191:1_REF, KI270710.1_dna:scaffold_scaffold:GRCh38:KI270710.1:1:40176:1_REF, KI270717.1_dna:scaffold_scaffold:GRCh38:KI270717.1:1:40062:1_REF, KI270724.1_dna:scaffold_scaffold:GRCh38:KI270724.1:1:39555:1_REF, KI270720.1_dna:scaffold_scaffold:GRCh38:KI270720.1:1:39050:1_REF, KI270723.1_dna:scaffold_scaffold:GRCh38:KI270723.1:1:38115:1_REF, KI270718.1_dna:scaffold_scaffold:GRCh38:KI270718.1:1:38054:1_REF, KI270317.1_dna:scaffold_scaffold:GRCh38:KI270317.1:1:37690:1_REF, KI270740.1_dna:scaffold_scaffold:GRCh38:KI270740.1:1:37240:1_REF, KI270755.1_dna:scaffold_scaffold:GRCh38:KI270755.1:1:36723:1_REF, KI270707.1_dna:scaffold_scaffold:GRCh38:KI270707.1:1:32032:1_REF, KI270579.1_dna:scaffold_scaffold:GRCh38:KI270579.1:1:31033:1_REF, KI270752.1_dna:scaffold_scaffold:GRCh38:KI270752.1:1:27745:1_REF, KI270512.1_dna:scaffold_scaffold:GRCh38:KI270512.1:1:22689:1_REF, KI270322.1_dna:scaffold_scaffold:GRCh38:KI270322.1:1:21476:1_REF, GL000226.1_dna:scaffold_scaffold:GRCh38:GL000226.1:1:15008:1_REF, KI270311.1_dna:scaffold_scaffold:GRCh38:KI270311.1:1:12399:1_REF, KI270366.1_dna:scaffold_scaffold:GRCh38:KI270366.1:1:8320:1_REF, KI270511.1_dna:scaffold_scaffold:GRCh38:KI270511.1:1:8127:1_REF, KI270448.1_dna:scaffold_scaffold:GRCh38:KI270448.1:1:7992:1_REF, KI270521.1_dna:scaffold_scaffold:GRCh38:KI270521.1:1:7642:1_REF, KI270581.1_dna:scaffold_scaffold:GRCh38:KI270581.1:1:7046:1_REF, KI270582.1_dna:scaffold_scaffold:GRCh38:KI270582.1:1:6504:1_REF, KI270515.1_dna:scaffold_scaffold:GRCh38:KI270515.1:1:6361:1_REF, KI270588.1_dna:scaffold_scaffold:GRCh38:KI270588.1:1:6158:1_REF, KI270591.1_dna:scaffold_scaffold:GRCh38:KI270591.1:1:5796:1_REF, KI270522.1_dna:scaffold_scaffold:GRCh38:KI270522.1:1:5674:1_REF, KI270507.1_dna:scaffold_scaffold:GRCh38:KI270507.1:1:5353:1_REF, KI270590.1_dna:scaffold_scaffold:GRCh38:KI270590.1:1:4685:1_REF, KI270584.1_dna:scaffold_scaffold:GRCh38:KI270584.1:1:4513:1_REF, KI270320.1_dna:scaffold_scaffold:GRCh38:KI270320.1:1:4416:1_REF, KI270382.1_dna:scaffold_scaffold:GRCh38:KI270382.1:1:4215:1_REF, KI270468.1_dna:scaffold_scaffold:GRCh38:KI270468.1:1:4055:1_REF, KI270467.1_dna:scaffold_scaffold:GRCh38:KI270467.1:1:3920:1_REF, KI270362.1_dna:scaffold_scaffold:GRCh38:KI270362.1:1:3530:1_REF, KI270517.1_dna:scaffold_scaffold:GRCh38:KI270517.1:1:3253:1_REF, KI270593.1_dna:scaffold_scaffold:GRCh38:KI270593.1:1:3041:1_REF, KI270528.1_dna:scaffold_scaffold:GRCh38:KI270528.1:1:2983:1_REF,
KI270587.1_dna:scaffold_scaffold:GRCh38:KI270587.1:1:2969:1_REF, KI270364.1_dna:scaffold_scaffold:GRCh38:KI270364.1:1:2855:1_REF, KI270371.1_dna:scaffold_scaffold:GRCh38:KI270371.1:1:2805:1_REF, KI270333.1_dna:scaffold_scaffold:GRCh38:KI270333.1:1:2699:1_REF, KI270374.1_dna:scaffold_scaffold:GRCh38:KI270374.1:1:2656:1_REF, KI270411.1_dna:scaffold_scaffold:GRCh38:KI270411.1:1:2646:1_REF, KI270414.1_dna:scaffold_scaffold:GRCh38:KI270414.1:1:2489:1_REF, KI270510.1_dna:scaffold_scaffold:GRCh38:KI270510.1:1:2415:1_REF, KI270390.1_dna:scaffold_scaffold:GRCh38:KI270390.1:1:2387:1_REF, KI270375.1_dna:scaffold_scaffold:GRCh38:KI270375.1:1:2378:1_REF, KI270420.1_dna:scaffold_scaffold:GRCh38:KI270420.1:1:2321:1_REF, KI270509.1_dna:scaffold_scaffold:GRCh38:KI270509.1:1:2318:1_REF, KI270315.1_dna:scaffold_scaffold:GRCh38:KI270315.1:1:2276:1_REF, KI270302.1_dna:scaffold_scaffold:GRCh38:KI270302.1:1:2274:1_REF, KI270518.1_dna:scaffold_scaffold:GRCh38:KI270518.1:1:2186:1_REF, KI270530.1_dna:scaffold_scaffold:GRCh38:KI270530.1:1:2168:1_REF, KI270304.1_dna:scaffold_scaffold:GRCh38:KI270304.1:1:2165:1_REF, KI270418.1_dna:scaffold_scaffold:GRCh38:KI270418.1:1:2145:1_REF, KI270424.1_dna:scaffold_scaffold:GRCh38:KI270424.1:1:2140:1_REF, KI270417.1_dna:scaffold_scaffold:GRCh38:KI270417.1:1:2043:1_REF, KI270508.1_dna:scaffold_scaffold:GRCh38:KI270508.1:1:1951:1_REF, KI270303.1_dna:scaffold_scaffold:GRCh38:KI270303.1:1:1942:1_REF, KI270381.1_dna:scaffold_scaffold:GRCh38:KI270381.1:1:1930:1_REF, KI270529.1_dna:scaffold_scaffold:GRCh38:KI270529.1:1:1899:1_REF, KI270425.1_dna:scaffold_scaffold:GRCh38:KI270425.1:1:1884:1_REF, KI270396.1_dna:scaffold_scaffold:GRCh38:KI270396.1:1:1880:1_REF, KI270363.1_dna:scaffold_scaffold:GRCh38:KI270363.1:1:1803:1_REF, KI270386.1_dna:scaffold_scaffold:GRCh38:KI270386.1:1:1788:1_REF, KI270465.1_dna:scaffold_scaffold:GRCh38:KI270465.1:1:1774:1_REF, KI270383.1_dna:scaffold_scaffold:GRCh38:KI270383.1:1:1750:1_REF, KI270384.1_dna:scaffold_scaffold:GRCh38:KI270384.1:1:1658:1_REF, KI270330.1_dna:scaffold_scaffold:GRCh38:KI270330.1:1:1652:1_REF, KI270372.1_dna:scaffold_scaffold:GRCh38:KI270372.1:1:1650:1_REF, KI270548.1_dna:scaffold_scaffold:GRCh38:KI270548.1:1:1599:1_REF, KI270580.1_dna:scaffold_scaffold:GRCh38:KI270580.1:1:1553:1_REF, KI270387.1_dna:scaffold_scaffold:GRCh38:KI270387.1:1:1537:1_REF, KI270391.1_dna:scaffold_scaffold:GRCh38:KI270391.1:1:1484:1_REF, KI270305.1_dna:scaffold_scaffold:GRCh38:KI270305.1:1:1472:1_REF, KI270373.1_dna:scaffold_scaffold:GRCh38:KI270373.1:1:1451:1_REF, KI270422.1_dna:scaffold_scaffold:GRCh38:KI270422.1:1:1445:1_REF, KI270316.1_dna:scaffold_scaffold:GRCh38:KI270316.1:1:1444:1_REF, KI270340.1_dna:scaffold_scaffold:GRCh38:KI270340.1:1:1428:1_REF, KI270338.1_dna:scaffold_scaffold:GRCh38:KI270338.1:1:1428:1_REF, KI270583.1_dna:scaffold_scaffold:GRCh38:KI270583.1:1:1400:1_REF, KI270334.1_dna:scaffold_scaffold:GRCh38:KI270334.1:1:1368:1_REF, KI270429.1_dna:scaffold_scaffold:GRCh38:KI270429.1:1:1361:1_REF, KI270393.1_dna:scaffold_scaffold:GRCh38:KI270393.1:1:1308:1_REF, KI270516.1_dna:scaffold_scaffold:GRCh38:KI270516.1:1:1300:1_REF, KI270389.1_dna:scaffold_scaffold:GRCh38:KI270389.1:1:1298:1_REF, KI270466.1_dna:scaffold_scaffold:GRCh38:KI270466.1:1:1233:1_REF, KI270388.1_dna:scaffold_scaffold:GRCh38:KI270388.1:1:1216:1_REF, KI270544.1_dna:scaffold_scaffold:GRCh38:KI270544.1:1:1202:1_REF, KI270310.1_dna:scaffold_scaffold:GRCh38:KI270310.1:1:1201:1_REF, KI270412.1_dna:scaffold_scaffold:GRCh38:KI270412.1:1:1179:1_REF, KI270395.1_dna:scaffold_scaffold:GRCh38:KI270395.1:1:1143:1_REF, KI270376.1_dna:scaffold_scaffold:GRCh38:KI270376.1:1:1136:1_REF, KI270337.1_dna:scaffold_scaffold:GRCh38:KI270337.1:1:1121:1_REF, KI270335.1_dna:scaffold_scaffold:GRCh38:KI270335.1:1:1048:1_REF, KI270378.1_dna:scaffold_scaffold:GRCh38:KI270378.1:1:1048:1_REF, KI270379.1_dna:scaffold_scaffold:GRCh38:KI270379.1:1:1045:1_REF, KI270329.1_dna:scaffold_scaffold:GRCh38:KI270329.1:1:1040:1_REF, KI270419.1_dna:scaffold_scaffold:GRCh38:KI270419.1:1:1029:1_REF, KI270336.1_dna:scaffold_scaffold:GRCh38:KI270336.1:1:1026:1_REF,
KI270312.1_dna:scaffold_scaffold:GRCh38:KI270312.1:1:998:1_REF, KI270539.1_dna:scaffold_scaffold:GRCh38:KI270539.1:1:993:1_REF, KI270385.1_dna:scaffold_scaffold:GRCh38:KI270385.1:1:990:1_REF, KI270423.1_dna:scaffold_scaffold:GRCh38:KI270423.1:1:981:1_REF, KI270392.1_dna:scaffold_scaffold:GRCh38:KI270392.1:1:971:1_REF, KI270394.1_dna:scaffold_scaffold:GRCh38:KI270394.1:1:970:1_REF]
[INFO] MethylationAnalysis: GATK: ##### ERROR reference contigs = [1, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 2, 20, 21, 22, 3, 4, 5, 6, 7, 8, 9, MT, X, Y, KI270728.1, KI270727.1, KI270442.1, KI270729.1, GL000225.1, KI270743.1, GL000008.2, GL000009.2, KI270747.1, KI270722.1, GL000194.1, KI270742.1, GL000205.2, GL000195.1, KI270736.1, KI270733.1, GL000224.1, GL000219.1, KI270719.1, GL000216.2, KI270712.1, KI270706.1, KI270725.1, KI270744.1, KI270734.1, GL000213.1, GL000220.1, KI270715.1, GL000218.1, KI270749.1, KI270741.1, GL000221.1, KI270716.1, KI270731.1, KI270751.1, KI270750.1, KI270519.1, GL000214.1, KI270708.1, KI270730.1, KI270438.1, KI270737.1, KI270721.1, KI270738.1, KI270748.1, KI270435.1, GL000208.1, KI270538.1, KI270756.1, KI270739.1, KI270757.1, KI270709.1, KI270746.1, KI270753.1, KI270589.1, KI270726.1, KI270735.1, KI270711.1, KI270745.1, KI270714.1, KI270732.1, KI270713.1, KI270754.1, KI270710.1, KI270717.1, KI270724.1, KI270720.1, KI270723.1, KI270718.1, KI270317.1, KI270740.1, KI270755.1, KI270707.1, KI270579.1, KI270752.1, KI270512.1, KI270322.1, GL000226.1, KI270311.1, KI270366.1, KI270511.1, KI270448.1, KI270521.1, KI270581.1, KI270582.1, KI270515.1, KI270588.1, KI270591.1, KI270522.1, KI270507.1, KI270590.1, KI270584.1, KI270320.1, KI270382.1, KI270468.1, KI270467.1, KI270362.1, KI270517.1, KI270593.1, KI270528.1, KI270587.1, KI270364.1, KI270371.1, KI270333.1, KI270374.1, KI270411.1, KI270414.1, KI270510.1, KI270390.1, KI270375.1, KI270420.1, KI270509.1, KI270315.1, KI270302.1, KI270518.1, KI270530.1, KI270304.1, KI270418.1, KI270424.1, KI270417.1, KI270508.1, KI270303.1, KI270381.1, KI270529.1, KI270425.1, KI270396.1, KI270363.1, KI270386.1, KI270465.1, KI270383.1, KI270384.1, KI270330.1, KI270372.1, KI270548.1, KI270580.1, KI270387.1, KI270391.1, KI270305.1, KI270373.1, KI270422.1, KI270316.1, KI270340.1, KI270338.1, KI270583.1, KI270334.1, KI270429.1, KI270393.1, KI270516.1, KI270389.1, KI270466.1, KI270388.1, KI270544.1, KI270310.1, KI270412.1, KI270395.1, KI270376.1, KI270337.1, KI270335.1, KI270378.1, KI270379.1, KI270329.1, KI270419.1, KI270336.1, KI270312.1, KI270539.1, KI270385.1, KI270423.1, KI270392.1, KI270394.1]
[INFO] MethylationAnalysis: GATK: ##### ERROR ------------------------------------------------------------------------------------------
[INFO] MethylationAnalysis: Methylation analysis of sample smalls OK
My theory is that the problem is because it didn't manage to align anything with the ".bam" files, mainly because of what I get when I run this code:
(base) oscar@oscar-OptiPlex-7090:~/Escritorio/Documentos/Pbic1/data/myproject/output$ samtools view -c -F 260 bisulfited_CT_smalls_against_hg38.fa_WATSON.sam.sorted.sam.bam
0
(base) oscar@oscar-OptiPlex-7090:~/Escritorio/Documentos/Pbic1/data/myproject/output$ samtools view -c -F 260 bisulfited_CT_smalls_against_hg38.fa_CRICK.sam.sorted.sam.bam
0
Maybe the problem is because the files I have been given are not of high enough quality, but then I don't understand why it has generated ".bam" files in the first place (and the weirdest thing is that these files are not 0 B but 7,3 kB in size).
What do you think is the problem?
Thank you very much in advance and sorry for this first long query, but I've been trying for a few weeks now and I don't know what to do.
Hi there,
Thanks for keeping up with my questions. As bicycle is able to from differential analysis between two different groups i.e treatment vs control. I wanted to know if bicycle can perform commonly methylated CpG shores, CPG islands, CpG shelves and promoter regions among a group of samples i.e control samples ?
Many thanks
Hello guys,
I am running bicycle analyze-differential-methylation to get differential methylation profiles for some regions of interests. Everything went OK until I run analyze-differential-methylation, I got the following exception:
SEVERE: Error during execution
java.lang.NullPointerException
at es.cnio.bioinfo.bicycle.gatk.GPFilesReader.readLine(GPFilesReader.java:85)
at es.cnio.bioinfo.bicycle.operations.DifferentialMethylationAnalysis.analyzeDifferentialMethylationByBase(DifferentialMethylationAnalysis.java:360)
at es.cnio.bioinfo.bicycle.cli.DifferentialMethylationAnalysisCommand.executeImpl(DifferentialMethylationAnalysisCommand.java:95)
at es.cnio.bioinfo.bicycle.cli.ProjectCommand.execute(ProjectCommand.java:52)
at es.cnio.bioinfo.bicycle.cli.CLIApplication.run(CLIApplication.java:86)
at es.cnio.bioinfo.bicycle.cli.Main.main(Main.java:27)
java.lang.NullPointerException
at es.cnio.bioinfo.bicycle.gatk.GPFilesReader.readLine(GPFilesReader.java:85)
at es.cnio.bioinfo.bicycle.operations.DifferentialMethylationAnalysis.analyzeDifferentialMethylationByBase(DifferentialMethylationAnalysis.java:360)
at es.cnio.bioinfo.bicycle.cli.DifferentialMethylationAnalysisCommand.executeImpl(DifferentialMethylationAnalysisCommand.java:95)
at es.cnio.bioinfo.bicycle.cli.ProjectCommand.execute(ProjectCommand.java:52)
at es.cnio.bioinfo.bicycle.cli.CLIApplication.run(CLIApplication.java:86)
at es.cnio.bioinfo.bicycle.cli.Main.main(Main.java:27)
Any idea what could be causing such an error?
Thank you in advance.
Hi there,
This is my first time using bicycle and i noticed with i align with more than three threads -t 4 i get a java error
Exception in thread "Thread-18" [INFO] BowtieAlignment: Start read feeding to alignment against workingDirectory/ucsc.hg19.fa_bisulfited_GA. Log file: output/bisulfited_CT_8209_against_ucsc.hg19.fa_CRICK.sam_p_1.log java.lang.RuntimeException: java.lang.StringIndexOutOfBoundsException: String index out of range: -1 at es.cnio.bioinfo.bicycle.operations.BowtieAlignment$1AlignerThread$1.run(BowtieAlignment.java:786) Caused by: java.lang.StringIndexOutOfBoundsException: String index out of range: -1 at java.lang.String.substring(String.java:1931)
Nevertheless, the mapping keep going but it get stuck in the end without moving to the next sample.
any suggestions of what might be going wrong ?
Thanks
Hi there,
I wanted to ask a question regarding differential DMR analysis is there a way to get the annotation for hg19. I do have the Illumina manifest files
one bed file with this structure:
chr1 17363 17575 chr1_17364-17575 chr1 91548 91553 chr1_91549-91553
And another txt file with this structure:
Chr Start Stop UCSC_CpG_Islands_Name Relation_to_UCSC_CpG_Island chr1 17363 17575 chr1 91548 91553 chr1 91570 91587 chr1 129279 129380 chr1 135141 135255 chr1:135124-135563 Island
based on the case study demo analysis, I see some gene names. could you direct me how to get annotation file (hg19) to include for the analysis ?
Potentially reference-bisulfitation will have the same problem, but with gzipped fastas?
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