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CDK12/CDK13 inhibition disrupts transcriptional elongation and replication fork progression in glioblastoma.

Code ↔ Paper

3 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 3 matches
  1. [1] § Methods › SLAM-seq data processing ↔ slamdunk/slamdunk.py, lines 376 to 432 · score 0.63 · SLAMdunk, variant fraction, trimmed, quality, bp, alignment · Report a mismatch
  2. [2] § Methods › SLAM-seq data processing ↔ slamdunk/dunks/filter.py, lines 213 to 315 · score 0.57 · retention strategy, quality, alignment, SlamDunk, filtering, mapping · Report a mismatch
  3. [3] § Methods › Cut&Run data processing ↔ slamdunk/dunks/simulator.py, lines 304 to 372 · score 0.52 · samtools view Sb, mapping, sequenced · Report a mismatch

Paper

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The authors' code

Python · 527 lines · 27 KB · AGPL-3.0 · 1 match

  1. #!/usr/bin/env python
  3. # Copyright (c) 2015 Tobias Neumann, Philipp Rescheneder.
  4. #
  5. # This file is part of Slamdunk.
  6. #
  7. # Slamdunk is free software: you can redistribute it and/or modify
  8. # it under the terms of the GNU Affero General Public License as
  9. # published by the Free Software Foundation, either version 3 of the
  10. # License, or (at your option) any later version.
  11. #
  12. # Slamdunk is distributed in the hope that it will be useful,
  13. # but WITHOUT ANY WARRANTY; without even the implied warranty of
  14. # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15. # GNU Affero General Public License for more details.
  16. #
  17. # You should have received a copy of the GNU Affero General Public License
  18. # along with this program. If not, see <http://www.gnu.org/licenses/>.
  20. #########################################################################
  21. # Main routine for the SLAMdunk analyzer
  22. #########################################################################
  23. # Imports
  24. #########################################################################
  25. from __future__ import print_function
  26. import sys, os, random
  28. from time import sleep
  29. from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter, SUPPRESS
  31. from os.path import basename
  33. from joblib import Parallel, delayed
  34. from slamdunk.dunks import tcounter, mapper, filter, deduplicator, snps
  35. from slamdunk.utils.misc import replaceExtension, estimateMaxReadLength
  36. from slamdunk.version import __version__
  38. ########################################################################
  39. # Global variables
  40. ########################################################################
  42. printOnly = False
  43. verbose = False
  45. mainOutput = sys.stderr
  47. logToMainOutput = False
  49. ########################################################################
  50. # Routine definitions
  51. ########################################################################
  53. def getLogFile(path):
  54. if(logToMainOutput):
  55. return mainOutput
  56. else:
  57. log = open(path, "a")
  58. return log
  60. def closeLogFile(log):
  61. if(not logToMainOutput):
  62. log.close()
  64. def message(msg):
  65. print(msg, file=mainOutput)
  67. def error(msg, code=-1):
  68. print(msg, file=mainOutput)
  69. sys.exit(code)
  71. def stepFinished():
  72. print(".", end="", file=mainOutput)
  74. def dunkFinished():
  75. print("", file=mainOutput)
  77. def createDir(directory):
  78. if not os.path.exists(directory):
  79. message("Creating output directory: " + directory)
  80. os.makedirs(directory)
  82. def readSampleFile(fileName):
  83. samples = []
  84. infos = []
  86. with open(fileName, "r") as ins:
  87. for line in ins:
  88. line = line.strip()
  89. if(len(line) > 1):
  90. if(fileName.endswith(".tsv")):
  91. cols = line.split("\t")
  92. elif(fileName.endswith(".csv")):
  93. cols = line.split(",")
  94. else:
  95. raise RuntimeError("Unknown file extension found: " + fileName)
  96. if(len(cols) < 4):
  97. raise RuntimeError("Invalid sample file found: " + fileName)
  98. samples.append(cols[0])
  99. infos.append(cols[1] + ":" + cols[2] + ":" + cols[3])
  101. return samples, infos
  103. def getSamples(bams, runOnly=-1):
  104. samples = []
  105. samplesInfos = []
  106. if len(bams) == 1 and (bams[0].endswith(".tsv") or bams[0].endswith(".csv")):
  107. # Sample file specified
  108. samples, samplesInfos = readSampleFile(bams[0])
  109. else:
  110. # List of BAM files specified
  111. samples = bams
  112. samplesInfos = [""] * len(samples)
  114. if(runOnly > 0):
  115. if(runOnly > len(samples)):
  116. raise RuntimeError("Sample index out of range. " + str(runOnly) + " > " + str(len(samples)) + ". Check -i/--sample-index")
  117. message("Running only job " + str(runOnly))
  118. samples = [ samples[runOnly - 1] ]
  119. samplesInfos = [ samplesInfos[runOnly - 1] ]
  120. elif(runOnly == 0):
  121. raise RuntimeError("Sample index (" + str(runOnly) + ") out of range. Starts with 1. Check -i/--sample-index")
  123. return samples, samplesInfos
  125. def runMap(tid, inputBAM, referenceFile, threads, trim5p, maxPolyA, quantseqMapping, endtoendMapping, topn, sampleDescription, outputDirectory, skipSAM) :
  126. if skipSAM:
  127. outputSAM = os.path.join(outputDirectory, replaceExtension(basename(inputBAM), ".bam", "_slamdunk_mapped"))
  128. else:
  129. outputSAM = os.path.join(outputDirectory, replaceExtension(basename(inputBAM), ".sam", "_slamdunk_mapped"))
  130. outputLOG = os.path.join(outputDirectory, replaceExtension(basename(inputBAM), ".log", "_slamdunk_mapped"))
  132. #sampleName = "sample_" + str(tid)
  133. sampleName = replaceExtension(basename(inputBAM), ".bam", "")
  134. sampleType = "NA"
  135. sampleTime = "-1"
  136. if(sampleDescription != ""):
  137. sampleDescriptions = sampleDescription.split(":")
  138. if(len(sampleDescriptions) >= 1):
  139. sampleName = sampleDescriptions[0]
  140. if(len(sampleDescriptions) >= 2):
  141. typeDict = { 'p': 'pulse', 'c':'chase', 'pulse':'pulse', 'chase':'chase', '':'NA'}
  142. if sampleDescriptions[1] in typeDict:
  143. sampleType = typeDict[sampleDescriptions[1]]
  144. else:
  145. sampleType = sampleDescriptions[1]
  146. if(len(sampleDescriptions) >= 3):
  147. sampleTime = sampleDescriptions[2]
  149. mapper.Map(inputBAM, referenceFile, outputSAM, getLogFile(outputLOG), quantseqMapping, endtoendMapping, threads=threads, trim5p=trim5p, maxPolyA=maxPolyA, topn=topn, sampleId=tid, sampleName=sampleName, sampleType=sampleType, sampleTime=sampleTime, printOnly=printOnly, verbose=verbose)
  150. stepFinished()
  152. def runSam2Bam(tid, bam, threads, outputDirectory):
  153. inputSAM = os.path.join(outputDirectory, replaceExtension(basename(bam), ".sam", "_slamdunk_mapped"))
  154. outputBAM = os.path.join(outputDirectory, replaceExtension(basename(bam), ".bam", "_slamdunk_mapped"))
  155. outputLOG = os.path.join(outputDirectory, replaceExtension(basename(bam), ".log", "_slamdunk_mapped"))
  156. mapper.sort(inputSAM, outputBAM, getLogFile(outputLOG), threads, False, printOnly, verbose)
  157. stepFinished()
  159. def runDedup(tid, bam, outputDirectory) :
  160. outputBAM = os.path.join(outputDirectory, replaceExtension(basename(bam), ".bam", "_dedup"))
  161. outputLOG = os.path.join(outputDirectory, replaceExtension(basename(bam), ".log", "_dedup"))
  162. log = getLogFile(outputLOG)
  163. deduplicator.Dedup(bam, outputBAM, log)
  164. closeLogFile(log)
  165. stepFinished()
  167. def runFilter(tid, bam, bed, mq, minIdentity, maxNM, outputDirectory):
  168. outputBAM = os.path.join(outputDirectory, replaceExtension(basename(bam), ".bam", "_filtered"))
  169. outputLOG = os.path.join(outputDirectory, replaceExtension(basename(bam), ".log", "_filtered"))
  170. filter.Filter(bam, outputBAM, getLogFile(outputLOG), bed, mq, minIdentity, maxNM, printOnly, verbose)
  171. stepFinished()
  173. def runSnp(tid, referenceFile, minCov, minVarFreq, minQual, inputBAM, outputDirectory) :
  174. outputSNP = os.path.join(outputDirectory, replaceExtension(basename(inputBAM), ".vcf", "_snp"))
  175. outputLOG = os.path.join(outputDirectory, replaceExtension(basename(inputBAM), ".log", "_snp"))
  176. snps.SNPs(inputBAM, outputSNP, referenceFile, minVarFreq, minCov, minQual, getLogFile(outputLOG), printOnly, verbose, False)
  177. stepFinished()
  179. def runCount(tid, bam, ref, bed, maxLength, minQual, conversionThreshold, outputDirectory, snpDirectory, vcfFile) :
  180. outputCSV = os.path.join(outputDirectory, replaceExtension(basename(bam), ".tsv", "_tcount"))
  181. outputBedgraphPlus = os.path.join(outputDirectory, replaceExtension(basename(bam), ".bedgraph", "_tcount_plus"))
  182. outputBedgraphMinus = os.path.join(outputDirectory, replaceExtension(basename(bam), ".bedgraph", "_tcount_mins"))
  183. outputLOG = os.path.join(outputDirectory, replaceExtension(basename(bam), ".log", "_tcount"))
  185. if (vcfFile != None) :
  186. inputSNP = vcfFile
  187. elif(snpDirectory != None):
  188. inputSNP = os.path.join(snpDirectory, replaceExtension(basename(bam), ".vcf", "_snp"))
  189. else:
  190. inputSNP = None
  192. if (maxLength == None) :
  193. maxLength = estimateMaxReadLength(bam)
  194. if (maxLength < 0) :
  195. print("Difference between minimum and maximum read length is > 10. Please specify --max-read-length parameter.")
  196. sys.exit(0)
  198. log = getLogFile(outputLOG)
  200. print("Using " + str(maxLength) + " as maximum read length.",file=log)
  202. tcounter.computeTconversions(ref, bed, inputSNP, bam, maxLength, minQual, outputCSV, outputBedgraphPlus, outputBedgraphMinus, conversionThreshold, log)
  203. stepFinished()
  204. return outputCSV
  206. def runAll(args) :
  207. message("slamdunk all")
  209. if args.sampleIndex > -1:
  210. sec = random.randrange(200,2000) / 1000.0
  211. message("Waiting " + str(sec) + " seconds")
  212. sleep(sec)
  214. # Setup slamdunk run folder
  216. outputDirectory = args.outputDir
  217. createDir(outputDirectory)
  219. n = args.threads
  220. referenceFile = args.referenceFile
  222. # Run mapper dunk
  224. dunkPath = os.path.join(outputDirectory, "map")
  225. createDir(dunkPath)
  227. samples, samplesInfos = getSamples(args.files, runOnly=args.sampleIndex)
  229. message("Running slamDunk map for " + str(len(samples)) + " files (" + str(n) + " threads)")
  231. for i in range(0, len(samples)):
  232. bam = samples[i]
  234. if not args.sampleName or len(samples) > 1:
  235. sampleName = replaceExtension(basename(bam), "", "")
  236. else :
  237. sampleName = args.sampleName
  239. sampleInfo = samplesInfos[i]
  240. if sampleInfo == "":
  241. sampleInfo = sampleName + ":" + args.sampleType + ":" + str(args.sampleTime)
  242. tid = i
  243. if args.sampleIndex > -1:
  244. tid = args.sampleIndex
  245. runMap(tid, bam, referenceFile, n, args.trim5, args.maxPolyA, args.quantseq, args.endtoend, args.topn, sampleInfo, dunkPath, args.skipSAM)
  247. dunkFinished()
  249. if(not args.skipSAM):
  250. message("Running slamDunk sam2bam for " + str(len(samples)) + " files (" + str(n) + " threads)")
  251. results = Parallel(n_jobs=1, verbose=verbose)(delayed(runSam2Bam)(tid, samples[tid], n, dunkPath) for tid in range(0, len(samples)))
  252. dunkFinished()
  254. dunkbufferIn = []
  256. for file in samples :
  257. dunkbufferIn.append(os.path.join(dunkPath, replaceExtension(basename(file), ".bam", "_slamdunk_mapped")))
  259. # Run filter dunk
  261. bed = args.bed
  263. if args.filterbed:
  264. bed = args.filterbed
  265. args.multimap = True
  267. if (not args.multimap) :
  268. bed = None
  270. dunkPath = os.path.join(outputDirectory, "filter")
  271. createDir(dunkPath)
  273. message("Running slamDunk filter for " + str(len(samples)) + " files (" + str(n) + " threads)")
  274. results = Parallel(n_jobs=n, verbose=verbose)(delayed(runFilter)(tid, dunkbufferIn[tid], bed, args.mq, args.identity, args.nm, dunkPath) for tid in range(0, len(samples)))
  276. dunkFinished()
  278. # Run filter dunk
  280. dunkbufferOut = []
  282. for file in dunkbufferIn :
  283. dunkbufferOut.append(os.path.join(dunkPath, replaceExtension(basename(file), ".bam", "_filtered")))
  285. dunkbufferIn = dunkbufferOut
  287. dunkbufferOut = []
  289. dunkFinished()
  291. # Run snps dunk only if vcf not specified
  293. snpDirectory = None
  294. vcfFile = None
  296. if not "vcfFile" in args:
  298. dunkPath = os.path.join(outputDirectory, "snp")
  299. createDir(dunkPath)
  301. minCov = args.cov
  302. minVarFreq = args.var
  304. snpThread = n
  305. if(snpThread > 1):
  306. snpThread = int(snpThread / 2)
  308. #if (args.minQual == 0) :
  309. # snpqual = 13
  310. #else :
  311. snpqual = args.minQual
  313. message("Running slamDunk SNP for " + str(len(samples)) + " files (" + str(snpThread) + " threads)")
  314. results = Parallel(n_jobs=snpThread, verbose=verbose)(delayed(runSnp)(tid, referenceFile, minCov, minVarFreq, snpqual, dunkbufferIn[tid], dunkPath) for tid in range(0, len(samples)))
  316. snpDirectory = os.path.join(outputDirectory, "snp")
  318. dunkFinished()
  319. else :
  320. vcfFile = args.vcfFile
  322. # Run count dunk
  324. dunkPath = os.path.join(outputDirectory, "count")
  325. createDir(dunkPath)
  327. message("Running slamDunk tcount for " + str(len(samples)) + " files (" + str(n) + " threads)")
  328. results = Parallel(n_jobs=n, verbose=verbose)(delayed(runCount)(tid, dunkbufferIn[tid], referenceFile, args.bed, args.maxLength, args.minQual, args.conversionThreshold, dunkPath, snpDirectory, vcfFile) for tid in range(0, len(samples)))
  330. dunkFinished()
  332. def run():
  333. ########################################################################
  334. # Argument parsing
  335. ########################################################################
  337. # Info
  338. usage = "SLAMdunk software for analyzing SLAM-seq data"
  340. # Main Parsers
  341. parser = ArgumentParser(description=usage, formatter_class=ArgumentDefaultsHelpFormatter)
  342. parser.add_argument('--version', action='version', version='%(prog)s ' + __version__)
  344. # Initialize Subparsers
  345. subparsers = parser.add_subparsers(help="", dest="command")
  347. # map command
  349. mapparser = subparsers.add_parser('map', help='Map SLAM-seq read data', formatter_class=ArgumentDefaultsHelpFormatter)
  350. mapparser.add_argument('files', action='store', help='Single csv/tsv file (recommended) containing all sample files and sample info or a list of all sample BAM/FASTA(gz)/FASTQ(gz) files' , nargs="+")
  351. mapparser.add_argument("-r", "--reference", type=str, required=True, dest="referenceFile", default=SUPPRESS, help="Reference fasta file")
  352. mapparser.add_argument("-o", "--outputDir", type=str, required=True, dest="outputDir", default=SUPPRESS, help="Output directory for mapped BAM files.")
  353. mapparser.add_argument("-5", "--trim-5p", type=int, required=False, dest="trim5", default=12, help="Number of bp removed from 5' end of all reads.")
  354. mapparser.add_argument("-n", "--topn", type=int, required=False, dest="topn", default=1, help="Max. number of alignments to report per read")
  355. mapparser.add_argument("-a", "--max-polya", type=int, required=False, dest="maxPolyA", default=4, help="Max number of As at the 3' end of a read.")
  356. mapparser.add_argument("-t", "--threads", type=int, required=False, dest="threads", default = 1, help="Thread number")
  357. mapparser.add_argument("-q", "--quantseq", dest="quantseq", action='store_true', required=False, help="Run plain Quantseq alignment without SLAM-seq scoring")
  358. mapparser.add_argument('-e', "--endtoend", action='store_true', dest="endtoend", help="Use a end to end alignment algorithm for mapping.")
  359. mapparser.add_argument('-sn', "--sampleName", type=str, dest="sampleName", required = False, help="Use this sample name for all supplied samples")
  360. mapparser.add_argument('-sy', "--sampleType", type=str, dest="sampleType", required = False, default = "pulse", help="Use this sample type for all supplied samples")
  361. mapparser.add_argument('-st', "--sampleTime", type=int, dest="sampleTime", required = False, default = 0, help="Use this sample time for all supplied samples")
  362. mapparser.add_argument("-i", "--sample-index", type=int, required=False, default=-1, dest="sampleIndex", help="Run analysis only for sample <i>. Use for distributing slamdunk analysis on a cluster (index is 1-based).")
  363. mapparser.add_argument('-ss', "--skip-sam", action='store_true', dest="skipSAM", help="Output BAM while mapping. Slower but, uses less hard disk.")
  365. # filter command
  367. filterparser = subparsers.add_parser('filter', help='Filter SLAM-seq aligned data')
  368. filterparser.add_argument('bam', action='store', help='Bam file(s)' , nargs="+")
  369. filterparser.add_argument("-o", "--outputDir", type=str, required=True, dest="outputDir", help="Output directory for mapped BAM files.")
  370. filterparser.add_argument("-b", "--bed", type=str, required=False, dest="bed", help="BED file, overrides MQ filter to 0")
  371. filterparser.add_argument("-mq", "--min-mq", type=int, required=False, default=2, dest="mq", help="Minimum mapping quality (default: %(default)d)")
  372. filterparser.add_argument("-mi", "--min-identity", type=float, required=False, default=0.95, dest="identity", help="Minimum alignment identity (default: %(default)s)")
  373. filterparser.add_argument("-nm", "--max-nm", type=int, required=False, default=-1, dest="nm", help="Maximum NM for alignments (default: %(default)d)")
  374. filterparser.add_argument("-t", "--threads", type=int, required=False, dest="threads", default=1, help="Thread number (default: %(default)d)")
  376. # snp command
  378. snpparser = subparsers.add_parser('snp', help='Call SNPs on SLAM-seq aligned data', formatter_class=ArgumentDefaultsHelpFormatter)
  379. snpparser.add_argument('bam', action='store', help='Bam file(s)' , nargs="+")
  380. snpparser.add_argument("-o", "--outputDir", type=str, required=True, dest="outputDir", default=SUPPRESS, help="Output directory for mapped BAM files.")
  381. snpparser.add_argument("-r", "--reference", required=True, dest="fasta", type=str, default=SUPPRESS, help="Reference fasta file")
  382. snpparser.add_argument("-c", "--min-coverage", required=False, dest="cov", type=int, help="Minimimum coverage to call variant", default=10)
  383. #snpparser.add_argument("-q", "--min-base-qual", type=int, default=13, required=False, dest="minQual", help="Min base quality for T -> C conversions (default: %(default)d)")
  384. snpparser.add_argument("-f", "--var-fraction", required=False, dest="var", type=float, help="Minimimum variant fraction to call variant", default=0.8)
  385. snpparser.add_argument("-t", "--threads", type=int, required=False, default=1, dest="threads", help="Thread number")
  387. # count command
  389. countparser = subparsers.add_parser('count', help='Count T/C conversions in SLAM-seq aligned data')
  390. countparser.add_argument('bam', action='store', help='Bam file(s)' , nargs="+")
  391. countparser.add_argument("-o", "--outputDir", type=str, required=True, dest="outputDir", default=SUPPRESS, help="Output directory for mapped BAM files.")
  392. countparser.add_argument("-s", "--snp-directory", type=str, required=False, dest="snpDir", default=SUPPRESS, help="Directory containing SNP files.")
  393. countparser.add_argument("-v", "--vcf", type=str, required=False, dest="vcfFile", default=SUPPRESS, help="Externally provided custom variant file.")
  394. countparser.add_argument("-r", "--reference", type=str, required=True, dest="ref", default=SUPPRESS, help="Reference fasta file")
  395. countparser.add_argument("-b", "--bed", type=str, required=True, dest="bed", default=SUPPRESS, help="BED file")
  396. countparser.add_argument("-c", "--conversion-threshold", type=int, dest="conversionThreshold", required=False, default=1,help="Number of T>C conversions required to count read as T>C read (default: %(default)d)")
  397. countparser.add_argument("-l", "--max-read-length", type=int, required=False, dest="maxLength", help="Max read length in BAM file")
  398. countparser.add_argument("-q", "--min-base-qual", type=int, default=27, required=False, dest="minQual", help="Min base quality for T -> C conversions (default: %(default)d)")
  399. countparser.add_argument("-t", "--threads", type=int, required=False, default=1, dest="threads", help="Thread number (default: %(default)d)")
  402. # all command
  404. allparser = subparsers.add_parser('all', help='Run entire SLAMdunk analysis')
  405. allparser.add_argument('files', action='store', help='Single csv/tsv file (recommended) containing all sample files and sample info or a list of all sample BAM/FASTA(gz)/FASTQ(gz) files' , nargs="+")
  406. allparser.add_argument("-r", "--reference", type=str, required=True, dest="referenceFile", help="Reference fasta file")
  407. allparser.add_argument("-b", "--bed", type=str, required=True, dest="bed", help="BED file with 3'UTR coordinates")
  408. allparser.add_argument("-fb", "--filterbed", type=str, required=False, dest="filterbed", help="BED file with 3'UTR coordinates to filter multimappers (activates -m)")
  409. allparser.add_argument("-v", "--vcf", type=str, required=False, dest="vcfFile", default=SUPPRESS, help="Skip SNP step and provide custom variant file.")
  410. allparser.add_argument("-o", "--outputDir", type=str, required=True, dest="outputDir", help="Output directory for slamdunk run.")
  411. allparser.add_argument("-5", "--trim-5p", type=int, required=False, dest="trim5", default=12, help="Number of bp removed from 5' end of all reads (default: %(default)s)")
  412. allparser.add_argument("-a", "--max-polya", type=int, required=False, dest="maxPolyA", default=4, help="Max number of As at the 3' end of a read (default: %(default)s)")
  413. allparser.add_argument("-n", "--topn", type=int, required=False, dest="topn", default=1, help="Max. number of alignments to report per read (default: %(default)s)")
  414. allparser.add_argument("-t", "--threads", type=int, required=False, default=1, dest="threads", help="Thread number (default: %(default)s)")
  415. allparser.add_argument("-q", "--quantseq", dest="quantseq", action='store_true', required=False, help="Run plain Quantseq alignment without SLAM-seq scoring")
  416. allparser.add_argument('-e', "--endtoend", action='store_true', dest="endtoend", help="Use a end to end alignment algorithm for mapping.")
  417. allparser.add_argument('-m', "--multimap", action='store_true', dest="multimap", help="Use reference to resolve multimappers (requires -n > 1).")
  418. allparser.add_argument("-mq", "--min-mq", type=int, required=False, default=2, dest="mq", help="Minimum mapping quality (default: %(default)s)")
  419. allparser.add_argument("-mi", "--min-identity", type=float, required=False, default=0.95, dest="identity", help="Minimum alignment identity (default: %(default)s)")
  420. allparser.add_argument("-nm", "--max-nm", type=int, required=False, default=-1, dest="nm", help="Maximum NM for alignments (default: %(default)s)")
  421. allparser.add_argument("-mc", "--min-coverage", required=False, dest="cov", type=int, help="Minimimum coverage to call variant (default: %(default)s)", default=10)
  422. allparser.add_argument("-mv", "--var-fraction", required=False, dest="var", type=float, help="Minimimum variant fraction to call variant (default: %(default)s)", default=0.8)
  423. allparser.add_argument("-c", "--conversion-threshold", type=int, dest="conversionThreshold", required=False, default=1,help="Number of T>C conversions required to count read as T>C read (default: %(default)d)")
  424. allparser.add_argument("-rl", "--max-read-length", type=int, required=False, dest="maxLength", help="Max read length in BAM file")
  425. allparser.add_argument("-mbq", "--min-base-qual", type=int, default=27, required=False, dest="minQual", help="Min base quality for T -> C conversions (default: %(default)d)")
  426. allparser.add_argument('-sn', "--sampleName", type=str, dest="sampleName", required = False, help="Use this sample name for all supplied samples")
  427. allparser.add_argument('-sy', "--sampleType", type=str, dest="sampleType", required = False, default = "pulse", help="Use this sample type for all supplied samples")
  428. allparser.add_argument('-st', "--sampleTime", type=int, dest="sampleTime", required = False, default = 0, help="Use this sample time for all supplied samples")
  429. allparser.add_argument("-i", "--sample-index", type=int, required=False, default=-1, dest="sampleIndex", help="Run analysis only for sample <i>. Use for distributing slamdunk analysis on a cluster (index is 1-based).")
  430. allparser.add_argument("-ss", "--skip-sam", action='store_true', dest="skipSAM", help="Output BAM while mapping. Slower but, uses less hard disk.")
  432. args = parser.parse_args()
  434. ########################################################################
  435. # Routine selection
  436. ########################################################################
  438. command = args.command
  440. if (command == "map") :
  441. mapper.checkNextGenMapVersion()
  443. outputDirectory = args.outputDir
  445. if args.sampleIndex > -1:
  446. sec = random.randrange(0,2000) / 1000
  447. message("Waiting " + str(sec) + " seconds")
  448. sleep(sec)
  450. createDir(outputDirectory)
  451. n = args.threads
  452. referenceFile = args.referenceFile
  454. samples, samplesInfos = getSamples(args.files, runOnly=args.sampleIndex)
  456. message("Running slamDunk map for " + str(len(samples)) + " files (" + str(n) + " threads)")
  457. for i in range(0, len(samples)):
  458. bam = samples[i]
  460. if not args.sampleName or len(samples) > 1:
  461. sampleName = replaceExtension(basename(bam), "", "")
  462. else :
  463. sampleName = args.sampleName
  465. sampleInfo = samplesInfos[i]
  466. if sampleInfo == "":
  467. sampleInfo = sampleName + ":" + args.sampleType + ":" + str(args.sampleTime)
  468. tid = i
  469. if args.sampleIndex > -1:
  470. tid = args.sampleIndex
  471. runMap(tid, bam, referenceFile, n, args.trim5, args.maxPolyA, args.quantseq, args.endtoend, args.topn, sampleInfo, outputDirectory, args.skipSAM)
  473. dunkFinished()
  475. if not args.skipSAM:
  476. message("Running slamDunk sam2bam for " + str(len(samples)) + " files (" + str(n) + " threads)")
  477. results = Parallel(n_jobs=1, verbose=verbose)(delayed(runSam2Bam)(tid, samples[tid], n, outputDirectory) for tid in range(0, len(samples)))
  478. dunkFinished()
  480. elif (command == "filter") :
  481. outputDirectory = args.outputDir
  482. createDir(outputDirectory)
  483. n = args.threads
  484. message("Running slamDunk filter for " + str(len(args.bam)) + " files (" + str(n) + " threads)")
  485. results = Parallel(n_jobs=n, verbose=verbose)(delayed(runFilter)(tid, args.bam[tid], args.bed, args.mq, args.identity, args.nm, outputDirectory) for tid in range(0, len(args.bam)))
  486. dunkFinished()
  488. elif (command == "snp") :
  489. outputDirectory = args.outputDir
  490. createDir(outputDirectory)
  491. fasta = args.fasta
  492. minCov = args.cov
  493. minVarFreq = args.var
  494. #minQual = args.minQual
  495. minQual = 15
  496. n = args.threads
  497. if(n > 1):
  498. n = int(n / 2)
  499. message("Running slamDunk SNP for " + str(len(args.bam)) + " files (" + str(n) + " threads)")
  500. results = Parallel(n_jobs=n, verbose=verbose)(delayed(runSnp)(tid, fasta, minCov, minVarFreq, minQual, args.bam[tid], outputDirectory) for tid in range(0, len(args.bam)))
  501. dunkFinished()
  503. elif (command == "count") :
  504. outputDirectory = args.outputDir
  505. createDir(outputDirectory)
  506. if "snpDir" in args:
  507. snpDirectory = args.snpDir
  508. else :
  509. snpDirectory = None
  510. if "vcfFile" in args:
  511. vcfFile = args.vcfFile
  512. else :
  513. vcfFile = None
  514. n = args.threads
  515. message("Running slamDunk tcount for " + str(len(args.bam)) + " files (" + str(n) + " threads)")
  516. results = Parallel(n_jobs=n, verbose=verbose)(delayed(runCount)(tid, args.bam[tid], args.ref, args.bed, args.maxLength, args.minQual, args.conversionThreshold, outputDirectory, snpDirectory, vcfFile) for tid in range(0, len(args.bam)))
  517. dunkFinished()
  519. elif (command == "all") :
  520. runAll(args)
  521. dunkFinished()
  523. else:
  524. parser.error("Too few arguments.")
  526. if __name__ == '__main__':
  527. run()

slamdunk.py at commit 14270e5, under AGPL-3.0 · at the source

Overview

Authors: Silje Lier1,2, Sara B Markusson1,2,3, Anja Kocijancic1, Martine Narum2, Solveig O Lund1,3, Bianka Böllering4, Anuja Lipsa5, Mirra L C Søegaard3,6, Idun D Rein7, Petra Santha1,3, Preeti Jain1,3, Anna Lång1,3, Emma Lång1,3, Niklas Meyer1,2, Aparajita Dutta8, Santosh Anand9, Sugith B Badugu10, Gaute J Nesse1,3, Rune J Forstrøm1,3, Arne Klungland1,3
and 10 other authorsAshish Anand11, Steven M Pollard12, Stig O Bøe1,3, Johanne E Rinholm1,2, Katrin B M Frauenknecht4,13, Anna Golebiewska5, Simone P Niclou5,14, Kumar Somyajit10, Mads Lerdrup3,6, Deo P Pandey1,3
ORCID iDs: Sara B Markusson, Anja Kocijancic, Bianka Böllering, Anuja Lipsa, Mirra L C Søegaard, Santosh Anand, Arne Klungland, Steven M Pollard, Katrin B M Frauenknecht, Anna Golebiewska, Kumar Somyajit, Mads Lerdrup, Deo P Pandey
14 affiliations
  1. Department of Microbiology, Rikshospitalet, Oslo University Hospital, Oslo, Norway
  2. Institute of Basic Medical Sciences and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
  3. CRESCO, Centre for Embryology and Healthy Development, University of Oslo, Oslo, Norway
  4. Institute of Neuropathology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
  5. NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Strassen, Luxembourg
  6. Center for Chromosome Stability, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
  7. Department of Core Facilities, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
  8. National Institute of technology, Silchar, India
  9. Division of Biological Sciences, University of Missouri, Columbia, 65211 MO USA
  10. Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark
  11. Department of Computer Science and Engineering, Indian Institute of Technology, Guwahati, Assam India
  12. Institute for Regeneration and Repair & Cancer Research UK Scotland Centre, Edinburgh, United Kingdom
  13. National Center of Pathology, Laboratoire national de santé, Dudelange, Luxembourg
  14. Department of Life Sciences and Medicine, University of Luxembourg, Belval, Luxembourg
Institutions: Oslo University Hospital (Norway); University of Oslo (Norway); Johannes Gutenberg University Mainz (Germany); University Medical Center of the Johannes Gutenberg University Mainz (Germany); Luxembourg Institute of Health (Luxembourg); University of Copenhagen (Denmark); National Institute Of Technology Silchar (India); University of Missouri (United States); University of Southern Denmark (Denmark); Indian Institute of Technology Guwahati (India); Laboratoire National de Santé (Luxembourg); University of Luxembourg (Luxembourg)
Journal: EMBO molecular medicine, volume 18, issue 5, pages 1592-1624
Dates: received 21 August 2025; accepted 9 February 2026; published online 25 March 2026; in print May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s44321-026-00393-w · PMID 41882177 · PMCID PMC13179391 · OpenAlex W7140329029
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: human (organism), mouse (organism), other condition (population), cellular / molecular (subfield)
Methods: Statistics, Machine learning, Evoked potentials, Connectivity, fMRI & imaging, Smoothing, state filtering, decompositions
Keywords: Transcriptional Addiction, Transcriptional Cycle, Transcriptional Cyclin-Dependent Kinases (tCDKs), DNA Replication, Glioblastoma, Cancer, Neuroscience
MeSH: Brain Neoplasms*, CDC2 Protein Kinase*, Cyclin-Dependent Kinases*, DNA Replication*, Glioblastoma*, Transcription Elongation, Genetic*, Animals, Cell Line, Tumor, Cyclin-Dependent Kinase-Activating Kinase, Humans, Mice, RNA Polymerase II (* major topic)
Topic: Cancer-related Molecular Pathways (Oncology, Medicine), according to OpenAlex
Funding: EC | European Health and Digital Executive Agency (HaDEA) (101156161); Norges Forskningsråd (332713); HOD | Helse Sør-Øst RHF (sorost) (HSØ 2018045,HSØ 2021037, HSØ 2024022, HSØ 2025082); UiO | Livsvitenskap, Universitetet i Oslo (SPARK Program); Danmarks Grundforskningsfond (DNRF) (DNRF115); UNIFOR; Fonds National de la Recherche Luxembourg (C20/BM/14646004/GLASS-LUX)
Citations: cited by 4 papers (Europe PMC); 76 references in the paper
Research resources: RRID:AB_2728735, RRID:AB_2728736, RRID:AB_2747403, RRID:AB_400326

Abstract

Glioblastomas are the most prevalent and aggressive malignant brain tumors, characterized by hypertranscription and dependence on neurodevelopmental transcription factors. The transcriptional cycle is regulated by phosphorylation of the C-terminal domain (CTD) of RNA polymerase II (RNAPII) by transcriptional cyclin-dependent kinases (tCDKs), including CDK7, CDK9, CDK12, and CDK13. Here we find that glioblastoma stem cells (GSCs) are selectively sensitive to CDK12/CDK13 inhibition, whereas CDK7 and CDK9 inhibition cause non-specific cytotoxicity. This selective targeting halts GSC and organoid proliferation, curtails GSC invasion and suppresses tumor growth in a xenograft mouse model. In GSCs, CDK12/CDK13 inhibition leads to a rapid and genome-wide loss of serine-2 phosphorylation (pSer2) of the RNAPII CTD, abolishing transcriptional elongation and a transcriptional program sustained by key neurodevelopmental transcription factors. CDK12/CDK13 inhibition unexpectedly arrests DNA replication and replication fork progression in a manner distinct from the effect of inhibiting other tCDKs. This dramatic arrest precedes DNA damage response activation and cell cycle arrest, directly linking RNAPII elongation to replication fork dynamics and revealing a previously unrecognized dependence of DNA replication on CDK12/CDK13-RNAPII regulation.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 3 matches between paragraphs and lines of code.

t-neumann/slamdunk

License: AGPL-3.0
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Commit: 14270e5794d36270f601a88c0bf369899d8ab4a0, 25 April 2024
Languages: Python (31), R (15), Shell (4)
Size: 73 files, 50 scripts
Software Heritage: archived
Found in: the resources table
Holds: README, license file, environment (Dockerfile, environment.yml, requirements.txt, setup.py), tests, continuous integration
Not found: CITATION.cff, documentation
Tools: pysam (8 files), ggplot2 (4 files), NumPy (4 files), BEDTools (3 files), Biopython (3 files), pandas (1 file), SAMtools (1 file)
Availability: 1 check, the latest on 30 September 2026: the link answers
  • 30 September 2026: the link answers
52 files
At the source: github.com/t-neumann/slamdunk

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 50 scripts, each with its path and the digest of its content;
  • 3 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Other data links

Data availability

The datasets produced in this study are available in the following databases: Cut&Run and SLAM-seq: NCBI’s Gene Expression Omnibus (Edgar et al, 2002), GSE186311 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE186311) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE186311).

The source data of this paper are collected in the following database record: biostudies:S-SCDT-10_1038-S44321-026-00393-w (https://www.ebi.ac.uk/biostudies/sourcedata/studies/S-SCDT-10_1038-S44321-026-00393-w).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 30 authors, 7 keywords, 12 MeSH terms, 7 funders, 76 references, 4 RRIDs.

Cite

This paper

Lier, S., Markusson, S. B., Kocijancic, A., Narum, M., Lund, S. O., Böllering, B., Lipsa, A., Søegaard, M. L. C., Rein, I. D., Santha, P., Jain, P., Lång, A., Lång, E., Meyer, N., Dutta, A., Anand, S., Badugu, S. B., Nesse, G. J., Forstrøm, R. J., . . . Pandey, D. P. (2026). CDK12/CDK13 inhibition disrupts transcriptional elongation and replication fork progression in glioblastoma. EMBO molecular medicine, 18(5), 1592-1624. https://doi.org/10.1038/s44321-026-00393-w

BibTeX

@article{lier2026cdk12,
author = {Lier, Silje and Markusson, Sara B and Kocijancic, Anja and Narum, Martine and Lund, Solveig O and Böllering, Bianka and Lipsa, Anuja and Søegaard, Mirra L C and Rein, Idun D and Santha, Petra and Jain, Preeti and Lång, Anna and Lång, Emma and Meyer, Niklas and Dutta, Aparajita and Anand, Santosh and Badugu, Sugith B and Nesse, Gaute J and Forstrøm, Rune J and Klungland, Arne and Anand, Ashish and Pollard, Steven M and Bøe, Stig O and Rinholm, Johanne E and Frauenknecht, Katrin B M and Golebiewska, Anna and Niclou, Simone P and Somyajit, Kumar and Lerdrup, Mads and Pandey, Deo P},
title = {{CDK12/CDK13 inhibition disrupts transcriptional elongation and replication fork progression in glioblastoma}},
journal = {EMBO molecular medicine},
year = {2026},
month = mar,
volume = {18},
number = {5},
pages = {1592--1624},
publisher = {Nature Publishing Group},
issn = {1757-4676},
doi = {10.1038/s44321-026-00393-w},
url = {https://doi.org/10.1038/s44321-026-00393-w},
pmid = {41882177},
pmcid = {PMC13179391}
}

RIS

TY - JOUR
AU - Lier, Silje
AU - Markusson, Sara B
AU - Kocijancic, Anja
AU - Narum, Martine
AU - Lund, Solveig O
AU - Böllering, Bianka
AU - Lipsa, Anuja
AU - Søegaard, Mirra L C
AU - Rein, Idun D
AU - Santha, Petra
AU - Jain, Preeti
AU - Lång, Anna
AU - Lång, Emma
AU - Meyer, Niklas
AU - Dutta, Aparajita
AU - Anand, Santosh
AU - Badugu, Sugith B
AU - Nesse, Gaute J
AU - Forstrøm, Rune J
AU - Klungland, Arne
AU - Anand, Ashish
AU - Pollard, Steven M
AU - Bøe, Stig O
AU - Rinholm, Johanne E
AU - Frauenknecht, Katrin B M
AU - Golebiewska, Anna
AU - Niclou, Simone P
AU - Somyajit, Kumar
AU - Lerdrup, Mads
AU - Pandey, Deo P
TI - CDK12/CDK13 inhibition disrupts transcriptional elongation and replication fork progression in glioblastoma
T2 - EMBO molecular medicine
J2 - EMBO Mol Med
PY - 2026
DA - 2026/03/25
VL - 18
IS - 5
SP - 1592
EP - 1624
SN - 1757-4676
PB - Nature Publishing Group
DO - 10.1038/s44321-026-00393-w
UR - https://doi.org/10.1038/s44321-026-00393-w
LA - en
ER -

CSL-JSON

{
"id": "10.1038/s44321-026-00393-w",
"type": "article-journal",
"title": "CDK12/CDK13 inhibition disrupts transcriptional elongation and replication fork progression in glioblastoma",
"container-title": "EMBO molecular medicine",
"author": [
{
"family": "Lier",
"given": "Silje"
},
{
"family": "Markusson",
"given": "Sara B"
},
{
"family": "Kocijancic",
"given": "Anja"
},
{
"family": "Narum",
"given": "Martine"
},
{
"family": "Lund",
"given": "Solveig O"
},
{
"family": "Böllering",
"given": "Bianka"
},
{
"family": "Lipsa",
"given": "Anuja"
},
{
"family": "Søegaard",
"given": "Mirra L C"
},
{
"family": "Rein",
"given": "Idun D"
},
{
"family": "Santha",
"given": "Petra"
},
{
"family": "Jain",
"given": "Preeti"
},
{
"family": "Lång",
"given": "Anna"
},
{
"family": "Lång",
"given": "Emma"
},
{
"family": "Meyer",
"given": "Niklas"
},
{
"family": "Dutta",
"given": "Aparajita"
},
{
"family": "Anand",
"given": "Santosh"
},
{
"family": "Badugu",
"given": "Sugith B"
},
{
"family": "Nesse",
"given": "Gaute J"
},
{
"family": "Forstrøm",
"given": "Rune J"
},
{
"family": "Klungland",
"given": "Arne"
},
{
"family": "Anand",
"given": "Ashish"
},
{
"family": "Pollard",
"given": "Steven M"
},
{
"family": "Bøe",
"given": "Stig O"
},
{
"family": "Rinholm",
"given": "Johanne E"
},
{
"family": "Frauenknecht",
"given": "Katrin B M"
},
{
"family": "Golebiewska",
"given": "Anna"
},
{
"family": "Niclou",
"given": "Simone P"
},
{
"family": "Somyajit",
"given": "Kumar"
},
{
"family": "Lerdrup",
"given": "Mads"
},
{
"family": "Pandey",
"given": "Deo P"
}
],
"container-title-short": "EMBO Mol Med",
"volume": "18",
"issue": "5",
"page": "1592-1624",
"DOI": "10.1038/s44321-026-00393-w",
"PMID": "41882177",
"PMCID": "PMC13179391",
"ISSN": "1757-4676",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s44321-026-00393-w",
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
25
]
]
}
}

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