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  • #31
    My histogram has 2 peaks in 149-150 and 200

    #Mean 166,846
    #Median 151
    #Mode 200
    #STDev 28,597
    #PercentOfPairs 16,089
    #InsertSize Count
    51 1
    57 1
    69 3
    73 1
    75 1
    76 1
    79 1
    82 2
    86 1
    87 1
    88 1
    91 1
    92 1
    95 1
    96 1
    97 1
    98 4
    101 1
    103 3
    105 1
    106 4
    107 2
    109 2
    111 3
    112 4
    113 2
    114 3
    115 9
    116 6
    117 3
    118 13
    119 3
    120 4
    121 17
    122 3
    123 8
    124 18
    125 12
    126 15
    127 16
    128 10
    129 13
    130 16
    131 8
    132 12
    133 17
    134 19
    135 16
    136 26
    137 25
    138 18
    139 48
    140 31
    141 32
    142 39
    143 35
    144 49
    145 53
    146 98
    147 160
    148 217
    149 398
    150 379
    151 240
    152 175
    153 114
    154 57
    155 32
    156 17
    157 8
    158 5
    159 2
    160 2
    161 1
    162 1
    163 1
    164 1
    165 2
    166 1
    167 3
    168 4
    169 1
    170 2
    172 5
    175 1
    176 1
    177 3
    178 4
    179 2
    180 5
    181 5
    182 4
    183 12
    184 4
    185 7
    186 3
    187 7
    188 13
    189 14
    190 15
    191 18
    192 31
    193 37
    194 52
    195 79
    196 82
    197 92
    198 267
    199 170
    200 405
    201 154
    202 52
    203 31
    204 22
    205 6
    206 3
    207 3
    208 1
    209 1
    210 2
    211 3
    214 1
    216 1
    217 3
    218 1
    221 4
    231 1
    238 1
    240 1
    241 2
    249 1
    256 1
    257 1
    260 2
    263 3
    264 2
    265 2
    266 2
    273 1
    282 3
    284 2
    286 2
    287 2
    288 2
    289 2
    290 1
    291 3
    292 1

    Comment


    • #32
      That would be very strange, for random shearing. Is it an amplicon library? If so, my previous post is irrelevant, it was based on the assumption of random shearing. Note that BBMerge can merge reads with insert size longer than read length using kmer counting, but that won't work for amplicons, only random fragmentation with sufficient coverage (>5x or so). Sometimes you can increase the merge rate by quality trimming (flags "qtrim2=r trimq=12" in BBMerge, which will only trim if the initial merge attempt fails), and for generating an insert size histogram of very low quality reads, I generally use the "xloose" flag which makes it more sensitive (at the expense of false positive merges).

      What's the read quality like? Can you post the per-base qscore histogram? (reformat.sh in=reads.fq qhist=qhist.txt).

      Comment


      • #33
        Dear Brian.

        I will continue giving you more info as soon as I get it.

        Meanwhile let my give you many thanks for your most valuable help. Besides that I want to ask you for a further help:

        Do you know any tutorial or book that I could read in order to learn thiese concepts. The bioinformatics books I have are too basic and do not treat these issues.

        Comment


        • #34
          Originally posted by bi_maniac View Post
          Do you know any tutorial or book that I could read in order to learn these concepts. The bioinformatics books I have are too basic and do not treat these issues.
          Sorry, I can't give you any advice there. Bioinformatics too rapidly-evolving now for books to be relevant for very long, I think.

          Comment


          • #35
            Hi Brian,

            It is amplicon library. Insert range is 300-370. I will send you exec reports soon.

            Comment


            • #36
              Hi, helpful people: this conversation continues here: http://seqanswers.com/forums/showthread.php?t=63930

              Thanks a lot.
              Last edited by bi_maniac; 11-02-2015, 11:55 AM.

              Comment

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