SPAdes should provide very nice results for your dataset. It will assemble your 100x using a multi k-mer approach, then it will resolve some repeats using your long MiSeq reads and it will scaffold additionally using PacBio.

http://bioinf.spbau.ru/spades

So you can use their suggested guidelines for 150bp reads:

spades.py -k 21,33,55,77 --careful <your reads> -o spades_output

You can specify pacbio as: --pacbio

Your 100x as: --pe1-1 and --pe2-1

and your single end MiSeq as --s2

Allpaths-LG can be a solution, it will perform the assembly from illumina short reads and then a scaffolding using the PacBio data.

For illumina reads, it needs a high coverage (100x), so for your case it's fine, but in other hand it needs very specific libraries (3 kbp matepair ?). You should check.

ALLPATHS‐LG requires a minimum of 2 paired‐end libraries - one short and one long. The short library average separation size must be slightly less than twice the read size, such that the reads from a pair will likely overlap - for example, for 100 base reads the insert size should be 180 bases. The distribution of sizes should be as small as possible, with a standard deviation of less than 20%. The long library insert size should be approximately 3000 bases long and can have a larger size distribution. Additional optional longer insert libraries can be used to help disambiguate larger repeat structures and may be generated at lower coverage

EDIT: Copied from the manual

You also can use MaSuRCA mega-reads.

Masurca in general gives relatively good results.

It is one of the rare real hybrid assembler (De Bruijn/OLC)

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